diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 38a49b6021..d75a64d662 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -75,6 +75,7 @@ jobs: LIBMESH: ${{ matrix.libmesh }} NPY_DISABLE_CPU_FEATURES: "AVX512F AVX512_SKX" OPENBLAS_NUM_THREADS: 1 + PYTEST_ADDOPTS: --cov=openmc --cov-report=lcov:coverage-python.lcov # libfabric complains about fork() as a result of using Python multiprocessing. # We can work around it with RDMAV_FORK_SAFE=1 in libfabric < 1.13 and with # FI_EFA_FORK_SAFE=1 in more recent versions. @@ -171,11 +172,37 @@ jobs: uses: mxschmitt/action-tmate@v3 timeout-minutes: 10 - - name: after_success + - name: Generate C++ coverage (gcovr) shell: bash run: | - cpp-coveralls -i src -i include -e src/external --exclude-pattern "/usr/*" --dump cpp_cov.json - coveralls --merge=cpp_cov.json --service=github + # Produce LCOV directly from gcov data in the build tree + gcovr \ + --root "$GITHUB_WORKSPACE" \ + --object-directory "$GITHUB_WORKSPACE/build" \ + --filter "$GITHUB_WORKSPACE/src" \ + --filter "$GITHUB_WORKSPACE/include" \ + --exclude "$GITHUB_WORKSPACE/src/external/.*" \ + --exclude "$GITHUB_WORKSPACE/src/include/openmc/external/.*" \ + --gcov-ignore-errors source_not_found \ + --gcov-ignore-errors output_error \ + --gcov-ignore-parse-errors suspicious_hits.warn \ + --print-summary \ + --lcov -o coverage-cpp.lcov || true + + - name: Merge C++ and Python coverage + shell: bash + run: | + # Merge C++ and Python LCOV into a single file for upload + cat coverage-cpp.lcov coverage-python.lcov > coverage.lcov + + - name: Upload coverage to Coveralls + if: ${{ hashFiles('coverage.lcov') != '' }} + uses: coverallsapp/github-action@v2 + with: + github-token: ${{ secrets.GITHUB_TOKEN }} + parallel: true + flag-name: C++ and Python + path-to-lcov: coverage.lcov finish: needs: main @@ -184,5 +211,5 @@ jobs: - name: Coveralls Finished uses: coverallsapp/github-action@v2 with: - github-token: ${{ secrets.github_token }} + github-token: ${{ secrets.GITHUB_TOKEN }} parallel-finished: true diff --git a/AGENTS.md b/AGENTS.md new file mode 100644 index 0000000000..32e30213ae --- /dev/null +++ b/AGENTS.md @@ -0,0 +1,280 @@ +# OpenMC AI Coding Agent Instructions + +## Project Overview + +OpenMC is a Monte Carlo particle transport code for simulating nuclear reactors, +fusion devices, or other systems with neutron/photon radiation. It's a hybrid +C++17/Python codebase where: +- **C++ core** (`src/`, `include/openmc/`) handles the computationally intensive transport simulation +- **Python API** (`openmc/`) provides user-facing model building, post-processing, and depletion capabilities +- **C API bindings** (`openmc/lib/`) wrap the C++ library via ctypes for runtime control + +## Architecture & Key Components + +### C++ Component Structure +- **Global vectors of unique_ptrs**: Core objects like `model::cells`, `model::universes`, `nuclides` are stored as `vector>` in nested namespaces (`openmc::model`, `openmc::simulation`, `openmc::settings`, `openmc::data`) +- **Custom container types**: OpenMC provides its own `vector`, `array`, `unique_ptr`, and `make_unique` in the `openmc::` namespace (defined in `vector.h`, `array.h`, `memory.h`). These are currently typedefs to `std::` equivalents but may become custom implementations for accelerator support. Always use `openmc::vector`, not `std::vector`. +- **Geometry systems**: + - **CSG (default)**: Arbitrarily complex Constructive Solid Geometry using `Surface`, `Region`, `Cell`, `Universe`, `Lattice` + - **DAGMC**: CAD-based geometry via Direct Accelerated Geometry Monte Carlo (optional, requires `OPENMC_USE_DAGMC`) + - **Unstructured mesh**: libMesh-based geometry (optional, requires `OPENMC_USE_LIBMESH`) +- **Particle tracking**: `Particle` class with `GeometryState` manages particle transport through geometry +- **Tallies**: Score quantities during simulation via `Filter` and `Tally` objects +- **Random ray solver**: Alternative deterministic method in `src/random_ray/` +- **Optional features**: DAGMC (CAD geometry), libMesh (unstructured mesh), MPI, all controlled by `#ifdef OPENMC_MPI`, etc. + +### Python Component Structure +- **ID management**: All geometry objects (Cell, Surface, Material, etc.) inherit from `IDManagerMixin` which auto-assigns unique integer IDs and tracks them via class-level `used_ids` and `next_id` +- **Input validation**: Extensive use of `openmc.checkvalue` module functions (`check_type`, `check_value`, `check_length`) for all setters +- **XML I/O**: Most classes implement `to_xml_element()` and `from_xml_element()` for serialization to OpenMC's XML input format +- **HDF5 output**: Post-simulation data in statepoint files read via `openmc.StatePoint` +- **Depletion**: `openmc.deplete` implements burnup via operator-splitting with various integrators (Predictor, CECM, etc.) +- **Nuclear Data**: `openmc.data` provides programmatic access to nuclear data files (ENDF, ACE, HDF5) + +## Critical Build & Test Workflows + +### Build Dependencies +- **C++17 compiler**: GCC, Clang, or Intel +- **CMake** (3.16+): Required for configuring and building the C++ library +- **HDF5**: Required for cross section data and output file formats +- **libpng**: Used for generating visualization when OpenMC is run in plotting mode + +Without CMake and HDF5, OpenMC cannot be compiled. + +### Building the C++ Library +```bash +# Configure with CMake (from build/ directory) +cmake .. -DOPENMC_USE_MPI=ON -DOPENMC_USE_OPENMP=ON -DCMAKE_BUILD_TYPE=RelWithDebInfo + +# Available CMake options (all default OFF except OPENMC_USE_OPENMP and OPENMC_BUILD_TESTS): +# -DOPENMC_USE_OPENMP=ON/OFF # OpenMP parallelism +# -DOPENMC_USE_MPI=ON/OFF # MPI support +# -DOPENMC_USE_DAGMC=ON/OFF # CAD geometry support +# -DOPENMC_USE_LIBMESH=ON/OFF # Unstructured mesh +# -DOPENMC_ENABLE_PROFILE=ON/OFF # Profiling flags +# -DOPENMC_ENABLE_COVERAGE=ON/OFF # Coverage analysis + +# Build +make -j + +# C++ unit tests (uses Catch2) +ctest +``` + +### Python Development +```bash +# Install in development mode (requires building C++ library first) +pip install -e . + +# Python tests (uses pytest) +pytest tests/unit_tests/ # Fast unit tests +pytest tests/regression_tests/ # Full regression suite (requires nuclear data) +``` + +### Nuclear Data Setup (CRITICAL for Running OpenMC) +Most tests require the NNDC HDF5 nuclear cross-section library. + +**Important**: Check if `OPENMC_CROSS_SECTIONS` is already set in the user's +environment before downloading, as many users already have nuclear data +installed. Though do note that if this variable is present that it may point to +different cross section data and that the NNDC data is required for tests to +pass. + +**If not already configured, download and setup:** +```bash +# Download NNDC HDF5 cross section library (~800 MB compressed) +wget -q -O - https://anl.box.com/shared/static/teaup95cqv8s9nn56hfn7ku8mmelr95p.xz | tar -C $HOME -xJ + +# Set environment variable (add to ~/.bashrc or ~/.zshrc for persistence) +export OPENMC_CROSS_SECTIONS=$HOME/nndc_hdf5/cross_sections.xml +``` + +**Alternative**: Use the provided download script (checks if data exists before downloading): +```bash +bash tools/ci/download-xs.sh # Downloads both NNDC HDF5 and ENDF/B-VII.1 data +``` + +Without this data, regression tests will fail with "No cross_sections.xml file +found" errors, or, in the case that alternative cross section data is configured +the tests will execute but will not pass. The `cross_sections.xml` file is an +index listing paths to individual HDF5 nuclear data files for each nuclide. + +## Testing Expectations + +### Environment Requirements + + - **Data**: As described above, OpenMC's test suite requires OpenMC to be configured with NNDC data. + - **OpenMP Settings**: OpenMC's tests may fail is more than two OpenMP threads are used. The environment variable `OMP_NUM_THREADS=2` should be set to avoid sporadic test failures. + - **Executable configuration**: The OpenMC executable should compiled with debug symbols enabled. + +### C++ Tests +Located in `tests/cpp_unit_tests/`, use Catch2 framework. Run via `ctest` after building with `-DOPENMC_BUILD_TESTS=ON`. + +### Python Unit Tests +Located in `tests/unit_tests/`, these are fast, standalone tests that verify Python API functionality without running full simulations. Use standard pytest patterns: + +**Categories**: +- **API validation**: Test object creation, property setters/getters, XML serialization (e.g., `test_material.py`, `test_cell.py`, `test_source.py`) +- **Data processing**: Test nuclear data handling, cross sections, depletion chains (e.g., `test_data_neutron.py`, `test_deplete_chain.py`) +- **Library bindings**: Test `openmc.lib` ctypes interface with `model.init_lib()`/`model.finalize_lib()` (e.g., `test_lib.py`) +- **Geometry operations**: Test bounding boxes, containment, lattice generation (e.g., `test_bounding_box.py`, `test_lattice.py`) + +**Common patterns**: +- Use fixtures from `tests/unit_tests/conftest.py` (e.g., `uo2`, `water`, `sphere_model`) +- Test invalid inputs with `pytest.raises(ValueError)` or `pytest.raises(TypeError)` +- Use `run_in_tmpdir` fixture for tests that create files +- Tests with `openmc.lib` require calling `model.init_lib()` in try/finally with `model.finalize_lib()` + +**Example**: +```python +def test_material_properties(): + m = openmc.Material() + m.add_nuclide('U235', 1.0) + assert 'U235' in m.nuclides + + with pytest.raises(TypeError): + m.add_nuclide('H1', '1.0') # Invalid type +``` + +Unit tests should be fast. For tests requiring simulation output, use regression tests instead. + +### Python Regression Tests +Regression tests compare OpenMC output against reference data. **Prefer using existing models from `openmc.examples` or those found in tests/unit_tests/conftest.py** (like `pwr_pin_cell()`, `pwr_assembly()`, `slab_mg()`) rather than building from scratch. + +**Test Harness Types** (in `tests/testing_harness.py`): +- **PyAPITestHarness**: Standard harness for Python API tests. Compares `inputs_true.dat` (XML hash) and `results_true.dat` (statepoint k-eff and tally values). Requires `model.xml` generation. +- **HashedPyAPITestHarness**: Like PyAPITestHarness but hashes the results for compact comparison +- **TolerantPyAPITestHarness**: For tests with floating-point non-associativity (e.g., random ray solver with single precision). Uses relative tolerance comparisons. +- **WeightWindowPyAPITestHarness**: Compares weight window bounds from `weight_windows.h5` +- **CollisionTrackTestHarness**: Compares collision track data from `collision_track.h5` against `collision_track_true.h5` +- **TestHarness**: Base harness for XML-based tests (no Python model building) +- **PlotTestHarness**: Compares plot output files (PNG or voxel HDF5) +- **CMFDTestHarness**: Specialized for CMFD acceleration tests +- **ParticleRestartTestHarness**: Tests particle restart functionality + +Almost all cases use either `PyAPITestHarness` or `HashedPyAPITestHarness` + +**Example Test**: +```python +from openmc.examples import pwr_pin_cell +from tests.testing_harness import PyAPITestHarness + +def test_my_feature(): + model = pwr_pin_cell() + model.settings.particles = 1000 # Modify to exercise feature + harness = PyAPITestHarness('statepoint.10.h5', model) + harness.main() +``` + +**Workflow**: Create `test.py` and `__init__.py` in `tests/regression_tests/my_test/`, run `pytest --update` to generate reference files (`inputs_true.dat`, `results_true.dat`, etc.), then verify with `pytest` without `--update`. Test results should be generated with a debug build (`-DCMAKE_BUILD_TYPE=Debug`) + +**Critical**: When modifying OpenMC code, regenerate affected test references with `pytest --update` and commit updated reference files. + +### Test Configuration + +`pytest.ini` sets: `python_files = test*.py`, `python_classes = NoThanks` (disables class-based test collection). + +### Testing Options + +For builds of OpenMC with MPI enabled, the `--mpi` flag should be passed to the test suite to ensure that appropriate tests are executed using two MPI processes. + +The entire test suite can be executed with OpenMC running in event-based mode (instead of the default history-based mode) by providing the `--event` flag to the `pytest` command. + +## Cross-Language Boundaries + +The C API (defined in `include/openmc/capi.h`) exposes C++ functionality to Python via ctypes bindings in `openmc/lib/`. Example: +```cpp +// C++ API in capi.h +extern "C" int openmc_run(); + +// Python binding in openmc/lib/core.py +_dll.openmc_run.restype = c_int +def run(): + _dll.openmc_run() +``` + +When modifying C++ public APIs, update corresponding ctypes signatures in `openmc/lib/*.py`. + +## Code Style & Conventions + +### C++ Style (enforced by .clang-format) + OpenMC generally tries to follow C++ core guidelines where possible + (https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines) and follow + modern C++ practices (e.g. RAII) whenever possible. + +- **Naming**: + - Classes: `CamelCase` (e.g., `HexLattice`) + - Functions/methods: `snake_case` (e.g., `get_indices`) + - Variables: `snake_case` with trailing underscore for class members (e.g., `n_particles_`, `energy_`) + - Constants: `UPPER_SNAKE_CASE` (e.g., `SQRT_PI`) +- **Namespaces**: All code in `openmc::` namespace, global state in sub-namespaces +- **Include order**: Related header first, then C/C++ stdlib, third-party libs, local headers +- **Comments**: C++-style (`//`) only, never C-style (`/* */`) +- **Standard**: C++17 features allowed +- **Formatting**: Run `clang-format` (version 15) before committing; install via `tools/dev/install-commit-hooks.sh` + +### Python Style +- **PEP8** compliant +- **Docstrings**: numpydoc format for all public functions/methods +- **Type hints**: Use sparingly, primarily for complex signatures +- **Path handling**: Use `pathlib.Path` for filesystem operations, accept `str | os.PathLike` in function arguments +- **Dependencies**: Core dependencies only (numpy, scipy, h5py, pandas, matplotlib, lxml, ipython, uncertainties, setuptools, endf). Other packages must be optional +- **Python version**: Minimum 3.11 (as of Nov 2025) + +### ID Management Pattern (Python) +When creating geometry objects, IDs can be auto-assigned or explicit: +```python +# Auto-assigned ID +cell = openmc.Cell() # Gets next available ID + +# Explicit ID +cell = openmc.Cell(id=10) # Warning if ID already used + +# Reset all IDs (useful in test fixtures) +openmc.reset_auto_ids() +``` + +### Input Validation Pattern (Python) +All setters use checkvalue functions: +```python +import openmc.checkvalue as cv + +@property +def temperature(self): + return self._temperature + +@temperature.setter +def temperature(self, temp): + cv.check_type('temperature', temp, Real) + cv.check_greater_than('temperature', temp, 0.0) + self._temperature = temp +``` + +### Working with HDF5 Files +C++ uses custom HDF5 wrappers in `src/hdf5_interface.cpp`. Python uses h5py directly. Statepoint format version is `VERSION_STATEPOINT` in `include/openmc/constants.h`. + +### Conditional Compilation +Check for optional features: +```cpp +#ifdef OPENMC_MPI + // MPI-specific code +#endif + +#ifdef OPENMC_DAGMC + // DAGMC-specific code +#endif +``` + +## Documentation + +- **User docs**: Sphinx documentation in `docs/source/` hosted at https://docs.openmc.org +- **C++ docs**: Doxygen-style comments with `\brief`, `\param` tags +- **Python docs**: numpydoc format docstrings + +## Common Pitfalls + +1. **Forgetting nuclear data**: Tests fail without `OPENMC_CROSS_SECTIONS` environment variable +2. **ID conflicts**: Python objects with duplicate IDs trigger `IDWarning`, use `reset_auto_ids()` between tests +3. **MPI builds**: Code must work with and without MPI; use `#ifdef OPENMC_MPI` guards +4. **Path handling**: Use `pathlib.Path` in new Python code, not `os.path` +5. **Clang-format version**: CI uses version 15; other versions may produce different formatting diff --git a/CITATION.cff b/CITATION.cff index 19b4213a15..ab27d89b83 100644 --- a/CITATION.cff +++ b/CITATION.cff @@ -1,9 +1,43 @@ +cff-version: 1.2.0 +message: "If you use this software, please cite it as below." +title: OpenMC +authors: +- family-names: Romano + given-names: Paul K. + orcid: "https://orcid.org/0000-0002-1147-045X" +- family-names: Shriwise + given-names: Patrick C. + orcid: "https://orcid.org/0000-0002-3979-7665" +- family-names: Shimwell + given-names: Jonathan + orcid: "https://orcid.org/0000-0001-6909-0946" +- family-names: Harper + given-names: Sterling +- family-names: Boyd + given-names: Will +- family-names: Nelson + given-names: Adam G. + orcid: "https://orcid.org/0000-0002-3614-0676" +- family-names: Tramm + given-names: John R. + orcid: "https://orcid.org/0000-0002-5397-4402" +- family-names: Ridley + given-names: Gavin + orcid: "https://orcid.org/0000-0003-1635-8042" +- family-names: Johnson + given-names: Andrew + orcid: "https://orcid.org/0000-0003-2125-8775" +- family-names: Peterson + given-names: Ethan E. + orcid: "https://orcid.org/0000-0002-5694-7194" +- family-names: Herman + given-names: Bryan R. preferred-citation: authors: - family-names: Romano given-names: Paul K. orcid: "https://orcid.org/0000-0002-1147-045X" - - final-names: Horelik + - family-names: Horelik given-names: Nicholas E. - family-names: Herman given-names: Bryan R. diff --git a/CMakeLists.txt b/CMakeLists.txt index 474451c8ae..87b8789d10 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -338,6 +338,7 @@ list(APPEND libopenmc_SOURCES src/cell.cpp src/chain.cpp src/cmfd_solver.cpp + src/collision_track.cpp src/cross_sections.cpp src/dagmc.cpp src/distribution.cpp diff --git a/cmake/OpenMCConfig.cmake.in b/cmake/OpenMCConfig.cmake.in index 3fe0c1bcd1..837a39c783 100644 --- a/cmake/OpenMCConfig.cmake.in +++ b/cmake/OpenMCConfig.cmake.in @@ -1,9 +1,12 @@ get_filename_component(OpenMC_CMAKE_DIR "${CMAKE_CURRENT_LIST_FILE}" DIRECTORY) -find_package(fmt REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../fmt) -find_package(pugixml REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../pugixml) -find_package(xtl REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../xtl) -find_package(xtensor REQUIRED HINTS ${OpenMC_CMAKE_DIR}/../xtensor) +# Compute the install prefix from this file's location +get_filename_component(_OPENMC_PREFIX "${OpenMC_CMAKE_DIR}/../../.." ABSOLUTE) + +find_package(fmt CONFIG REQUIRED HINTS ${_OPENMC_PREFIX}) +find_package(pugixml CONFIG REQUIRED HINTS ${_OPENMC_PREFIX}) +find_package(xtl CONFIG REQUIRED HINTS ${_OPENMC_PREFIX}) +find_package(xtensor CONFIG REQUIRED HINTS ${_OPENMC_PREFIX}) if(@OPENMC_USE_DAGMC@) find_package(DAGMC REQUIRED HINTS @DAGMC_DIR@) endif() diff --git a/docs/source/capi/index.rst b/docs/source/capi/index.rst index d9ac0d1e01..2583d51dff 100644 --- a/docs/source/capi/index.rst +++ b/docs/source/capi/index.rst @@ -84,6 +84,17 @@ Functions :return: Return status (negative if an error occurred) :rtype: int +.. c:function:: int openmc_cell_get_density(int32_t index, const int32_t* instance, double* density) + + Get the density of a cell + + :param int32_t index: Index in the cells array + :param int32_t* instance: Which instance of the cell. If a null pointer is passed, the density + multiplier of the first instance is returned. + :param double* density: Density of the cell in [g/cm3] + :return: Return status (negative if an error occurred) + :rtype: int + .. c:function:: int openmc_cell_set_fill(int32_t index, int type, int32_t n, const int32_t* indices) Set the fill for a cell @@ -113,8 +124,22 @@ Functions :param double T: Temperature in Kelvin :param instance: Which instance of the cell. To set the temperature for all instances, pass a null pointer. - :param set_contained: If the cell is not filled by a material, whether to set the temperatures - of all filled cells + :param bool set_contained: If the cell is not filled by a material, whether + to set the temperatures of all filled cells + :type instance: const int32_t* + :return: Return status (negative if an error occurred) + :rtype: int + +.. c:function:: int openmc_cell_set_density(index index, double density, const int32_t* instance, bool set_contained) + + Set the density of a cell. + + :param int32_t index: Index in the cells array + :param double density: Density of the cell in [g/cm3] + :param instance: Which instance of the cell. To set the density multiplier for all + instances, pass a null pointer. + :param bool set_contained: If the cell is not filled by a material, whether + to set the density multiplier of all filled cells :type instance: const int32_t* :return: Return status (negative if an error occurred) :rtype: int diff --git a/docs/source/conf.py b/docs/source/conf.py index 8aeff5cdc7..826c20022a 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -121,9 +121,7 @@ pygments_style = 'tango' # -- Options for HTML output --------------------------------------------------- # The theme to use for HTML and HTML Help pages -import sphinx_rtd_theme html_theme = 'sphinx_rtd_theme' -html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] html_baseurl = "https://docs.openmc.org/en/stable/" html_logo = '_images/openmc_logo.png' diff --git a/docs/source/devguide/policies.rst b/docs/source/devguide/policies.rst index 2cf3199876..3644ae8223 100644 --- a/docs/source/devguide/policies.rst +++ b/docs/source/devguide/policies.rst @@ -21,8 +21,8 @@ C++ code in OpenMC must conform to the most recent C++ standard that is fully supported in the `version of the gcc compiler `_ that is distributed with the oldest version of Ubuntu that is still within its `standard support period -`_. Ubuntu 20.04 LTS will be supported -through April 2025 and is distributed with gcc 9.3.0, which fully supports the +`_. Ubuntu 22.04 LTS will be supported +through April 2027 and is distributed with gcc 11.4.0, which fully supports the C++17 standard. -------------------- @@ -31,5 +31,5 @@ CMake Version Policy Similar to the C++ standard policy, the minimum supported version of CMake corresponds to whatever version is distributed with the oldest version of Ubuntu -still within its standard support period. Ubuntu 20.04 LTS is distributed with -CMake 3.16. +still within its standard support period. Ubuntu 22.04 LTS is distributed with +CMake 3.22. diff --git a/docs/source/io_formats/collision_track.rst b/docs/source/io_formats/collision_track.rst new file mode 100644 index 0000000000..a364597544 --- /dev/null +++ b/docs/source/io_formats/collision_track.rst @@ -0,0 +1,46 @@ +.. _io_collision_track: + +=========================== +Collision Track File Format +=========================== + +When collision tracking is enabled with ``mcpl=false`` (the default), OpenMC +writes binary data to an HDF5 file named ``collision_track.h5``. The same data +may also be written after each batch when multiple files are requested +(``collision_track.N.h5``) or when the run is performed in parallel. The file +contains the information needed to reconstruct each recorded collision. + +The current revision of the collision track file format is 1.0. + +**/** + +:Attributes: + - **filetype** (*char[]*) -- String indicating the type of file. + For collision-track files the value is ``"collision_track"``. + +:Datasets: + + - **collision_track_bank** (Compound type) -- Collision information + for each stored event. Each entry in the dataset corresponds to one + collision and contains the following fields: + + - ``r`` (*double[3]*) -- Position of the collision in [cm]. + - ``u`` (*double[3]*) -- Direction unit vector immediately after the collision. + - ``E`` (*double*) -- Incident particle energy before the collision in [eV]. + - ``dE`` (*double*) -- Energy loss over the collision (:math:`E_\text{before} - E_\text{after}`) in [eV]. + - ``time`` (*double*) -- Time of the collision in [s]. + - ``wgt`` (*double*) -- Particle weight at the collision. + - ``event_mt`` (*int*) -- ENDF MT number identifying the reaction. + - ``delayed_group`` (*int*) -- Delayed neutron group index (non-zero for delayed events). + - ``cell_id`` (*int*) -- ID of the cell in which the collision occurred. + - ``nuclide_id`` (*int*) -- ZA identifier of the nuclide (ZZZAAAM format). + - ``material_id`` (*int*) -- ID of the material containing the collision site. + - ``universe_id`` (*int*) -- ID of the universe containing the collision site. + - ``n_collision`` (*int*) -- Collision counter for the particle history. + - ``particle`` (*int*) -- Particle type (0=neutron, 1=photon, 2=electron, 3=positron). + - ``parent_id`` (*int64*) -- Unique ID of the parent particle. + - ``progeny_id`` (*int64*) -- Progeny ID of the particle. + +In an MPI run, OpenMC writes the combined dataset by gathering collision-track +entries from all ranks before flushing them to disk, so the final file appears +as though it were produced serially. diff --git a/docs/source/io_formats/depletion_chain.rst b/docs/source/io_formats/depletion_chain.rst index 89c76525f8..74413e7b61 100644 --- a/docs/source/io_formats/depletion_chain.rst +++ b/docs/source/io_formats/depletion_chain.rst @@ -56,6 +56,27 @@ attributes: .. _io_chain_reaction: +-------------------- +```` Element +-------------------- + +The ```` element represents photon and electron sources associated with +the decay of a nuclide and contains information to construct an +:class:`openmc.stats.Univariate` object that represents this emission as an +energy distribution. This element has the following attributes: + + :type: + The type of :class:`openmc.stats.Univariate` source term. + + :particle: + The type of particle emitted, e.g., 'photon' or 'electron' + + :parameters: + The parameters of the source term, e.g., for a + :class:`openmc.stats.Discrete` source, the energies (in [eV]) at which the + particles are emitted and their relative intensities in [Bq/atom] (in other + words, decay constants). + ---------------------- ```` Element ---------------------- diff --git a/docs/source/io_formats/depletion_results.rst b/docs/source/io_formats/depletion_results.rst index 7035fc9c9e..b2a726dad0 100644 --- a/docs/source/io_formats/depletion_results.rst +++ b/docs/source/io_formats/depletion_results.rst @@ -4,7 +4,7 @@ Depletion Results File Format ============================= -The current version of the depletion results file format is 1.1. +The current version of the depletion results file format is 1.2. **/** @@ -12,22 +12,20 @@ The current version of the depletion results file format is 1.1. - **version** (*int[2]*) -- Major and minor version of the statepoint file format. -:Datasets: - **eigenvalues** (*double[][][2]*) -- k-eigenvalues at each - time/stage. This array has shape (number of timesteps, number of - stages, value). The last axis contains the eigenvalue and the - associated uncertainty - - **number** (*double[][][][]*) -- Total number of atoms. This array - has shape (number of timesteps, number of stages, number of +:Datasets: - **eigenvalues** (*double[][2]*) -- k-eigenvalues at each timestep. + This array has shape (number of timesteps, 2). The second axis + contains the eigenvalue and its associated uncertainty. + - **number** (*double[][][]*) -- Total number of atoms at each + timestep. This array has shape (number of timesteps, number of materials, number of nuclides). - - **reaction rates** (*double[][][][][]*) -- Reaction rates used to - build depletion matrices. This array has shape (number of - timesteps, number of stages, number of materials, number of - nuclides, number of reactions). + - **reaction rates** (*double[][][][]*) -- Reaction rates at each + timestep. This array has shape (number of timesteps, number of + materials, number of nuclides, number of reactions). Only stored if + write_rates=True. - **time** (*double[][2]*) -- Time in [s] at beginning/end of each step. - - **source_rate** (*double[][]*) -- Power in [W] or source rate in - [neutron/sec]. This array has shape (number of timesteps, number - of stages). + - **source_rate** (*double[]*) -- Power in [W] or source rate in + [neutron/sec] for each timestep. - **depletion time** (*double[]*) -- Average process time in [s] spent depleting a material across all burnable materials and, if applicable, MPI processes. diff --git a/docs/source/io_formats/geometry.rst b/docs/source/io_formats/geometry.rst index 2947502196..cd5b243fea 100644 --- a/docs/source/io_formats/geometry.rst +++ b/docs/source/io_formats/geometry.rst @@ -38,11 +38,9 @@ Each ```` element can have the following attributes or sub-elements: :boundary: The boundary condition for the surface. This can be "transmission", - "vacuum", "reflective", or "periodic". Periodic boundary conditions can - only be applied to x-, y-, and z-planes. Only axis-aligned periodicity is - supported, i.e., x-planes can only be paired with x-planes. Specify which - planes are periodic and the code will automatically identify which planes - are paired together. + "vacuum", "reflective", or "periodic". Specify which planes are + periodic and the code will automatically identify which planes are + paired together. *Default*: "transmission" diff --git a/docs/source/io_formats/index.rst b/docs/source/io_formats/index.rst index 4bbaa961a6..5b4efea669 100644 --- a/docs/source/io_formats/index.rst +++ b/docs/source/io_formats/index.rst @@ -44,6 +44,7 @@ Output Files statepoint source + collision_track summary properties depletion_results diff --git a/docs/source/io_formats/properties.rst b/docs/source/io_formats/properties.rst index 5030e78f35..4cc5da379b 100644 --- a/docs/source/io_formats/properties.rst +++ b/docs/source/io_formats/properties.rst @@ -4,7 +4,7 @@ Properties File Format ====================== -The current version of the properties file format is 1.0. +The current version of the properties file format is 1.1. **/** @@ -25,6 +25,7 @@ The current version of the properties file format is 1.0. **/geometry/cells/cell /** :Datasets: - **temperature** (*double[]*) -- Temperature of the cell in [K]. + - **density** (*double[]*) -- Density of the cell in [g/cm3]. **/materials/** diff --git a/docs/source/io_formats/settings.rst b/docs/source/io_formats/settings.rst index 26673faac2..b7874fcf2f 100644 --- a/docs/source/io_formats/settings.rst +++ b/docs/source/io_formats/settings.rst @@ -20,6 +20,85 @@ source neutrons. *Default*: None +----------------------------- +```` Element +----------------------------- + +The ```` element indicates to track information about particle +collisions based on a set of criteria and store these events in a file named +``collision_track.h5``. This file records details such as the position of the +interaction, direction of the incoming particle, incident energy and deposited +energy, weight, time of the interaction, and the delayed neutron group (0 for +prompt neutrons). Additional information such as the cell ID, material ID, +universe ID, nuclide ZAID, particle type, and event MT number are also stored. +Users can specify one or more criterion to filter collisions. If no criteria are +specified, it defaults to tracking all collisions across the model. + +.. warning:: + Storing all collisions can be very memory intensive. For more targeted + tracking, users can employ a variety of parameters such as ``cell_ids``, + ``reactions``, ``universe_ids``, ``material_ids``, ``nuclides``, and + ``deposited_E_threshold`` to refine the selection of particle interactions + to be banked. + +This element can contain one or more of the following attributes or +sub-elements: + + :max_collisions: + An integer indicating the maximum number of collisions to be banked per file. + + *Default*: 1000 + + :max_collision_track_files: + An integer indicating the number of collision_track files to be used. + + *Default*: 1 + + :mcpl: + An optional boolean to enable MCPL_-format instead of the native HDF5-based + format. If activated, the output file name and type is changed to + ``collision_track.mcpl``. + + *Default*: false + + .. _MCPL: https://mctools.github.io/mcpl/mcpl.pdf + + :cell_ids: + A list of integers representing cell IDs to define specific cells in which + collisions are to be banked. + + *Default*: None + + :universe_ids: + A list of integers representing the universe IDs to define specific + universes in which collisions are to be banked. + + *Default*: None + + :material_ids: + A list of integers representing the material IDs to define specific + materials in which collisions are to be banked. + + *Default*: None + + :nuclides: + A list of strings representing the nuclide, to define specific + define specific target nuclide collisions to be banked. + + *Default*: None + + :reactions: + A list of integers representing the ENDF-6 format MT numbers or strings + (e.g. (n,fission)) to define specific reaction types to be banked. + + *Default*: None + + :deposited_E_threshold: + A float defining the minimum deposited energy per collision (in eV) to + trigger banking. + + *Default*: 0.0 + ---------------------------------- ```` Element ---------------------------------- @@ -178,6 +257,16 @@ history-based parallelism. *Default*: false +-------------------------------- +```` Element +-------------------------------- + +The ```` element specifies the energy multiplier, expressed +in units of :math:`kT`, that determines when the free gas scattering approach is +used for elastic scattering. Values must be positive. + + *Default*: 400.0 + ----------------------------------- ```` Element ----------------------------------- diff --git a/docs/source/io_formats/statepoint.rst b/docs/source/io_formats/statepoint.rst index 3b10317696..2309643dc8 100644 --- a/docs/source/io_formats/statepoint.rst +++ b/docs/source/io_formats/statepoint.rst @@ -149,6 +149,8 @@ The current version of the statepoint file format is 18.1. tallies will have a value of 0 unless otherwise instructed. - **multiply_density** (*int*) -- Flag indicating whether reaction rates should be multiplied by atom density (1) or not (0). + - **higher_moments** (*int*) -- Flag indicating whether + higher-order tally moments are enabled (1) or not (0). :Datasets: - **n_realizations** (*int*) -- Number of realizations. - **n_filters** (*int*) -- Number of filters used. diff --git a/docs/source/io_formats/summary.rst b/docs/source/io_formats/summary.rst index 7d3ab94d9f..64ca68b9c3 100644 --- a/docs/source/io_formats/summary.rst +++ b/docs/source/io_formats/summary.rst @@ -4,7 +4,7 @@ Summary File Format =================== -The current version of the summary file format is 6.0. +The current version of the summary file format is 6.1. **/** @@ -38,6 +38,7 @@ The current version of the summary file format is 6.0. is an array if the cell uses distributed materials, otherwise it is a scalar. - **temperature** (*double[]*) -- Temperature of the cell in Kelvin. + - **density** (*double[]*) -- Density of the cell in [g/cm3]. - **translation** (*double[3]*) -- Translation applied to the fill universe. This dataset is present only if fill_type is set to 'universe'. diff --git a/docs/source/methods/charged_particles_physics.rst b/docs/source/methods/charged_particles_physics.rst new file mode 100644 index 0000000000..5d763074fd --- /dev/null +++ b/docs/source/methods/charged_particles_physics.rst @@ -0,0 +1,362 @@ +.. _methods_charged_particle_physics: + +======================== +Charged Particle Physics +======================== + +OpenMC neglects the spatial transport of charged particles (electrons and +positrons), assuming they deposit all their energy locally and produce +bremsstrahlung photons at their birth location. This approximation, called +thick-target bremsstrahlung (TTB) approximation is justified by the fact that +charged particles have much shorter stopping ranges compared to neutrons and +photons, especially in high-density materials. + +----------------------------- +Charged Particle Interactions +----------------------------- + +Bremsstrahlung +-------------- + +When a charged particle is decelerated in the field of an atom, some of its +kinetic energy is converted into electromagnetic radiation known as +bremsstrahlung, or 'braking radiation'. In each event, an electron or positron +with kinetic energy :math:`T` generates a photon with an energy :math:`E` +between :math:`0` and :math:`T`. Bremsstrahlung is described by a cross section +that is differential in photon energy, in the direction of the emitted photon, +and in the final direction of the charged particle. However, in Monte Carlo +simulations it is typical to integrate over the angular variables to obtain a +single differential cross section with respect to photon energy, which is often +expressed in the form + +.. math:: + :label: bremsstrahlung-dcs + + \frac{d\sigma_{\text{br}}}{dE} = \frac{Z^2}{\beta^2} \frac{1}{E} + \chi(Z, T, \kappa), + +where :math:`\kappa = E/T` is the reduced photon energy and :math:`\chi(Z, T, +\kappa)` is the scaled bremsstrahlung cross section, which is experimentally +measured. + +Because electrons are attracted to atomic nuclei whereas positrons are +repulsed, the cross section for positrons is smaller, though it approaches that +of electrons in the high energy limit. To obtain the positron cross section, we +multiply :eq:`bremsstrahlung-dcs` by the :math:`\kappa`-independent factor used +in Salvat_, + +.. math:: + :label: positron-factor + + \begin{aligned} + F_{\text{p}}(Z,T) = + & 1 - \text{exp}(-1.2359\times 10^{-1}t + 6.1274\times 10^{-2}t^2 - 3.1516\times 10^{-2}t^3 \\ + & + 7.7446\times 10^{-3}t^4 - 1.0595\times 10^{-3}t^5 + 7.0568\times 10^{-5}t^6 \\ + & - 1.8080\times 10^{-6}t^7), + \end{aligned} + +where + +.. math:: + :label: positron-factor-t + + t = \ln\left(1 + \frac{10^6}{Z^2}\frac{T}{\text{m}_\text{e}c^2} \right). + +:math:`F_{\text{p}}(Z,T)` is the ratio of the radiative stopping powers for +positrons and electrons. Stopping power describes the average energy loss per +unit path length of a charged particle as it passes through matter: + +.. math:: + :label: stopping-power + + -\frac{dT}{ds} = n \int E \frac{d\sigma}{dE} dE \equiv S(T), + +where :math:`n` is the number density of the material and :math:`d\sigma/dE` is +the cross section differential in energy loss. The total stopping power +:math:`S(T)` can be separated into two components: the radiative stopping +power :math:`S_{\text{rad}}(T)`, which refers to energy loss due to +bremsstrahlung, and the collision stopping power :math:`S_{\text{col}}(T)`, +which refers to the energy loss due to inelastic collisions with bound +electrons in the material that result in ionization and excitation. The +radiative stopping power for electrons is given by + +.. math:: + :label: radiative-stopping-power + + S_{\text{rad}}(T) = n \frac{Z^2}{\beta^2} T \int_0^1 \chi(Z,T,\kappa) + d\kappa. + + +To obtain the radiative stopping power for positrons, +:eq:`radiative-stopping-power` is multiplied by :eq:`positron-factor`. + +While the models for photon interactions with matter described above can safely +assume interactions occur with free atoms, sampling the target atom based on +the macroscopic cross sections, molecular effects cannot necessarily be +disregarded for charged particle treatment. For compounds and mixtures, the +bremsstrahlung cross section is calculated using Bragg's additivity rule as + +.. math:: + :label: material-bremsstrahlung-dcs + + \frac{d\sigma_{\text{br}}}{dE} = \frac{1}{\beta^2 E} \sum_i \gamma_i Z^2_i + \chi(Z_i, T, \kappa), + +where the sum is over the constituent elements and :math:`\gamma_i` is the +atomic fraction of the :math:`i`-th element. Similarly, the radiative stopping +power is calculated using Bragg's additivity rule as + +.. math:: + :label: material-radiative-stopping-power + + S_{\text{rad}}(T) = \sum_i w_i S_{\text{rad},i}(T), + +where :math:`w_i` is the mass fraction of the :math:`i`-th element and +:math:`S_{\text{rad},i}(T)` is found for element :math:`i` using +:eq:`radiative-stopping-power`. The collision stopping power, however, is a +function of certain quantities such as the mean excitation energy :math:`I` and +the density effect correction :math:`\delta_F` that depend on molecular +properties. These quantities cannot simply be summed over constituent elements +in a compound, but should instead be calculated for the material. The Bethe +formula can be used to find the collision stopping power of the material: + +.. math:: + :label: material-collision-stopping-power + + S_{\text{col}}(T) = \frac{2 \pi r_e^2 m_e c^2}{\beta^2} N_A \frac{Z}{A_M} + [\ln(T^2/I^2) + \ln(1 + \tau/2) + F(\tau) - \delta_F(T)], + +where :math:`N_A` is Avogadro's number, :math:`A_M` is the molar mass, +:math:`\tau = T/m_e`, and :math:`F(\tau)` depends on the particle type. For +electrons, + +.. math:: + :label: F-electron + + F_{-}(\tau) = (1 - \beta^2)[1 + \tau^2/8 - (2\tau + 1) \ln2], + +while for positrons + +.. math:: + :label: F-positron + + F_{+}(\tau) = 2\ln2 - (\beta^2/12)[23 + 14/(\tau + 2) + 10/(\tau + 2)^2 + + 4/(\tau + 2)^3]. + +The density effect correction :math:`\delta_F` takes into account the reduction +of the collision stopping power due to the polarization of the material the +charged particle is passing through by the electric field of the particle. +It can be evaluated using the method described by Sternheimer_, where the +equation for :math:`\delta_F` is + +.. math:: + :label: density-effect-correction + + \delta_F(\beta) = \sum_{i=1}^n f_i \ln[(l_i^2 + l^2)/l_i^2] - + l^2(1-\beta^2). + +Here, :math:`f_i` is the oscillator strength of the :math:`i`-th transition, +given by :math:`f_i = n_i/Z`, where :math:`n_i` is the number of electrons in +the :math:`i`-th subshell. The frequency :math:`l` is the solution of the +equation + +.. math:: + :label: density-effect-l + + \frac{1}{\beta^2} - 1 = \sum_{i=1}^{n} \frac{f_i}{\bar{\nu}_i^2 + l^2}, + +where :math:`\bar{v}_i` is defined as + +.. math:: + :label: density-effect-nubar + + \bar{\nu}_i = h\nu_i \rho / h\nu_p. + +The plasma energy :math:`h\nu_p` of the medium is given by + +.. math:: + :label: plasma-frequency + + h\nu_p = \sqrt{\frac{(hc)^2 r_e \rho_m N_A Z}{\pi A}}, + +where :math:`A` is the atomic weight and :math:`\rho_m` is the density of the +material. In :eq:`density-effect-nubar`, :math:`h\nu_i` is the oscillator +energy, and :math:`\rho` is an adjustment factor introduced to give agreement +between the experimental values of the oscillator energies and the mean +excitation energy. The :math:`l_i` in :eq:`density-effect-correction` are +defined as + +.. math:: + :label: density-effect-li + + \begin{aligned} + l_i &= (\bar{\nu}_i^2 + 2/3f_i)^{1/2} ~~~~&\text{for}~~ \bar{\nu}_i > 0 \\ + l_n &= f_n^{1/2} ~~~~&\text{for}~~ \bar{\nu}_n = 0, + \end{aligned} + +where the second case applies to conduction electrons. For a conductor, +:math:`f_n` is given by :math:`n_c/Z`, where :math:`n_c` is the effective +number of conduction electrons, and :math:`v_n = 0`. The adjustment factor +:math:`\rho` is determined using the equation for the mean excitation energy: + +.. math:: + :label: mean-excitation-energy + + \ln I = \sum_{i=1}^{n-1} f_i \ln[(h\nu_i\rho)^2 + 2/3f_i(h\nu_p)^2]^{1/2} + + f_n \ln (h\nu_pf_n^{1/2}). + +.. _ttb: + + +Thick-Target Bremsstrahlung Approximation ++++++++++++++++++++++++++++++++++++++++++ + +Since charged particles lose their energy on a much shorter distance scale than +neutral particles, not much error should be introduced by neglecting to +transport electrons. However, the bremsstrahlung emitted from high energy +electrons and positrons can travel far from the interaction site. Thus, even +without a full electron transport mode it is necessary to model bremsstrahlung. +We use a thick-target bremsstrahlung (TTB) approximation based on the models in +Salvat_ and Kaltiaisenaho_ for generating bremsstrahlung photons, which assumes +the charged particle loses all its energy in a single homogeneous material +region. + +To model bremsstrahlung using the TTB approximation, we need to know the number +of photons emitted by the charged particle and the energy distribution of the +photons. These quantities can be calculated using the continuous slowing down +approximation (CSDA). The CSDA assumes charged particles lose energy +continuously along their trajectory with a rate of energy loss equal to the +total stopping power, ignoring fluctuations in the energy loss. The +approximation is useful for expressing average quantities that describe how +charged particles slow down in matter. For example, the CSDA range approximates +the average path length a charged particle travels as it slows to rest: + +.. math:: + :label: csda-range + + R(T) = \int^T_0 \frac{dT'}{S(T')}. + +Actual path lengths will fluctuate around :math:`R(T)`. The average number of +photons emitted per unit path length is given by the inverse bremsstrahlung +mean free path: + +.. math:: + :label: inverse-bremsstrahlung-mfp + + \lambda_{\text{br}}^{-1}(T,E_{\text{cut}}) + = n\int_{E_{\text{cut}}}^T\frac{d\sigma_{\text{br}}}{dE}dE + = n\frac{Z^2}{\beta^2}\int_{\kappa_{\text{cut}}}^1\frac{1}{\kappa} + \chi(Z,T,\kappa)d\kappa. + +The lower limit of the integral in :eq:`inverse-bremsstrahlung-mfp` is non-zero +because the bremsstrahlung differential cross section diverges for small photon +energies but is finite for photon energies above some cutoff energy +:math:`E_{\text{cut}}`. The mean free path +:math:`\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})` is used to calculate the +photon number yield, defined as the average number of photons emitted with +energy greater than :math:`E_{\text{cut}}` as the charged particle slows down +from energy :math:`T` to :math:`E_{\text{cut}}`. The photon number yield is +given by + +.. math:: + :label: photon-number-yield + + Y(T,E_{\text{cut}}) = \int^{R(T)}_{R(E_{\text{cut}})} + \lambda_{\text{br}}^{-1}(T',E_{\text{cut}})ds = \int_{E_{\text{cut}}}^T + \frac{\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})}{S(T')}dT'. + +:math:`Y(T,E_{\text{cut}})` can be used to construct the energy spectrum of +bremsstrahlung photons: the number of photons created with energy between +:math:`E_1` and :math:`E_2` by a charged particle with initial kinetic energy +:math:`T` as it comes to rest is given by :math:`Y(T,E_1) - Y(T,E_2)`. + +To simulate the emission of bremsstrahlung photons, the total stopping power +and bremsstrahlung differential cross section for positrons and electrons must +be calculated for a given material using :eq:`material-bremsstrahlung-dcs` and +:eq:`material-radiative-stopping-power`. These quantities are used to build the +tabulated bremsstrahlung energy PDF and CDF for that material for each incident +energy :math:`T_k` on the energy grid. The following algorithm is then applied +to sample the photon energies: + +1. For an incident charged particle with energy :math:`T`, sample the number of + emitted photons as + + .. math:: + + N = \lfloor Y(T,E_{\text{cut}}) + \xi_1 \rfloor. + +2. Rather than interpolate the PDF between indices :math:`k` and :math:`k+1` + for which :math:`T_k < T < T_{k+1}`, which is computationally expensive, use + the composition method and sample from the PDF at either :math:`k` or + :math:`k+1`. Using linear interpolation on a logarithmic scale, the PDF can + be expressed as + + .. math:: + + p_{\text{br}}(T,E) = \pi_k p_{\text{br}}(T_k,E) + \pi_{k+1} + p_{\text{br}}(T_{k+1},E), + + where the interpolation weights are + + .. math:: + + \pi_k = \frac{\ln T_{k+1} - \ln T}{\ln T_{k+1} - \ln T_k},~~~ + \pi_{k+1} = \frac{\ln T - \ln T_k}{\ln T_{k+1} - \ln T_k}. + + Sample either the index :math:`i = k` or :math:`i = k+1` according to the + point probabilities :math:`\pi_{k}` and :math:`\pi_{k+1}`. + +3. Determine the maximum value of the CDF :math:`P_{\text{br,max}}`. + +3. Sample the photon energies using the inverse transform method with the + tabulated CDF :math:`P_{\text{br}}(T_i, E)` i.e., + + .. math:: + + E = E_j \left[ (1 + a_j) \frac{\xi_2 P_{\text{br,max}} - + P_{\text{br}}(T_i, E_j)} {E_j p_{\text{br}}(T_i, E_j)} + 1 + \right]^{\frac{1}{1 + a_j}} + + where the interpolation factor :math:`a_j` is given by + + .. math:: + + a_j = \frac{\ln p_{\text{br}}(T_i,E_{j+1}) - \ln p_{\text{br}}(T_i,E_j)} + {\ln E_{j+1} - \ln E_j} + + and :math:`P_{\text{br}}(T_i, E_j) \le \xi_2 P_{\text{br,max}} \le + P_{\text{br}}(T_i, E_{j+1})`. + +We ignore the range of the electron or positron, i.e., the bremsstrahlung +photons are produced in the same location that the charged particle was +created. The direction of the photons is assumed to be the same as the +direction of the incident charged particle, which is a reasonable approximation +at higher energies when the bremsstrahlung radiation is emitted at small +angles. + + +Electron-Positron Annihilation +------------------------------ + +When a positron collides with an electron, both particles are annihilated and +generally two photons with equal energy are created. If the kinetic energy of +the positron is high enough, the two photons can have different energies, and +the higher-energy photon is emitted preferentially in the direction of flight +of the positron. It is also possible to produce a single photon if the +interaction occurs with a bound electron, and in some cases three (or, rarely, +even more) photons can be emitted. However, the annihilation cross section is +largest for low-energy positrons, and as the positron energy decreases, the +angular distribution of the emitted photons becomes isotropic. + +In OpenMC, we assume the most likely case in which a low-energy positron (which +has already lost most of its energy to bremsstrahlung radiation) interacts with +an electron which is free and at rest. Two photons with energy equal to the +electron rest mass energy :math:`m_e c^2 = 0.511` MeV are emitted isotropically +in opposite directions. + + +.. _Kaltiaisenaho: https://aaltodoc.aalto.fi/bitstream/handle/123456789/21004/master_Kaltiaisenaho_Toni_2016.pdf + +.. _Salvat: https://doi.org/10.1787/32da5043-en + +.. _Sternheimer: https://doi.org/10.1103/PhysRevB.26.6067 diff --git a/docs/source/methods/index.rst b/docs/source/methods/index.rst index 75c421c877..121d04b1de 100644 --- a/docs/source/methods/index.rst +++ b/docs/source/methods/index.rst @@ -14,6 +14,7 @@ Theory and Methodology random_numbers neutron_physics photon_physics + charged_particles_physics tallies eigenvalue depletion @@ -21,4 +22,4 @@ Theory and Methodology parallelization cmfd variance_reduction - random_ray \ No newline at end of file + random_ray diff --git a/docs/source/methods/neutron_physics.rst b/docs/source/methods/neutron_physics.rst index fe8b8ad850..2b797e3dbc 100644 --- a/docs/source/methods/neutron_physics.rst +++ b/docs/source/methods/neutron_physics.rst @@ -290,7 +290,10 @@ create and store fission sites for the following generation. First, the average number of prompt and delayed neutrons must be determined to decide whether the secondary neutrons will be prompt or delayed. This is important because delayed neutrons have a markedly different spectrum from prompt neutrons, one that has a -lower average energy of emission. The total number of neutrons emitted +lower average energy of emission. Furthermore, in simulations where tracking +time of neutrons is important, we need to consider the emission time delay of +the secondary neutrons, which is dependent on the decay constant of the +delayed neutron precursor. The total number of neutrons emitted :math:`\nu_t` is given as a function of incident energy in the ENDF format. Two representations exist for :math:`\nu_t`. The first is a polynomial of order :math:`N` with coefficients :math:`c_0,c_1,\dots,c_N`. If :math:`\nu_t` has this @@ -306,8 +309,8 @@ interpolation law. The number of prompt neutrons released per fission event :math:`\nu_p` is also given as a function of incident energy and can be specified in a polynomial or tabular format. The number of delayed neutrons released per fission event :math:`\nu_d` can only be specified in a tabular -format. In practice, we only need to determine :math:`nu_t` and -:math:`nu_d`. Once these have been determined, we can calculated the delayed +format. In practice, we only need to determine :math:`\nu_t` and +:math:`\nu_d`. Once these have been determined, we can calculate the delayed neutron fraction .. math:: @@ -335,8 +338,14 @@ neutrons. Otherwise, we produce :math:`\lfloor \nu \rfloor + 1` neutrons. Then, for each fission site produced, we sample the outgoing angle and energy according to the algorithms given in :ref:`sample-angle` and :ref:`sample-energy` respectively. If the neutron is to be born delayed, then -there is an extra step of sampling a delayed neutron precursor group since they -each have an associated secondary energy distribution. +there is an extra step of sampling a delayed neutron precursor group to get the +associated secondary energy distribution and the decay constant +:math:`\lambda`, which is needed to sample the emission delay time :math:`t_d`: + +.. math:: + :label: sample-delay-time + + t_d = -\frac{\ln \xi}{\lambda}. The sampled outgoing angle and energy of fission neutrons along with the position of the collision site are stored in an array called the fission diff --git a/docs/source/methods/photon_physics.rst b/docs/source/methods/photon_physics.rst index 22d2c7f26a..d2bd3ac760 100644 --- a/docs/source/methods/photon_physics.rst +++ b/docs/source/methods/photon_physics.rst @@ -667,342 +667,6 @@ and Auger electrons: 5. Repeat from step 1 for vacancy left by the transition electron. -Electron-Positron Annihilation ------------------------------- - -When a positron collides with an electron, both particles are annihilated and -generally two photons with equal energy are created. If the kinetic energy of -the positron is high enough, the two photons can have different energies, and -the higher-energy photon is emitted preferentially in the direction of flight -of the positron. It is also possible to produce a single photon if the -interaction occurs with a bound electron, and in some cases three (or, rarely, -even more) photons can be emitted. However, the annihilation cross section is -largest for low-energy positrons, and as the positron energy decreases, the -angular distribution of the emitted photons becomes isotropic. - -In OpenMC, we assume the most likely case in which a low-energy positron (which -has already lost most of its energy to bremsstrahlung radiation) interacts with -an electron which is free and at rest. Two photons with energy equal to the -electron rest mass energy :math:`m_e c^2 = 0.511` MeV are emitted isotropically -in opposite directions. - -Bremsstrahlung --------------- - -When a charged particle is decelerated in the field of an atom, some of its -kinetic energy is converted into electromagnetic radiation known as -bremsstrahlung, or 'braking radiation'. In each event, an electron or positron -with kinetic energy :math:`T` generates a photon with an energy :math:`E` -between :math:`0` and :math:`T`. Bremsstrahlung is described by a cross section -that is differential in photon energy, in the direction of the emitted photon, -and in the final direction of the charged particle. However, in Monte Carlo -simulations it is typical to integrate over the angular variables to obtain a -single differential cross section with respect to photon energy, which is often -expressed in the form - -.. math:: - :label: bremsstrahlung-dcs - - \frac{d\sigma_{\text{br}}}{dE} = \frac{Z^2}{\beta^2} \frac{1}{E} - \chi(Z, T, \kappa), - -where :math:`\kappa = E/T` is the reduced photon energy and :math:`\chi(Z, T, -\kappa)` is the scaled bremsstrahlung cross section, which is experimentally -measured. - -Because electrons are attracted to atomic nuclei whereas positrons are -repulsed, the cross section for positrons is smaller, though it approaches that -of electrons in the high energy limit. To obtain the positron cross section, we -multiply :eq:`bremsstrahlung-dcs` by the :math:`\kappa`-independent factor used -in Salvat_, - -.. math:: - :label: positron-factor - - \begin{aligned} - F_{\text{p}}(Z,T) = - & 1 - \text{exp}(-1.2359\times 10^{-1}t + 6.1274\times 10^{-2}t^2 - 3.1516\times 10^{-2}t^3 \\ - & + 7.7446\times 10^{-3}t^4 - 1.0595\times 10^{-3}t^5 + 7.0568\times 10^{-5}t^6 \\ - & - 1.8080\times 10^{-6}t^7), - \end{aligned} - -where - -.. math:: - :label: positron-factor-t - - t = \ln\left(1 + \frac{10^6}{Z^2}\frac{T}{\text{m}_\text{e}c^2} \right). - -:math:`F_{\text{p}}(Z,T)` is the ratio of the radiative stopping powers for -positrons and electrons. Stopping power describes the average energy loss per -unit path length of a charged particle as it passes through matter: - -.. math:: - :label: stopping-power - - -\frac{dT}{ds} = n \int E \frac{d\sigma}{dE} dE \equiv S(T), - -where :math:`n` is the number density of the material and :math:`d\sigma/dE` is -the cross section differential in energy loss. The total stopping power -:math:`S(T)` can be separated into two components: the radiative stopping -power :math:`S_{\text{rad}}(T)`, which refers to energy loss due to -bremsstrahlung, and the collision stopping power :math:`S_{\text{col}}(T)`, -which refers to the energy loss due to inelastic collisions with bound -electrons in the material that result in ionization and excitation. The -radiative stopping power for electrons is given by - -.. math:: - :label: radiative-stopping-power - - S_{\text{rad}}(T) = n \frac{Z^2}{\beta^2} T \int_0^1 \chi(Z,T,\kappa) - d\kappa. - - -To obtain the radiative stopping power for positrons, -:eq:`radiative-stopping-power` is multiplied by :eq:`positron-factor`. - -While the models for photon interactions with matter described above can safely -assume interactions occur with free atoms, sampling the target atom based on -the macroscopic cross sections, molecular effects cannot necessarily be -disregarded for charged particle treatment. For compounds and mixtures, the -bremsstrahlung cross section is calculated using Bragg's additivity rule as - -.. math:: - :label: material-bremsstrahlung-dcs - - \frac{d\sigma_{\text{br}}}{dE} = \frac{1}{\beta^2 E} \sum_i \gamma_i Z^2_i - \chi(Z_i, T, \kappa), - -where the sum is over the constituent elements and :math:`\gamma_i` is the -atomic fraction of the :math:`i`-th element. Similarly, the radiative stopping -power is calculated using Bragg's additivity rule as - -.. math:: - :label: material-radiative-stopping-power - - S_{\text{rad}}(T) = \sum_i w_i S_{\text{rad},i}(T), - -where :math:`w_i` is the mass fraction of the :math:`i`-th element and -:math:`S_{\text{rad},i}(T)` is found for element :math:`i` using -:eq:`radiative-stopping-power`. The collision stopping power, however, is a -function of certain quantities such as the mean excitation energy :math:`I` and -the density effect correction :math:`\delta_F` that depend on molecular -properties. These quantities cannot simply be summed over constituent elements -in a compound, but should instead be calculated for the material. The Bethe -formula can be used to find the collision stopping power of the material: - -.. math:: - :label: material-collision-stopping-power - - S_{\text{col}}(T) = \frac{2 \pi r_e^2 m_e c^2}{\beta^2} N_A \frac{Z}{A_M} - [\ln(T^2/I^2) + \ln(1 + \tau/2) + F(\tau) - \delta_F(T)], - -where :math:`N_A` is Avogadro's number, :math:`A_M` is the molar mass, -:math:`\tau = T/m_e`, and :math:`F(\tau)` depends on the particle type. For -electrons, - -.. math:: - :label: F-electron - - F_{-}(\tau) = (1 - \beta^2)[1 + \tau^2/8 - (2\tau + 1) \ln2], - -while for positrons - -.. math:: - :label: F-positron - - F_{+}(\tau) = 2\ln2 - (\beta^2/12)[23 + 14/(\tau + 2) + 10/(\tau + 2)^2 + - 4/(\tau + 2)^3]. - -The density effect correction :math:`\delta_F` takes into account the reduction -of the collision stopping power due to the polarization of the material the -charged particle is passing through by the electric field of the particle. -It can be evaluated using the method described by Sternheimer_, where the -equation for :math:`\delta_F` is - -.. math:: - :label: density-effect-correction - - \delta_F(\beta) = \sum_{i=1}^n f_i \ln[(l_i^2 + l^2)/l_i^2] - - l^2(1-\beta^2). - -Here, :math:`f_i` is the oscillator strength of the :math:`i`-th transition, -given by :math:`f_i = n_i/Z`, where :math:`n_i` is the number of electrons in -the :math:`i`-th subshell. The frequency :math:`l` is the solution of the -equation - -.. math:: - :label: density-effect-l - - \frac{1}{\beta^2} - 1 = \sum_{i=1}^{n} \frac{f_i}{\bar{\nu}_i^2 + l^2}, - -where :math:`\bar{v}_i` is defined as - -.. math:: - :label: density-effect-nubar - - \bar{\nu}_i = h\nu_i \rho / h\nu_p. - -The plasma energy :math:`h\nu_p` of the medium is given by - -.. math:: - :label: plasma-frequency - - h\nu_p = \sqrt{\frac{(hc)^2 r_e \rho_m N_A Z}{\pi A}}, - -where :math:`A` is the atomic weight and :math:`\rho_m` is the density of the -material. In :eq:`density-effect-nubar`, :math:`h\nu_i` is the oscillator -energy, and :math:`\rho` is an adjustment factor introduced to give agreement -between the experimental values of the oscillator energies and the mean -excitation energy. The :math:`l_i` in :eq:`density-effect-correction` are -defined as - -.. math:: - :label: density-effect-li - - \begin{aligned} - l_i &= (\bar{\nu}_i^2 + 2/3f_i)^{1/2} ~~~~&\text{for}~~ \bar{\nu}_i > 0 \\ - l_n &= f_n^{1/2} ~~~~&\text{for}~~ \bar{\nu}_n = 0, - \end{aligned} - -where the second case applies to conduction electrons. For a conductor, -:math:`f_n` is given by :math:`n_c/Z`, where :math:`n_c` is the effective -number of conduction electrons, and :math:`v_n = 0`. The adjustment factor -:math:`\rho` is determined using the equation for the mean excitation energy: - -.. math:: - :label: mean-excitation-energy - - \ln I = \sum_{i=1}^{n-1} f_i \ln[(h\nu_i\rho)^2 + 2/3f_i(h\nu_p)^2]^{1/2} + - f_n \ln (h\nu_pf_n^{1/2}). - -.. _ttb: - -Thick-Target Bremsstrahlung Approximation -+++++++++++++++++++++++++++++++++++++++++ - -Since charged particles lose their energy on a much shorter distance scale than -neutral particles, not much error should be introduced by neglecting to -transport electrons. However, the bremsstrahlung emitted from high energy -electrons and positrons can travel far from the interaction site. Thus, even -without a full electron transport mode it is necessary to model bremsstrahlung. -We use a thick-target bremsstrahlung (TTB) approximation based on the models in -Salvat_ and Kaltiaisenaho_ for generating bremsstrahlung photons, which assumes -the charged particle loses all its energy in a single homogeneous material -region. - -To model bremsstrahlung using the TTB approximation, we need to know the number -of photons emitted by the charged particle and the energy distribution of the -photons. These quantities can be calculated using the continuous slowing down -approximation (CSDA). The CSDA assumes charged particles lose energy -continuously along their trajectory with a rate of energy loss equal to the -total stopping power, ignoring fluctuations in the energy loss. The -approximation is useful for expressing average quantities that describe how -charged particles slow down in matter. For example, the CSDA range approximates -the average path length a charged particle travels as it slows to rest: - -.. math:: - :label: csda-range - - R(T) = \int^T_0 \frac{dT'}{S(T')}. - -Actual path lengths will fluctuate around :math:`R(T)`. The average number of -photons emitted per unit path length is given by the inverse bremsstrahlung -mean free path: - -.. math:: - :label: inverse-bremsstrahlung-mfp - - \lambda_{\text{br}}^{-1}(T,E_{\text{cut}}) - = n\int_{E_{\text{cut}}}^T\frac{d\sigma_{\text{br}}}{dE}dE - = n\frac{Z^2}{\beta^2}\int_{\kappa_{\text{cut}}}^1\frac{1}{\kappa} - \chi(Z,T,\kappa)d\kappa. - -The lower limit of the integral in :eq:`inverse-bremsstrahlung-mfp` is non-zero -because the bremsstrahlung differential cross section diverges for small photon -energies but is finite for photon energies above some cutoff energy -:math:`E_{\text{cut}}`. The mean free path -:math:`\lambda_{\text{br}}^{-1}(T,E_{\text{cut}})` is used to calculate the -photon number yield, defined as the average number of photons emitted with -energy greater than :math:`E_{\text{cut}}` as the charged particle slows down -from energy :math:`T` to :math:`E_{\text{cut}}`. The photon number yield is -given by - -.. math:: - :label: photon-number-yield - - Y(T,E_{\text{cut}}) = \int^{R(T)}_{R(E_{\text{cut}})} - \lambda_{\text{br}}^{-1}(T',E_{\text{cut}})ds = \int_{E_{\text{cut}}}^T - \frac{\lambda_{\text{br}}^{-1}(T',E_{\text{cut}})}{S(T')}dT'. - -:math:`Y(T,E_{\text{cut}})` can be used to construct the energy spectrum of -bremsstrahlung photons: the number of photons created with energy between -:math:`E_1` and :math:`E_2` by a charged particle with initial kinetic energy -:math:`T` as it comes to rest is given by :math:`Y(T,E_1) - Y(T,E_2)`. - -To simulate the emission of bremsstrahlung photons, the total stopping power -and bremsstrahlung differential cross section for positrons and electrons must -be calculated for a given material using :eq:`material-bremsstrahlung-dcs` and -:eq:`material-radiative-stopping-power`. These quantities are used to build the -tabulated bremsstrahlung energy PDF and CDF for that material for each incident -energy :math:`T_k` on the energy grid. The following algorithm is then applied -to sample the photon energies: - -1. For an incident charged particle with energy :math:`T`, sample the number of - emitted photons as - - .. math:: - - N = \lfloor Y(T,E_{\text{cut}}) + \xi_1 \rfloor. - -2. Rather than interpolate the PDF between indices :math:`k` and :math:`k+1` - for which :math:`T_k < T < T_{k+1}`, which is computationally expensive, use - the composition method and sample from the PDF at either :math:`k` or - :math:`k+1`. Using linear interpolation on a logarithmic scale, the PDF can - be expressed as - - .. math:: - - p_{\text{br}}(T,E) = \pi_k p_{\text{br}}(T_k,E) + \pi_{k+1} - p_{\text{br}}(T_{k+1},E), - - where the interpolation weights are - - .. math:: - - \pi_k = \frac{\ln T_{k+1} - \ln T}{\ln T_{k+1} - \ln T_k},~~~ - \pi_{k+1} = \frac{\ln T - \ln T_k}{\ln T_{k+1} - \ln T_k}. - - Sample either the index :math:`i = k` or :math:`i = k+1` according to the - point probabilities :math:`\pi_{k}` and :math:`\pi_{k+1}`. - -3. Determine the maximum value of the CDF :math:`P_{\text{br,max}}`. - -3. Sample the photon energies using the inverse transform method with the - tabulated CDF :math:`P_{\text{br}}(T_i, E)` i.e., - - .. math:: - - E = E_j \left[ (1 + a_j) \frac{\xi_2 P_{\text{br,max}} - - P_{\text{br}}(T_i, E_j)} {E_j p_{\text{br}}(T_i, E_j)} + 1 - \right]^{\frac{1}{1 + a_j}} - - where the interpolation factor :math:`a_j` is given by - - .. math:: - - a_j = \frac{\ln p_{\text{br}}(T_i,E_{j+1}) - \ln p_{\text{br}}(T_i,E_j)} - {\ln E_{j+1} - \ln E_j} - - and :math:`P_{\text{br}}(T_i, E_j) \le \xi_2 P_{\text{br,max}} \le - P_{\text{br}}(T_i, E_{j+1})`. - -We ignore the range of the electron or positron, i.e., the bremsstrahlung -photons are produced in the same location that the charged particle was -created. The direction of the photons is assumed to be the same as the -direction of the incident charged particle, which is a reasonable approximation -at higher energies when the bremsstrahlung radiation is emitted at small -angles. .. _photon_production: @@ -1070,5 +734,3 @@ emitted photon. .. _Kaltiaisenaho: https://aaltodoc.aalto.fi/bitstream/handle/123456789/21004/master_Kaltiaisenaho_Toni_2016.pdf .. _Salvat: https://doi.org/10.1787/32da5043-en - -.. _Sternheimer: https://doi.org/10.1103/PhysRevB.26.6067 diff --git a/docs/source/methods/tallies.rst b/docs/source/methods/tallies.rst index 79a63fbdd8..27a3f873ab 100644 --- a/docs/source/methods/tallies.rst +++ b/docs/source/methods/tallies.rst @@ -387,6 +387,101 @@ of this is that the longer you run a simulation, the better you know your results. Therefore, by running a simulation long enough, it is possible to reduce the stochastic uncertainty to arbitrarily low levels. +Skewness +++++++++ + +The `skewness`_ of a population quantifies the asymmetry of the probability +distribution around its mean. Positive and negative skewness indicate a +longer/heavier right and left tail respectively. Let :math:`x_1,\ldots,x_n` be +the per-realization values for a bin, with sample mean :math:`\bar{x}` and +sample central moments: + +.. math:: + + m_k \;=\; \frac{1}{n}\sum_{i=1}^{n}\bigl(x_i-\bar{x}\bigr)^k. + +OpenMC reports the *adjusted Fisher-Pearson skewness* (defined for :math:`n \ge +3`), which is commonly used in many statistical packages: + +.. math:: + + G_1 \;=\; \frac{\sqrt{n \cdot (n-1)}}{\,n-2\,}\cdot\frac{m_3}{m_2^{3/2}}. + +where :math:`m_2` and :math:`m_3` correspond to the biased sample second and +third central moment respectively. + +Kurtosis +++++++++ + +The `kurtosis`_ of a population quantifies tail weight (also called tailedness) +of the probability distribution relative to a normal distribution. Positive +excess kurtosis indicates *heavier tails* whereas negative excess kurtosis +indicates *lighter tails*. Kurtosis is especially useful for identifying bins +where occasional extreme scores dominate uncertainty. OpenMC reports the +*adjusted excess kurtosis* (defined for :math:`n \ge 4`): + +.. math:: + + G_2 \;=\; \frac{(n-1)}{(n-2)(n-3)} + \left[(n+1)\,\frac{m_4}{m_2^{2}} \;-\; 3(n-1)\right]. + +where :math:`m_2` and :math:`m_4` correspond to the biased sample second and +fourth central moment respectively. For a perfectly normal distribution, the +excess kurtosis is :math:`0`. + +Variance of Variance +++++++++++++++++++++ + +The variance of the variance (also known as the coefficient of variation +squared) measures *stability of the sample variance* :math:`s^2` and, by +extension, the reliability of reported relative errors. High VOV means that +error bars themselves are noisy—often due to heavy tails, skewness, or too few +realizations. + +.. math:: + + VOV = \frac{s^2(s_{\bar{X}}^2)}{s_{\bar{X}}^4 } = \frac{m_4}{m_2^2} - \frac{1}{n} + +where :math:`s_{\bar{X}}^2` is the estimated variance of the mean and +:math:`s^2(s_{\bar{X}}^2)` is the estimated variance in :math:`s_{\bar{X}}^2`. +The MCNP manual suggests a hard threshold such that :math:`VOV < 0.1` to improve +the probability of forming a reliable confidence interval. However, OpenMC does +not enforce an universal cut-off because the suitability of any single threshold +depends strongly on problem specifics (estimator choice, variance-reduction +settings, tally binning, or even effective sample size). + + +Normality Tests (D'Agostino-Pearson) +++++++++++++++++++++++++++++++++++++ + +These normality test verify the hypothesis that fluctuations are *approximately +normal*, a working assumption behind many Monte Carlo diagnostics and +`confidence-interval heuristics`_. Tests are provided for: (i) skewness-only, +(ii) kurtosis-only, and (iii) the *omnibus* combination. OpenMC uses the +finite-sample-adjusted skewness :math:`G_1` and excess kurtosis :math:`G_2` +above to construct standardized normal scores :math:`Z_1` (from :math:`G_1`) and +:math:`Z_2` (from :math:`G_2`) via the D'Agostino-Pearson transformations. The +omnibus statistic is + +.. math:: + + K^2 \;=\; Z_1^{\,2} \;+\; Z_2^{\,2} + \;\sim\; \chi^2_{(2)} \quad \text{under } H_0:\ \text{normality}. + +OpenMC reports :math:`Z_1`, :math:`Z_2`, :math:`K^2`, and their p-values when +prerequisites are met (skewness for :math:`n\ge 3`, kurtosis and omnibus for +:math:`n\ge 4`). Given a user-chosen significance level :math:`\alpha` (default +is :math:`0.05`), reject :math:`H_0` if :math:`\text{p-value}<\alpha`; otherwise +fail to reject. OpenMC leaves the interpretation to the user, who should +consider VOV together with skewness, kurtosis, and normality tests results when +judging whether reported confidence intervals are credible for their application +[#norm-tests]_. + +.. [#norm-tests] + Higher-moments accumulation must be enabled with ``higher_moments = True`` + for running these diagnostics including the skewness, kurtosis, and normality + tests. + Figure of Merit +++++++++++++++ @@ -405,14 +500,16 @@ defined as .. math:: :label: relative_error - r = \frac{s_\bar{X}}{\bar{x}}. + r = \frac{s_{\bar{X}}}{\bar{x}}. Based on this definition, one can see that a higher FOM is desirable. The FOM is useful as a comparative tool. For example, if a variance reduction technique is being applied to a simulation, the FOM with variance reduction can be compared to the FOM without variance reduction to ascertain whether the reduction in variance outweighs the potential increase in execution time (e.g., due to -particle splitting). +particle splitting). It is important to note that MCNP reports the FOM using CPU +time (wall-clock time multiplied by the number of threads/cores), whereas OpenMC +reports the FOM using only the wall-clock time :math:`t`. Confidence Intervals ++++++++++++++++++++ @@ -521,6 +618,8 @@ improve the estimate of the percentile. .. rubric:: References +.. _confidence-interval heuristics: https://doi.org/10.1080/00031305.1990.10475751 + .. _following approximation: https://doi.org/10.1080/03610918708812641 .. _Bessel's correction: https://en.wikipedia.org/wiki/Bessel's_correction @@ -541,6 +640,10 @@ improve the estimate of the percentile. .. _converges in distribution: https://en.wikipedia.org/wiki/Convergence_of_random_variables#Convergence_in_distribution +.. _skewness: https://en.wikipedia.org/wiki/Skewness + +.. _kurtosis: https://en.wikipedia.org/wiki/Kurtosis + .. _confidence intervals: https://en.wikipedia.org/wiki/Confidence_interval .. _Student's t-distribution: https://en.wikipedia.org/wiki/Student%27s_t-distribution diff --git a/docs/source/pythonapi/base.rst b/docs/source/pythonapi/base.rst index 2a9d0876cd..dea8c4427c 100644 --- a/docs/source/pythonapi/base.rst +++ b/docs/source/pythonapi/base.rst @@ -176,7 +176,8 @@ Geometry Plotting :nosignatures: :template: myclass.rst - openmc.Plot + openmc.SlicePlot + openmc.VoxelPlot openmc.WireframeRayTracePlot openmc.SolidRayTracePlot openmc.Plots @@ -216,6 +217,9 @@ Post-processing :nosignatures: :template: myfunction.rst + openmc.read_collision_track_file + openmc.read_collision_track_hdf5 + openmc.read_collision_track_mcpl openmc.voxel_to_vtk The following classes and functions are used for functional expansion reconstruction. diff --git a/docs/source/pythonapi/deplete.rst b/docs/source/pythonapi/deplete.rst index f112cf8ccf..25fcd898f4 100644 --- a/docs/source/pythonapi/deplete.rst +++ b/docs/source/pythonapi/deplete.rst @@ -287,6 +287,16 @@ the following abstract base classes: abc.SIIntegrator abc.DepSystemSolver +R2S Automation +-------------- + +.. autosummary:: + :toctree: generated + :nosignatures: + :template: myclass.rst + + R2SManager + D1S Functions ------------- diff --git a/docs/source/releasenotes/0.15.3.rst b/docs/source/releasenotes/0.15.3.rst new file mode 100644 index 0000000000..c509581047 --- /dev/null +++ b/docs/source/releasenotes/0.15.3.rst @@ -0,0 +1,226 @@ +==================== +What's New in 0.15.3 +==================== + +.. currentmodule:: openmc + +------- +Summary +------- + +This release of OpenMC includes many bug fixes, performance improvements, and +several notable new features. The major highlights of this release include a new +:class:`~openmc.deplete.R2SManager` class that automates the workflow for +rigorous 2-step (R2S) shutdown dose rate calculations, the ability to collect +higher moments for tally results that can be used to test normality, a new +uncertainty-aware criticality search method, a new collision tracking feature +that enables detailed tracking of particle interactions, support for distributed +cell densities, and several new tally filters. The random ray solver also +continues to receive significant updates, including automatic setup +capabilities, improved geometry handling, and better weight window support. +Depletion capabilities have been expanded with thermochemical redox control, +external transfer rates, and improved performance. + +------------------------------------ +Compatibility Notes and Deprecations +------------------------------------ + +MCPL has been changed from a build-time dependency to a runtime optional +dependency, which means OpenMC will attempt to load the MCPL library at +runtime when needed rather than requiring it at build time. + +The ``openmc.mgxs.Library.add_to_tallies_file`` method has been renamed to +:meth:`openmc.mgxs.Library.add_to_tallies`. + +------------ +New Features +------------ + +- A new collision tracking feature enables detailed tracking of particle + interactions (`#3417 `_) +- Added :meth:`~openmc.model.Model.keff_search` method for automated criticality + searches (`#3569 `_) +- Introduced automated workflow for mesh- or cell-based R2S calculations + (`#3508 `_) +- Ability to source electron/positrons directly for charged particle + simulations (`#3404 `_) +- Multi-group capability for kinetics parameter calculations with Iterated + Fission Probability (`#3425 + `_) +- Introduced a new :class:`openmc.MeshMaterialFilter` class (`#3406 + `_) +- Added support for distributed cell densities (`#3546 + `_) +- Implemented a :class:`openmc.WeightWindowsList` class that enables export to + HDF5 (`#3456 `_) +- Added :meth:`openmc.Material.mean_free_path` method (`#3469 + `_) +- Introduced :func:`openmc.lib.TemporarySession` context manager (`#3475 + `_) +- Added material depletion function for tracking individual material depletion + (`#3420 `_) +- Added methods on :class:`~openmc.Material` class for waste disposal rating / + classification (`#3366 `_, + `#3376 `_) +- Support for thermochemical redox control transfer rates in depletion + (`#2783 `_) +- Support for external transfer rates source term in depletion (`#3088 + `_) +- Added combing capability for fission site sampling and delayed neutron + emission time (`#2992 `_) +- Ability to specify reference direction for azimuthal angle in + :class:`~openmc.stats.PolarAzimuthal` distribution (`#3582 + `_) +- Allow spatial constraints on element sources within + :class:`~openmc.MeshSource` (`#3431 + `_) +- Added VTK HDF (.vtkhdf) format support for writing VTK data (`#3252 + `_) +- Implemented filter weight capability (`#3345 + `_) +- Optionally collect higher moments for tallies (`#3363 + `_) +- Several random ray solver enhancements: + + - Random Ray AutoMagic Setup for automatic configuration (`#3351 `_) + - Point source locator for random ray mode (`#3360 `_) + - Support for DAGMC geometries (`#3374 `_) + - Optimized mapping of source regions to tallies (`#3465 `_) + - Base source region refactor (`#3576 `_) + +--------------------------- +Bug Fixes and Small Changes +--------------------------- + +- Add two MPI barriers in R2S workflow (`#3646 `_) +- Fix a few warnings, rename add_to_tallies_file (`#3639 `_) +- Fix typo in DAGMC lost particle test (`#3634 `_) +- Avoid multiprocessing Pool when running depletion tests with MPI (`#3633 `_) +- Support MPI parallelism in R2SManager (`#3632 `_) +- Update documentation for particle tracks (`#3627 `_) +- Adding variance of variance and normality tests for tally statistics (`#3454 `_) +- Avoid divide-by-zero in ``from_multigroup_flux`` when flux is zero (`#3624 `_) +- Write particle states as separate lines in track VTK files (`#3628 `_) +- Reset DAGMC history when reviving from source (`#3601 `_) +- Add energy group structure: SCALE-999 (`#3564 `_) +- Fix bug in normalization of tally results with no_reduce (`#3619 `_) +- Enable nuclide filters with get_decay_photon_energy (`#3614 `_) +- Update ``check_type`` calls to accept both ``str`` and ``os.PathLike`` objects (`#3618 `_) +- Speed up ``apply_time_correction`` by reducing file I/O and deepcopies (`#3617 `_) +- FW-CADIS Disregard Max Realizations Setting (`#3616 `_) +- Random Ray Geometry Debug Mode Fix (`#3615 `_) +- Don't write reaction rates in depletion results by default (`#3609 `_) +- Allow Path objects in MGXSLibrary.export_to_hdf5 (`#3608 `_) +- Clip mixture distributions based on mean times integral (`#3603 `_) +- Allow V0 in atomic_mass function (for ENDF/B-VII.0 data) (`#3607 `_) +- Re-run flaky tests when needed (`#3604 `_) +- Ability to load mesh objects from weight_windows.h5 file (`#3598 `_) +- Switch to using coveralls github action for reporting (`#3594 `_) +- Add user setting for free gas threshold (`#3593 `_) +- Speed up time correction factors (`#3592 `_) +- Fix caching issue when using NCrystal materials (`#3538 `_) +- Fix random ray source region mesh export when using model.export_to_xml() (`#3579 `_) +- Ensure weight_windows_file information is read from XML (`#3587 `_) +- Add missing documentation on in depletion chain file format (`#3590 `_) +- Adding tally filter type option to statepoint get_tally (`#3584 `_) +- Optional separation of mesh-material-volume calc from get_homogenized_materials (`#3581 `_) +- Fix IFP implementation (`#3580 `_) +- Remove several TODOs related to C++17 support (`#3574 `_) +- Fix performance regression in libMesh unstructured mesh tallies (`#3577 `_) +- Update find_package calls in OpenMCConfig.cmake (`#3572 `_) +- Ensure ``n_dimension_`` attribute is set for unstructured meshes (`#3575 `_) +- Allow newer Sphinx version and fix docbuild warnings (`#3571 `_) +- Fixed a bug when combining TimeFilter, MeshFilter, and tracklength estimator (`#3525 `_) +- PowerLaw raises an error if sampling interval contains negative values (`#3542 `_) +- depletion: fix performance of chain matrix construction (`#3567 `_) +- Do not apply boundary conditions when initialized in volume calculation mode (`#3562 `_) +- Bump up tolerance for flaky activation test (`#3560 `_) +- Fixed a bug in plotting cross sections with S(a,b) data (`#3558 `_) +- Change test order to run unit tests first (`#3533 `_) +- adding ecco 33 (`#3556 `_) +- Refactor endf_data to be a fixture (`#3539 `_) +- Revert "fix broken CI" (`#3554 `_) +- fix broken CI (`#3551 `_) +- Leverage particle.move_distance in event advance (`#3544 `_) +- fix tests that accidentaly got broken (`#3543 `_) +- not printing nuclides with 0 percent to terminal (option 2 ) (`#3448 `_) +- Fix a bug in time cutoff behavior (`#3526 `_) +- Avoid duplicate materials written to XML (`#3536 `_) +- Use cached property for openmc.data.Decay.sources (`#3535 `_) +- more helpful error message for dose_coefficients (`#3534 `_) +- Adding 616 group structure (`#3531 `_) +- Remove unused special accessors for tallies (`#3527 `_) +- Consistent XML parsing using functions from _xml module (`#3517 `_) +- Add stat:sum field to MCPL files for proper weight normalization (`#3522 `_) +- Remove reorder_attributes from openmc._xml (`#3519 `_) +- fixed a bug in MeshMaterialFilter.from_volumes (`#3520 `_) +- Fixed a bug in distribcell offsets logic (`#3424 `_) +- Add test for FW-CADIS based WW generation on a DAGMC model (`#3504 `_) +- Fix for Weight Window Scaling Bug (`#3511 `_) +- Fix: ``materials``, ``plots``, and ``tallies`` cannot be passed as lists (`#3513 `_) +- Allow already-initialized openmc.lib in TemporarySession (`#3505 `_) +- Update DAGMC and libMesh precompiler definitions (`#3510 `_) +- Avoid adding ParentNuclideFilter twice when calling prepare_tallies (`#3506 `_) +- Enabling MCPL source files to be read when using surf_source_read (`#3472 `_) +- Boundary info accessors (`#3496 `_) +- automatically finding appropriate dimension when making regular mesh from domain (`#3468 `_) +- Add accessor methods for LocalCoord (`#3494 `_) +- Make MCPL a Runtime Optional Dependency (`#3429 `_) +- Use auto-chunking for StepResult HDF5 writing (`#3498 `_) +- Provide a way to get ID maps from plot parameters on the Model class (`#3481 `_) +- Update OSX install instructions to point to x64 platform (`#3501 `_) +- Update conda install instructions for macOS Apple silicon (`#3488 `_) +- Only show warning if in restart mode (`#3478 `_) +- Add flag to CMakeLists to use submodules instead of searching (`#3480 `_) +- Added citation metadata file (`#3409 `_) +- fix zam parsing (`#3484 `_) +- Support flux collapse method in ``get_microxs_and_flux`` (`#3466 `_) +- Stabilize Adjoint Source (`#3476 `_) +- Refactor and Harden Configuration Management (`#3461 `_) +- Updated Docs to Not Give Specific Python Version Requirement (`#3473 `_) +- Parallelization of Weight Window Update (`#3467 `_) +- Limit Random Ray Weight Window Generation to Final Batch (`#3464 `_) +- Fix Dockerfile DAGMC build (`#3463 `_) +- Fix Weight Window Infinite Loop Bug (`#3457 `_) +- Weight Window Birth Scaling (`#3459 `_) +- Adding checks to geometry.plot to avoid material name overlaps (`#3458 `_) +- Fixing crash when calling Geometry.plot when DAGMCUniverse in geometry (`#3455 `_) +- fixing expansion of elemental Ta bug (`#3443 `_) +- Prevent Adjoint Sources from Trending towards Infinity (`#3449 `_) +- adding plot function to DAGMCUnvierse (`#3451 `_) +- Allow specifying number of equiprobable angles for thermal scattering data generation (`#3346 `_) +- Change Dockerfile from debian:bookworm-slim to ubuntu:24.04 (`#3442 `_) +- Fix Resetting of Auto IDs When Generating MGXS (`#3437 `_) +- Allowing chain_file to be chain object to save reloading time (`#3436 `_) +- update units for flux (`#3441 `_) +- Fix raytrace infinite loop (`#3423 `_) +- Apply Max Number of Events Check to Random Rays (`#3438 `_) +- Add user setting for source rejection fraction (`#3433 `_) +- Adding fix and tests for spherical mesh as spatial distribution (`#3428 `_) +- Random Ray Missed Cell Policy Change for Adjoint Mode (`#3434 `_) +- Random Ray External Source Plotting Fix (`#3430 `_) +- Avoid negative heating values during pair production and bremsstrahlung (`#3426 `_) +- Fix no serialization of periodic_surface_id bug (`#3421 `_) +- Update _get_start_data to always grab the beginning of timestep time (`#3414 `_) +- Fixed a bug in charged particle energy deposition (`#3416 `_) +- Fix bug where the same mesh is written multiple times to settings.xml (`#3418 `_) +- small typo - spelling of Debian (`#3411 `_) +- added test for dagmc geometry plot (`#3375 `_) +- Random Ray Misc Memory Error Fixes (`#3405 `_) +- added type hints to model file (`#3399 `_) +- Apply resolve paths to path values in ``config`` (`#3400 `_) +- Fixing an incorrect computation of CDF of bremsstrahlung photons (`#3396 `_) +- Fix weight modification for uniform source sampling (`#3395 `_) +- Updates to VTK data checks (`#3371 `_) +- Map Compton subshell data to atomic relaxation data (`#3392 `_) +- Skip atomic relaxation if binding energy is larger than photon energy (`#3391 `_) +- Fix extremely large yields from Bremsstrahlung (`#3386 `_) +- corrected tally name in D1S example (`#3383 `_) +- Install MCPL using same build type as OpenMC in CI (`#3388 `_) +- using reduce chain level to remove need for reduce chain (`#3377 `_) +- Fix negative distances from bins_crossed for CylindricalMesh (`#3370 `_) +- Add check for equal value bins in an EnergyFilter (`#3372 `_) +- Fix for Issue Loading MGXS Data Files with LLVM 20 or Newer (`#3368 `_) +- Report plot ID instead of index for unsupported plot types in random ray mode (`#3361 `_) +- Handle Missing Tags in Versioning by Setting Default to 0 (`#3359 `_) +- added kg units to doc string in results class (`#3358 `_) diff --git a/docs/source/releasenotes/index.rst b/docs/source/releasenotes/index.rst index d24b83f9eb..1292599ba9 100644 --- a/docs/source/releasenotes/index.rst +++ b/docs/source/releasenotes/index.rst @@ -7,6 +7,7 @@ Release Notes .. toctree:: :maxdepth: 1 + 0.15.3 0.15.2 0.15.1 0.15.0 diff --git a/docs/source/usersguide/decay_sources.rst b/docs/source/usersguide/decay_sources.rst index d5a078135b..398680e746 100644 --- a/docs/source/usersguide/decay_sources.rst +++ b/docs/source/usersguide/decay_sources.rst @@ -6,42 +6,189 @@ Decay Sources Through the :ref:`depletion ` capabilities in OpenMC, it is possible to simulate radiation emitted from the decay of activated materials. -For fusion energy systems, this is commonly done using what is known as the -`rigorous 2-step `_ (R2S) method. -In this method, a neutron transport calculation is used to determine the neutron -flux and reaction rates over a cell- or mesh-based spatial discretization of the -model. Then, the neutron flux in each discrete region is used to predict the -activated material composition using a depletion solver. Finally, a photon -transport calculation with a source based on the activity and energy spectrum of -the activated materials is used to determine a desired physical response (e.g., -a dose rate) at one or more locations of interest. +For fusion energy systems, this is commonly done using either the `rigorous +2-step `_ (R2S) method or the +`direct 1-step `_ (D1S) method. +In the R2S method, a neutron transport calculation is used to determine the +neutron flux and reaction rates over a cell- or mesh-based spatial +discretization of the model. Then, the neutron flux in each discrete region is +used to predict the activated material composition using a depletion solver. +Finally, a photon transport calculation with a source based on the activity and +energy spectrum of the activated materials is used to determine a desired +physical response (e.g., a dose rate) at one or more locations of interest. +OpenMC includes automation for both the R2S and D1S methods as described in the +following sections. -Once a depletion simulation has been completed in OpenMC, the intrinsic decay -source can be determined as follows. First the activated material composition -can be determined using the :class:`openmc.deplete.Results` object. Indexing an -instance of this class with the timestep index returns a -:class:`~openmc.deplete.StepResult` object, which itself has a -:meth:`~openmc.deplete.StepResult.get_material` method. Once the activated -:class:`~openmc.Material` has been obtained, the -:meth:`~openmc.Material.get_decay_photon_energy` method will give the energy -spectrum of the decay photon source. The integral of the spectrum also indicates -the intensity of the source in units of [Bq]. Altogether, the workflow looks as -follows:: +Rigorous 2-Step (R2S) Calculations +================================== +OpenMC includes an :class:`openmc.deplete.R2SManager` class that fully automates +cell- and mesh-based R2S calculations. Before we describe this class, it is +useful to understand the basic mechanics of how an R2S calculation works. +Generally, it involves the following steps: + +1. The :meth:`openmc.deplete.get_microxs_and_flux` function is called to run a + neutron transport calculation that determines fluxes and microscopic cross + sections in each activation region. +2. The :class:`openmc.deplete.IndependentOperator` and + :class:`openmc.deplete.PredictorIntegrator` classes are used to carry out a + depletion (activation) calculation in order to determine predicted material + compositions based on a set of timesteps and source rates. +3. The activated material composition is determined using the + :class:`openmc.deplete.Results` class. Indexing an instance of this class + with the timestep index returns a :class:`~openmc.deplete.StepResult` object, + which itself has a :meth:`~openmc.deplete.StepResult.get_material` method + returning an activated material. +4. The :meth:`openmc.Material.get_decay_photon_energy` method is used to obtain + the energy spectrum of the decay photon source. The integral of the spectrum + also indicates the intensity of the source in units of [Bq]. +5. A new photon source is defined using one of OpenMC's source classes with the + energy distribution set equal to the object returned by the + :meth:`openmc.Material.get_decay_photon_energy` method. The source is then + assigned to a photon :class:`~openmc.Model`. +6. A photon transport calculation is run with ``model.run()``. + +Altogether, the workflow looks as follows:: + + # Run neutron transport calculation + fluxes, micros = openmc.deplete.get_microxs_and_flux(model, domains) + + # Run activation calculation + op = openmc.deplete.IndependentOperator(mats, fluxes, micros) + timesteps = ... + source_rates = ... + integrator = openmc.deplete.Integrator(op, timesteps, source_rates) + integrator.integrate() + + # Get decay photon source at last timestep results = openmc.deplete.Results("depletion_results.h5") - - # Get results at last timestep step = results[-1] - - # Get activated material composition for ID=1 activated_mat = step.get_material('1') - - # Determine photon source photon_energy = activated_mat.get_decay_photon_energy() + photon_source = openmc.IndependentSource( + space=..., + energy=photon_energy, + particle='photon', + strength=photon_energy.integral() + ) -By default, the :meth:`~openmc.Material.get_decay_photon_energy` method will -eliminate spectral lines with very low intensity, but this behavior can be -configured with the ``clip_tolerance`` argument. + # Run photon transport calculation + model.settings.source = photon_source + model.run() + +Note that by default, the :meth:`~openmc.Material.get_decay_photon_energy` +method will eliminate spectral lines with very low intensity, but this behavior +can be configured with the ``clip_tolerance`` argument. + +Cell-based R2S +-------------- + +In practice, users do not need to manually go through each of the steps in an R2S +calculation described above. The :class:`~openmc.deplete.R2SManager` fully +automates the execution of neutron transport, depletion, decay source +generation, and photon transport. For a cell-based R2S calculation, once you +have a :class:`~openmc.Model` that has been defined, simply create an instance +of :class:`~openmc.deplete.R2SManager` by passing the model and a list of cells +to activate:: + + r2s = openmc.deplete.R2SManager(model, [cell1, cell2, cell3]) + +Note that the ``volume`` attribute must be set for any cell that is to be +activated. The :class:`~openmc.deplete.R2SManager` class allows you to +optionally specify a separate photon model; if not given as an argument, it will +create a shallow copy of the original neutron model (available as the +``neutron_model`` attribute) and store it in the ``photon_model`` attribute. We +can use this to define tallies specific to the photon model:: + + dose_tally = openmc.Tally() + ... + r2s.photon_model.tallies = [dose_tally] + +Next, define the timesteps and source rates for the activation calculation:: + + timesteps = [(3.0, 'd'), (5.0, 'h')] + source_rates = [1e12, 0.0] + +In this case, the model is irradiated for 3 days with a source rate of +:math:`10^{12}` neutron/sec and then the source is turned off and the activated +materials are allowed to decay for 5 hours. These parameters should be passed to +the :meth:`~openmc.deplete.R2SManager.run` method to execute the full R2S +calculation. Before we can do that though, for a cell-based calculation, the one +other piece of information that is needed is bounding boxes of the activated +cells:: + + bounding_boxes = { + cell1.id: cell1.bounding_box, + cell2.id: cell2.bounding_box, + cell3.id: cell3.bounding_box + } + +Note that calling the ``bounding_box`` attribute may not work for all +constructive solid geometry regions (for example, a cell that uses a +non-axis-aligned plane). In these cases, the bounding box will need to be +specified manually. Once you have a set of bounding boxes, the R2S calculation +can be run:: + + r2s.run(timesteps, source_rates, bounding_boxes=bounding_boxes) + +If not specified otherwise, a photon transport calculation is run at each time +in the depletion schedule. That means in the case above, we would see three +photon transport calculations. To specify specific times at which photon +transport calculations should be run, pass the ``photon_time_indices`` argument. +For example, if we wanted to run a photon transport calculation only on the last +time (after the 5 hour decay), we would run:: + + r2s.run(timesteps, source_rates, bounding_boxes=bounding_boxes, + photon_time_indices=[2]) + +After an R2S calculation has been run, the :class:`~openmc.deplete.R2SManager` +instance will have a ``results`` dictionary that allows you to directly access +results from each of the steps. It will also write out all the output files into +a directory that is named "r2s_/". The ``output_dir`` argument to the +:meth:`~openmc.deplete.R2SManager.run` method enables you to override the +default output directory name if desired. + +The :meth:`~openmc.deplete.R2SManager.run` method actually runs three +lower-level methods under the hood:: + + r2s.step1_neutron_transport(...) + r2s.step2_activation(...) + r2s.step3_photon_transport(...) + +For users looking for more control over the calculation, these lower-level +methods can be used in lieu of the :meth:`openmc.deplete.R2SManager.run` method. + +Mesh-based R2S +-------------- + +Executing a mesh-based R2S calculation looks nearly identical to the cell-based +R2S workflow described above. The only difference is that instead of passing a +list of cells to the ``domains`` argument of +:class:`~openmc.deplete.R2SManager`, you need to define a mesh object and pass +that instead. This might look like the following:: + + # Define a regular Cartesian mesh + mesh = openmc.RegularMesh() + mesh.lower_left = (-50., -50., 0.) + mesh.upper_right = (50., 50., 75.) + mesh.dimension = (10, 10, 5) + + r2s = openmc.deplete.R2SManager(model, mesh) + +Executing the R2S calculation is then performed by adding photon tallies and +calling the :meth:`~openmc.deplete.R2SManager.run` method with the appropriate +timesteps and source rates. Note that in this case we do not need to define cell +volumes or bounding boxes as is required for a cell-based R2S calculation. +Instead, during the neutron transport step, OpenMC will run a raytracing +calculation to determine material volume fractions within each mesh element +using the :meth:`openmc.MeshBase.material_volumes` method. Arguments to this +method can be customized via the ``mat_vol_kwargs`` argument to the +:meth:`~openmc.deplete.R2SManager.run` method. Most often, this would involve +customizing the number of rays traced to obtain better estimates of volumes. As +an example, if we wanted to run the raytracing calculation with 10 million rays, +we would run:: + + r2s.run(timesteps, source_rates, mat_vol_kwargs={'n_samples': 10_000_000}) Direct 1-Step (D1S) Calculations ================================ diff --git a/docs/source/usersguide/geometry.rst b/docs/source/usersguide/geometry.rst index 6f14ebfa51..f51fbd73c0 100644 --- a/docs/source/usersguide/geometry.rst +++ b/docs/source/usersguide/geometry.rst @@ -182,6 +182,8 @@ boundary condition. Periodic boundary conditions can be applied to pairs of planar surfaces. If there are only two periodic surfaces they will be matched automatically. + + Otherwise it is necessary to specify pairs explicitly using the :attr:`Surface.periodic_surface` attribute as in the following example:: @@ -192,7 +194,7 @@ Otherwise it is necessary to specify pairs explicitly using the Both rotational and translational periodic boundary conditions are specified in the same fashion. If both planes have the same normal vector, a translational periodicity is assumed; rotational periodicity is assumed otherwise. Currently, -only rotations about the :math:`z`-axis are supported. +rotations must be about the :math:`x`-, :math:`y`-, or :math:`z`-axis. For a rotational periodic BC, the normal vectors of each surface must point inwards---towards the valid geometry. For example, a :class:`XPlane` and @@ -530,6 +532,89 @@ UWUW and OpenMC material ID space will cause an error. To automatically resolve these ID overlaps, ``auto_ids`` can be set to ``True`` to append the UWUW material IDs to the OpenMC material ID space. + +Material overrides and differentiation +-------------------------------------- + +Programmatic access to DAGMC cell information for material overrides +and differentiation requires synchronization of the DAGMC universe +representation across Python and C-API:: + + model.init_lib() + model.sync_dagmc_universes() + model.finalize_lib() + +Upon completion of these steps, the :attr:`DAGMCUniverse.cells` attribute will +be populated with :class:`DAGMCCell` proxy objects that represent the cells +defined in the DAGMC model. The :class:`DAGMCCell` objects will have +:class:`openmc.Material`'s' applied according to the assignments upon +initialization of the model. These materials can be replaced in the same manner +as :class:`openmc.Cell` objects to override material assignments in the DAGMC +model. + +Depletion with DAGMC geometry +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The synchronization of :class:`openmc.DAGMCUniverse`'s is important for +depletion calculations using DAGMC geometry when materials need to be +differentiated to perform material burnup independently in each DAGMC cell. See +:meth:`openmc.model.Model.differentiate_mats`. + +Material overrides +~~~~~~~~~~~~~~~~~~ + +OpenMC supports overriding material assignments defined inside a DAGMC HDF5 +model so that CAD-assigned materials can be replaced by :class:`openmc.Material` +objects. This is useful when the CAD geometry provides the shape but OpenMC +materials (specific nuclide content, densities, or depletion behavior) are +required. + + +Replacing materials by name +^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +If a DAGMC file includes material name tags, you can replace all cells that +reference a particular name with an :class:`openmc.Material` using +:meth:`~openmc.DAGMCUniverse.replace_material_assignment`:: + + import openmc + + dag_univ = openmc.DAGMCUniverse('dagmc.h5m') + + fuel = openmc.Material(name='fuel') + fuel.add_nuclide('U235', 0.05) + fuel.add_nuclide('U238', 0.95) + fuel.set_density('g/cm3', 10.5) + + dag_univ.replace_material_assignment('Fuel', fuel) + +This lets you keep CAD geometry while adopting OpenMC material definitions. + +Per-cell material overrides +^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +To assign overrides without initializing :class:`openmc.Model`, the +:meth:`openmc.DAGMCUniverse.add_material_override` method can be used to assign +materials to particular DAGMC cells. The method accepts either an integer cell +ID:: + + dag_univ = openmc.DAGMCUniverse('dagmc.h5m') + + enriched = openmc.Material(name='fuel_enriched') + enriched.add_nuclide('U235', 0.10) + enriched.add_nuclide('U238', 0.90) + enriched.set_density('g/cm3', 10.5) + + dag_univ.add_material_override(1, enriched) + +In the case that the :class:`openmc.DAGMCUniverse` has already been synchronized, +a :class:`openmc.DAGMCCell` object can also be provide to assign the material. + +Overrides are written to the `` element of the +:ref:` ` XML element so the C++ core can apply +them on initialization. + + .. _Direct Accelerated Geometry Monte Carlo: https://svalinn.github.io/DAGMC/ .. _University of Wisconsin Unified Workflow: https://svalinn.github.io/DAGMC/usersguide/uw2.html diff --git a/docs/source/usersguide/kinetics.rst b/docs/source/usersguide/kinetics.rst index bdf26d341b..9024ff8227 100644 --- a/docs/source/usersguide/kinetics.rst +++ b/docs/source/usersguide/kinetics.rst @@ -67,6 +67,23 @@ are needed to compute kinetics parameters in OpenMC: Obtaining kinetics parameters ----------------------------- +The ``Model`` class can be used to automatically generate all IFP tallies using +the Python API with :attr:`openmc.Settings.ifp_n_generation` greater than 0 and +the :meth:`openmc.Model.add_ifp_kinetics_tallies` method:: + + model = openmc.Model(geometry, settings=settings) + model.add_kinetics_parameters_tallies(num_groups=6) # Add 6 precursor groups + +Alternatively, each of the tallies can be manually defined using group-wise or +total :math:`\beta_{\text{eff}}` specified by providing a 6-group +:class:`openmc.DelayedGroupFilter`:: + + beta_tally = openmc.Tally(name="group-beta-score") + beta_tally.scores = ["ifp-beta-numerator"] + + # Add DelayedGroupFilter to enable group-wise tallies + beta_tally.filters = [openmc.DelayedGroupFilter(list(range(1, 7)))] + Here is an example showing how to declare the three available IFP scores in a single tally:: @@ -95,6 +112,12 @@ for ``ifp-denominator``: \beta_{\text{eff}} = \frac{S_{\text{ifp-beta-numerator}}}{S_{\text{ifp-denominator}}} +The kinetics parameters can be retrieved directly from a statepoint file using +the :meth:`openmc.StatePoint.ifp_results` method:: + + with openmc.StatePoint(output_path) as sp: + generation_time, beta_eff = sp.get_kinetics_parameters() + .. only:: html .. rubric:: References @@ -107,4 +130,4 @@ for ``ifp-denominator``: of the Iterated Fission Probability Method in OpenMC to Compute Adjoint-Weighted Kinetics Parameters", International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025), Denver, April 27-30, - 2025 (to be presented). + 2025. diff --git a/docs/source/usersguide/plots.rst b/docs/source/usersguide/plots.rst index da0c69bdd8..b5c29a3e88 100644 --- a/docs/source/usersguide/plots.rst +++ b/docs/source/usersguide/plots.rst @@ -6,13 +6,14 @@ Geometry Visualization .. currentmodule:: openmc -OpenMC is capable of producing two-dimensional slice plots of a geometry as well -as three-dimensional voxel plots using the geometry plotting :ref:`run mode -`. The geometry plotting mode relies on the presence of a -:ref:`plots.xml ` file that indicates what plots should be created. To -create this file, one needs to create one or more :class:`openmc.Plot` -instances, add them to a :class:`openmc.Plots` collection, and then use the -:class:`Plots.export_to_xml` method to write the ``plots.xml`` file. +OpenMC is capable of producing two-dimensional slice plots of a geometry, +three-dimensional voxel plots, and three-dimensional raytrace plots using the +geometry plotting :ref:`run mode `. The geometry plotting +mode relies on the presence of a :ref:`plots.xml ` file that indicates +what plots should be created. To create this file, one needs to create one or +more instances of the various plot classes described below, add them to a +:class:`openmc.Plots` collection, and then use the :class:`Plots.export_to_xml` +method to write the ``plots.xml`` file. ----------- Slice Plots @@ -21,15 +22,14 @@ Slice Plots .. image:: ../_images/atr.png :width: 300px -By default, when an instance of :class:`openmc.Plot` is created, it indicates -that a 2D slice plot should be made. You can specify the origin of the plot -(:attr:`Plot.origin`), the width of the plot in each direction -(:attr:`Plot.width`), the number of pixels to use in each direction -(:attr:`Plot.pixels`), and the basis directions for the plot. For example, to -create a :math:`x` - :math:`z` plot centered at (5.0, 2.0, 3.0) with a width of -(50., 50.) and 400x400 pixels:: +The :class:`openmc.SlicePlot` class indicates that a 2D slice plot should be +made. You can specify the origin of the plot (:attr:`SlicePlot.origin`), the +width of the plot in each direction (:attr:`SlicePlot.width`), the number of +pixels to use in each direction (:attr:`SlicePlot.pixels`), and the basis +directions for the plot. For example, to create a :math:`x` - :math:`z` plot +centered at (5.0, 2.0, 3.0) with a width of (50., 50.) and 400x400 pixels:: - plot = openmc.Plot() + plot = openmc.SlicePlot() plot.basis = 'xz' plot.origin = (5.0, 2.0, 3.0) plot.width = (50., 50.) @@ -47,7 +47,7 @@ that location. By default, a unique color will be assigned to each cell in the geometry. If you want your plot to be colored by material instead, change the -:attr:`Plot.color_by` attribute:: +:attr:`SlicePlot.color_by` attribute:: plot.color_by = 'material' @@ -68,8 +68,8 @@ particular cells/materials should be given colors of your choosing:: Note that colors can be given as RGB tuples or by a string indicating a valid `SVG color `_. -When you're done creating your :class:`openmc.Plot` instances, you need to then -assign them to a :class:`openmc.Plots` collection and export it to XML:: +When you're done creating your :class:`openmc.SlicePlot` instances, you need to +then assign them to a :class:`openmc.Plots` collection and export it to XML:: plots = openmc.Plots([plot1, plot2, plot3]) plots.export_to_xml() @@ -97,13 +97,11 @@ Voxel Plots .. image:: ../_images/3dba.png :width: 200px -The :class:`openmc.Plot` class can also be told to generate a 3D voxel plot -instead of a 2D slice plot. Simply change the :attr:`Plot.type` attribute to -'voxel'. In this case, the :attr:`Plot.width` and :attr:`Plot.pixels` attributes -should be three items long, e.g.:: +The :class:`openmc.VoxelPlot` class enables the generation of a 3D voxel plot +instead of a 2D slice plot. In this case, the :attr:`VoxelPlot.width` and +:attr:`VoxelPlot.pixels` attributes should be three items long, e.g.:: - vox_plot = openmc.Plot() - vox_plot.type = 'voxel' + vox_plot = openmc.VoxelPlot() vox_plot.width = (100., 100., 50.) vox_plot.pixels = (400, 400, 200) diff --git a/docs/source/usersguide/processing.rst b/docs/source/usersguide/processing.rst index 8b5ae53fac..fe6ab0826f 100644 --- a/docs/source/usersguide/processing.rst +++ b/docs/source/usersguide/processing.rst @@ -68,17 +68,17 @@ generation, and particle number of the desired particle. For example, to create a track file for particle 4 of batch 1 and generation 2:: settings = openmc.Settings() - settings.track = (1, 2, 4) + settings.track = [(1, 2, 4)] -To specify multiple particles, the length of the iterable should be a multiple -of three, e.g., if we wanted particles 3 and 4 from batch 1 and generation 2:: +To specify multiple particles, specify a list of tuples, e.g., if we wanted +particles 3 and 4 from batch 1 and generation 2:: - settings.track = (1, 2, 3, 1, 2, 4) + settings.track = [(1, 2, 3), (1, 2, 4)] -After running OpenMC, the working directory will contain a file of the form -"track_(batch #)_(generation #)_(particle #).h5" for each particle tracked. -These track files can be converted into VTK poly data files with the -:class:`openmc.Tracks` class. +After running OpenMC (now, without the ``-t`` argument), the working directory +will contain a file named `tracks.h5`, which contains a collection of particle +tracks. These track files can be converted into VTK poly data files or +matplotlib plots with the :class:`openmc.Tracks` class. ---------------------- Source Site Processing diff --git a/docs/source/usersguide/random_ray.rst b/docs/source/usersguide/random_ray.rst index 138ae910c9..382381a9ee 100644 --- a/docs/source/usersguide/random_ray.rst +++ b/docs/source/usersguide/random_ray.rst @@ -644,7 +644,8 @@ model to use these multigroup cross sections. An example is given below:: nparticles=2000, overwrite_mgxs_library=False, mgxs_path="mgxs.h5", - correction=None + correction=None, + source_energy=None ) The most important parameter to set is the ``method`` parameter, which can be @@ -706,6 +707,31 @@ generation and use an existing library file. with a :math:`\rho` default value of 1.0, which can be adjusted with the ``settings.random_ray['diagonal_stabilization_rho']`` parameter. +When generating MGXS data with either the ``stochastic_slab`` or +``infinite_medium`` methods, by default the simulation will use a uniform source +distribution spread evenly over all energy groups. This ensures that all energy +groups receive tallies and therefore produce non-zero total multigroup cross +sections. Additionally, the function will convert any sources in the model into +simplified spatial sources that retain the original energy distributions. If +sources are present, they will be used 99% of the time to sample source energies +during MGXS generation. The other 1% of the time, energies will be sampled +uniformly over all energy groups to ensure that all groups receive some tallies. +However, the user may wish to specify a different source energy spectrum (for +instance, if they are using a FileSource, such that the energy distribution +cannot be extracted from the python source object). This can be done by +providing a :class:`openmc.stats.Univariate` distribution as the +``source_energy`` parameter of the :meth:`openmc.Model.convert_to_multigroup` +method. If provided, it will override any sources present in the model and will +be used 99% of the time to sample source energies during MGXS generation. The +other 1% of the time, energies will be sampled uniformly over all energy groups +to ensure that all groups receive some tallies. + +For instance, a D-D fusion simulation may involve a complex file source. In this +case, the user may wish to provide a discrete 2.45 MeV energy source +distribution for MGXS generation as:: + + source_energy = openmc.stats.delta_function(2.45e6) + Ultimately, the methods described above are all just approximations. Approximations in the generated MGXS data will fundamentally limit the potential accuracy of the random ray solver. However, the methods described above are all @@ -765,7 +791,7 @@ energy decomposition:: # Create a "tallies.xml" file for the MGXS Library tallies = openmc.Tallies() - mgxs_lib.add_to_tallies_file(tallies, merge=True) + mgxs_lib.add_to_tallies(tallies, merge=True) # Export tallies.export_to_xml() @@ -1105,11 +1131,10 @@ given below: tallies.export_to_xml() # Create voxel plot - plot = openmc.Plot() + plot = openmc.VoxelPlot() plot.origin = [0, 0, 0] plot.width = [2*pitch, 2*pitch, 1] plot.pixels = [1000, 1000, 1] - plot.type = 'voxel' # Instantiate a Plots collection and export to XML plots = openmc.Plots([plot]) @@ -1189,11 +1214,10 @@ given below: tallies.export_to_xml() # Create voxel plot - plot = openmc.Plot() + plot = openmc.VoxelPlot() plot.origin = [0, 0, 0] plot.width = [2*pitch, 2*pitch, 1] plot.pixels = [1000, 1000, 1] - plot.type = 'voxel' # Instantiate a Plots collection and export to XML plots = openmc.Plots([plot]) diff --git a/docs/source/usersguide/scripts.rst b/docs/source/usersguide/scripts.rst index 0879d63efd..eb0abeb0dd 100644 --- a/docs/source/usersguide/scripts.rst +++ b/docs/source/usersguide/scripts.rst @@ -48,6 +48,7 @@ flags: restart file -s, --threads N Run with *N* OpenMP threads -t, --track Write tracks for all particles (up to max_tracks) +-q, --verbosity V Set the output verbosity to *V* -v, --version Show version information -h, --help Show help message diff --git a/docs/source/usersguide/settings.rst b/docs/source/usersguide/settings.rst index 1b2d4bc1a5..f973f14655 100644 --- a/docs/source/usersguide/settings.rst +++ b/docs/source/usersguide/settings.rst @@ -756,6 +756,62 @@ instance, whereas the :meth:`openmc.Track.filter` method returns a new track_files = [f"tracks_p{rank}.h5" for rank in range(32)] openmc.Tracks.combine(track_files, "tracks.h5") +Collision Track File +--------------------- + +OpenMC can generate a collision track file that contains detailed collision +information (position, direction, energy, deposited energy, time, weight, cell +ID, material ID, universe ID, nuclide ZAID, particle type, particle delayed +group and particle ID) for each particle collision depending on user-defined +parameters. To invoke this feature, set the +:attr:`~openmc.Settings.collision_track` attribute as shown in this example:: + + settings.collision_track = { + "max_collisions": 300, + "reactions": ["(n,fission)", "(n,2n)"], + "material_ids": [1,2], + "nuclides": ["U238", "O16"], + "cell_ids": [5, 12] + } + +In this example, collision track information is written to the +collision_track.h5 file at the end of the simulation. The file contains +300 recorded collisions that occurred in materials with IDs 1 or 2, involving +fission or (n,2n) reactions on the nuclides U-238 or O-16, within cells +with IDs 5 and 12. +The file can be read using :func:`openmc.read_collision_track_file`. +The example below shows how to extract the data from the collision_track +feature and displays the fields stored in the file: + +>>> data = openmc.read_collision_track_file('collision_track.h5') +>>> data.dtype + dtype([('r', [('x', '`. # we used for source region decomposition wwg = openmc.WeightWindowGenerator( method='fw_cadis', - mesh=mesh, - max_realizations=settings.batches + mesh=mesh ) # Add generator to openmc.settings object @@ -162,7 +161,7 @@ solver, the Python input just needs to load the h5 file:: settings.weight_window_checkpoints = {'collision': True, 'surface': True} settings.survival_biasing = False - settings.weight_windows = openmc.WeightWindowsList.from_hdf5('weight_windows.h5') + settings.weight_windows_file = "weight_windows.h5" settings.weight_windows_on = True The :class:`~openmc.WeightWindowGenerator` instance is not needed to load an diff --git a/examples/lattice/hexagonal/build_xml.py b/examples/lattice/hexagonal/build_xml.py index 9485d0aa45..2624e52b4d 100644 --- a/examples/lattice/hexagonal/build_xml.py +++ b/examples/lattice/hexagonal/build_xml.py @@ -128,14 +128,14 @@ settings_file.export_to_xml() # Exporting to OpenMC plots.xml file ############################################################################### -plot_xy = openmc.Plot(plot_id=1) +plot_xy = openmc.SlicePlot(plot_id=1) plot_xy.filename = 'plot_xy' plot_xy.origin = [0, 0, 0] plot_xy.width = [6, 6] plot_xy.pixels = [400, 400] plot_xy.color_by = 'material' -plot_yz = openmc.Plot(plot_id=2) +plot_yz = openmc.SlicePlot(plot_id=2) plot_yz.filename = 'plot_yz' plot_yz.basis = 'yz' plot_yz.origin = [0, 0, 0] diff --git a/examples/lattice/nested/build_xml.py b/examples/lattice/nested/build_xml.py index 2db23a46b3..a1d9c092dd 100644 --- a/examples/lattice/nested/build_xml.py +++ b/examples/lattice/nested/build_xml.py @@ -135,7 +135,7 @@ settings_file.export_to_xml() # Exporting to OpenMC plots.xml file ############################################################################### -plot = openmc.Plot(plot_id=1) +plot = openmc.SlicePlot(plot_id=1) plot.origin = [0, 0, 0] plot.width = [4, 4] plot.pixels = [400, 400] diff --git a/examples/lattice/simple/build_xml.py b/examples/lattice/simple/build_xml.py index 56c4661216..44531edd8a 100644 --- a/examples/lattice/simple/build_xml.py +++ b/examples/lattice/simple/build_xml.py @@ -128,7 +128,7 @@ settings_file.export_to_xml() # Exporting to OpenMC plots.xml file ############################################################################### -plot = openmc.Plot(plot_id=1) +plot = openmc.SlicePlot(plot_id=1) plot.origin = [0, 0, 0] plot.width = [4, 4] plot.pixels = [400, 400] diff --git a/examples/pincell_pulsed/run_pulse.py b/examples/pincell_pulsed/run_pulse.py new file mode 100644 index 0000000000..b6a61ad3d8 --- /dev/null +++ b/examples/pincell_pulsed/run_pulse.py @@ -0,0 +1,101 @@ +import matplotlib.pyplot as plt +import numpy as np +import openmc + +############################################################################### +# Create materials for the problem + +uo2 = openmc.Material(name="UO2 fuel at 2.4% wt enrichment") +uo2.set_density("g/cm3", 10.29769) +uo2.add_element("U", 1.0, enrichment=2.4) +uo2.add_element("O", 2.0) + +helium = openmc.Material(name="Helium for gap") +helium.set_density("g/cm3", 0.001598) +helium.add_element("He", 2.4044e-4) + +zircaloy = openmc.Material(name="Zircaloy 4") +zircaloy.set_density("g/cm3", 6.55) +zircaloy.add_element("Sn", 0.014, "wo") +zircaloy.add_element("Fe", 0.00165, "wo") +zircaloy.add_element("Cr", 0.001, "wo") +zircaloy.add_element("Zr", 0.98335, "wo") + +borated_water = openmc.Material(name="Borated water") +borated_water.set_density("g/cm3", 0.740582) +borated_water.add_element("B", 2.0e-4) # 3x the original pincell +borated_water.add_element("H", 5.0e-2) +borated_water.add_element("O", 2.4e-2) +borated_water.add_s_alpha_beta("c_H_in_H2O") + +############################################################################### +# Define problem geometry + +# Create cylindrical surfaces +fuel_or = openmc.ZCylinder(r=0.39218, name="Fuel OR") +clad_ir = openmc.ZCylinder(r=0.40005, name="Clad IR") +clad_or = openmc.ZCylinder(r=0.45720, name="Clad OR") + +# Create a region represented as the inside of a rectangular prism +pitch = 1.25984 +box = openmc.model.RectangularPrism(pitch, pitch, boundary_type="reflective") + +# Create cells, mapping materials to regions +fuel = openmc.Cell(fill=uo2, region=-fuel_or) +gap = openmc.Cell(fill=helium, region=+fuel_or & -clad_ir) +clad = openmc.Cell(fill=zircaloy, region=+clad_ir & -clad_or) +water = openmc.Cell(fill=borated_water, region=+clad_or & -box) + +# Create a model and assign geometry +model = openmc.Model() +model.geometry = openmc.Geometry([fuel, gap, clad, water]) + +############################################################################### +# Define problem settings + +# Set the mode +model.settings.run_mode = "fixed source" + +# Indicate how many batches and particles to run +model.settings.batches = 10 +model.settings.particles = 10000 + +# Set time cutoff (we only care about t < 100 seconds, see tally below) +model.settings.cutoff = {"time_neutron": 100} + +# Create the neutron pulse source (by default, isotropic direction, t=0) +space = openmc.stats.Point() # At the origin (0, 0, 0) +energy = openmc.stats.delta_function(14.1e6) # At 14.1 MeV +model.settings.source = openmc.IndependentSource(space=space, energy=energy) + +############################################################################### +# Define tallies + +# Create time filter +t_grid = np.insert(np.logspace(-6, 2, 100), 0, 0.0) +time_filter = openmc.TimeFilter(t_grid) + +# Tally for total neutron density in time +density_tally = openmc.Tally(name="Density") +density_tally.filters = [time_filter] +density_tally.scores = ["inverse-velocity"] + +# Add tallies to model +model.tallies = openmc.Tallies([density_tally]) + + +# Run the model +model.run(apply_tally_results=True) + +# Bin-averaged result +density_mean = density_tally.mean.ravel() / np.diff(t_grid) + +# Plot particle density versus time +fig, ax = plt.subplots() +ax.stairs(density_mean, t_grid) +ax.set_xscale("log") +ax.set_yscale("log") +ax.set_xlabel("Time [s]") +ax.set_ylabel("Total density") +ax.grid() +plt.show() diff --git a/examples/pincell_random_ray/build_xml.py b/examples/pincell_random_ray/build_xml.py index b3dd8020a5..5ff4c0082f 100644 --- a/examples/pincell_random_ray/build_xml.py +++ b/examples/pincell_random_ray/build_xml.py @@ -192,11 +192,10 @@ tallies.export_to_xml() # Exporting to OpenMC plots.xml file ############################################################################### -plot = openmc.Plot() +plot = openmc.VoxelPlot() plot.origin = [0, 0, 0] plot.width = [pitch, pitch, pitch] plot.pixels = [1000, 1000, 1] -plot.type = 'voxel' # Instantiate a Plots collection and export to XML plots = openmc.Plots([plot]) diff --git a/include/openmc/bank.h b/include/openmc/bank.h index fd8fbd73ee..c4e940bc87 100644 --- a/include/openmc/bank.h +++ b/include/openmc/bank.h @@ -20,6 +20,8 @@ extern vector source_bank; extern SharedArray surf_source_bank; +extern SharedArray collision_track_bank; + extern SharedArray fission_bank; extern vector> ifp_source_delayed_group_bank; diff --git a/include/openmc/bank_io.h b/include/openmc/bank_io.h new file mode 100644 index 0000000000..418ec111f2 --- /dev/null +++ b/include/openmc/bank_io.h @@ -0,0 +1,105 @@ +#ifndef OPENMC_BANK_IO_H +#define OPENMC_BANK_IO_H + +#include "hdf5.h" + +#include "openmc/message_passing.h" +#include "openmc/span.h" +#include "openmc/vector.h" + +#include + +#ifdef OPENMC_MPI +#include +#endif + +namespace openmc { + +template +void write_bank_dataset( + const char* dataset_name, hid_t group_id, span bank, + const vector& bank_index, hid_t membanktype, hid_t filebanktype +#ifdef OPENMC_MPI + , + MPI_Datatype mpi_dtype +#endif +) +{ + int64_t dims_size = bank_index.back(); + int64_t count_size = bank_index[mpi::rank + 1] - bank_index[mpi::rank]; + +#ifdef PHDF5 + hsize_t dims[] {static_cast(dims_size)}; + hid_t dspace = H5Screate_simple(1, dims, nullptr); + hid_t dset = H5Dcreate(group_id, dataset_name, filebanktype, dspace, + H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); + + hsize_t count[] {static_cast(count_size)}; + hid_t memspace = H5Screate_simple(1, count, nullptr); + + hsize_t start[] {static_cast(bank_index[mpi::rank])}; + H5Sselect_hyperslab(dspace, H5S_SELECT_SET, start, nullptr, count, nullptr); + + hid_t plist = H5Pcreate(H5P_DATASET_XFER); + H5Pset_dxpl_mpio(plist, H5FD_MPIO_COLLECTIVE); + + H5Dwrite(dset, membanktype, memspace, dspace, plist, bank.data()); + + H5Sclose(dspace); + H5Sclose(memspace); + H5Dclose(dset); + H5Pclose(plist); +#else + if (mpi::master) { + hsize_t dims[] {static_cast(dims_size)}; + hid_t dspace = H5Screate_simple(1, dims, nullptr); + hid_t dset = H5Dcreate(group_id, dataset_name, filebanktype, dspace, + H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); + +#ifdef OPENMC_MPI + vector temp_bank {bank.begin(), bank.end()}; +#endif + + for (int i = 0; i < mpi::n_procs; ++i) { + hsize_t count[] {static_cast(bank_index[i + 1] - bank_index[i])}; + hid_t memspace = H5Screate_simple(1, count, nullptr); + +#ifdef OPENMC_MPI + if (i > 0) { + MPI_Recv(bank.data(), count[0], mpi_dtype, i, i, mpi::intracomm, + MPI_STATUS_IGNORE); + } +#endif + + hid_t dspace_rank = H5Dget_space(dset); + hsize_t start[] {static_cast(bank_index[i])}; + H5Sselect_hyperslab( + dspace_rank, H5S_SELECT_SET, start, nullptr, count, nullptr); + + H5Dwrite( + dset, membanktype, memspace, dspace_rank, H5P_DEFAULT, bank.data()); + + H5Sclose(memspace); + H5Sclose(dspace_rank); + } + + H5Dclose(dset); + +#ifdef OPENMC_MPI + std::copy(temp_bank.begin(), temp_bank.end(), bank.begin()); +#endif + } +#ifdef OPENMC_MPI + else { + if (!bank.empty()) { + MPI_Send( + bank.data(), bank.size(), mpi_dtype, 0, mpi::rank, mpi::intracomm); + } + } +#endif +#endif +} + +} // namespace openmc + +#endif // OPENMC_BANK_IO_H diff --git a/include/openmc/boundary_condition.h b/include/openmc/boundary_condition.h index af40131f1c..5a14239e8b 100644 --- a/include/openmc/boundary_condition.h +++ b/include/openmc/boundary_condition.h @@ -138,18 +138,26 @@ protected: //============================================================================== //! A BC that rotates particles about a global axis. // -//! Currently only rotations about the z-axis are supported. +//! Only rotations about the x, y, and z axes are supported. //============================================================================== class RotationalPeriodicBC : public PeriodicBC { public: - RotationalPeriodicBC(int i_surf, int j_surf); - + enum PeriodicAxis { x, y, z }; + RotationalPeriodicBC(int i_surf, int j_surf, PeriodicAxis axis); + double compute_periodic_rotation( + double rise_1, double run_1, double rise_2, double run_2) const; void handle_particle(Particle& p, const Surface& surf) const override; protected: //! Angle about the axis by which particle coordinates will be rotated double angle_; + //! Ensure that choice of axes is right handed. axis_1_idx_ corresponds to the + //! independent axis and axis_2_idx_ corresponds to the dependent axis in the + //! 2D plane perpendicular to the planes' axis of rotation + int zero_axis_idx_; + int axis_1_idx_; + int axis_2_idx_; }; } // namespace openmc diff --git a/include/openmc/capi.h b/include/openmc/capi.h index 54257d0938..d8041ef414 100644 --- a/include/openmc/capi.h +++ b/include/openmc/capi.h @@ -17,6 +17,8 @@ int openmc_cell_get_fill( int openmc_cell_get_id(int32_t index, int32_t* id); int openmc_cell_get_temperature( int32_t index, const int32_t* instance, double* T); +int openmc_cell_get_density( + int32_t index, const int32_t* instance, double* rho); int openmc_cell_get_translation(int32_t index, double xyz[]); int openmc_cell_get_rotation(int32_t index, double rot[], size_t* n); int openmc_cell_get_name(int32_t index, const char** name); @@ -27,6 +29,8 @@ int openmc_cell_set_fill( int openmc_cell_set_id(int32_t index, int32_t id); int openmc_cell_set_temperature( int32_t index, double T, const int32_t* instance, bool set_contained = false); +int openmc_cell_set_density(int32_t index, double rho, const int32_t* instance, + bool set_contained = false); int openmc_cell_set_translation(int32_t index, const double xyz[]); int openmc_cell_set_rotation(int32_t index, const double rot[], size_t rot_len); int openmc_dagmc_universe_get_cell_ids( diff --git a/include/openmc/cell.h b/include/openmc/cell.h index d2365c84c4..a581291dfc 100644 --- a/include/openmc/cell.h +++ b/include/openmc/cell.h @@ -216,6 +216,18 @@ public: //! \return Temperature in [K] double temperature(int32_t instance = -1) const; + //! Get the density multiplier of a cell instance + //! \param[in] instance Instance index. If -1 is given, the density multiplier + //! for the first instance is returned. + //! \return Density multiplier + double density_mult(int32_t instance = -1) const; + + //! Get the density of a cell instance in g/cm3 + //! \param[in] instance Instance index. If -1 is given, the density + //! for the first instance is returned. + //! \return Density in [g/cm3] + double density(int32_t instance = -1) const; + //! Set the temperature of a cell instance //! \param[in] T Temperature in [K] //! \param[in] instance Instance index. If -1 is given, the temperature for @@ -226,6 +238,16 @@ public: void set_temperature( double T, int32_t instance = -1, bool set_contained = false); + //! Set the density of a cell instance + //! \param[in] density Density [g/cm3] + //! \param[in] instance Instance index. If -1 is given, the density + //! for all instances is set. + //! \param[in] set_contained If this cell is not filled with a material, + //! collect all contained cells with material fills and set their + //! densities. + void set_density( + double density, int32_t instance = -1, bool set_contained = false); + int32_t n_instances() const; //! Set the rotation matrix of a cell instance @@ -341,6 +363,9 @@ public: //! T. The units are sqrt(eV). vector sqrtkT_; + //! \brief Unitless density multiplier(s) within this cell. + vector density_mult_; + //! \brief Neighboring cells in the same universe. NeighborList neighbors_; diff --git a/include/openmc/collision_track.h b/include/openmc/collision_track.h new file mode 100644 index 0000000000..208b8f6e1f --- /dev/null +++ b/include/openmc/collision_track.h @@ -0,0 +1,23 @@ +#ifndef OPENMC_COLLISION_TRACK_H +#define OPENMC_COLLISION_TRACK_H + +#include + +namespace openmc { + +class Particle; + +//! Reserve space in the collision track bank according to user settings. +void collision_track_reserve_bank(); + +//! Write collision track data to disk when the bank is full or the batch ends. +void collision_track_flush_bank(); + +//! Record the current particle as a collision-track entry when applicable. +//! +//! \param particle Particle whose collision should be recorded if eligible +void collision_track_record(Particle& particle); + +} // namespace openmc + +#endif // OPENMC_COLLISION_TRACK_H diff --git a/include/openmc/constants.h b/include/openmc/constants.h index ae70560795..bba260c3a4 100644 --- a/include/openmc/constants.h +++ b/include/openmc/constants.h @@ -28,12 +28,13 @@ constexpr int HDF5_VERSION[] {3, 0}; constexpr array VERSION_STATEPOINT {18, 1}; constexpr array VERSION_PARTICLE_RESTART {2, 0}; constexpr array VERSION_TRACK {3, 0}; -constexpr array VERSION_SUMMARY {6, 0}; +constexpr array VERSION_SUMMARY {6, 1}; constexpr array VERSION_VOLUME {1, 0}; constexpr array VERSION_VOXEL {2, 0}; constexpr array VERSION_MGXS_LIBRARY {1, 0}; -constexpr array VERSION_PROPERTIES {1, 0}; +constexpr array VERSION_PROPERTIES {1, 1}; constexpr array VERSION_WEIGHT_WINDOWS {1, 0}; +constexpr array VERSION_COLLISION_TRACK {1, 0}; // ============================================================================ // ADJUSTABLE PARAMETERS @@ -68,6 +69,11 @@ constexpr double MIN_HITS_PER_BATCH {1.5}; // prevent extremely large adjoint source terms from being generated. constexpr double ZERO_FLUX_CUTOFF {1e-22}; +// The minimum macroscopic cross section value considered non-void for the +// random ray solver. Materials with any group with a cross section below this +// value will be converted to pure void. +constexpr double MINIMUM_MACRO_XS {1e-6}; + // ============================================================================ // MATH AND PHYSICAL CONSTANTS @@ -286,7 +292,7 @@ enum class MgxsType { // ============================================================================ // TALLY-RELATED CONSTANTS -enum class TallyResult { VALUE, SUM, SUM_SQ, SIZE }; +enum class TallyResult { VALUE, SUM, SUM_SQ, SUM_THIRD, SUM_FOURTH }; enum class TallyType { VOLUME, MESH_SURFACE, SURFACE, PULSE_HEIGHT }; diff --git a/include/openmc/distribution_multi.h b/include/openmc/distribution_multi.h index 9e84d03d57..75126593f7 100644 --- a/include/openmc/distribution_multi.h +++ b/include/openmc/distribution_multi.h @@ -51,6 +51,8 @@ public: Distribution* phi() const { return phi_.get(); } private: + Direction v_ref_ {1.0, 0.0, 0.0}; //!< reference direction + Direction w_ref_; UPtrDist mu_; //!< Distribution of polar angle UPtrDist phi_; //!< Distribution of azimuthal angle }; diff --git a/include/openmc/geometry_aux.h b/include/openmc/geometry_aux.h index f60f2d649e..4dafdea5c2 100644 --- a/include/openmc/geometry_aux.h +++ b/include/openmc/geometry_aux.h @@ -37,6 +37,12 @@ void adjust_indices(); void assign_temperatures(); +//============================================================================== +//! Finalize densities (compute density multipliers). +//============================================================================== + +void finalize_cell_densities(); + //============================================================================== //! \brief Obtain a list of temperatures that each nuclide/thermal scattering //! table appears at in the model. Later, this list is used to determine the diff --git a/include/openmc/hdf5_interface.h b/include/openmc/hdf5_interface.h index 0092c08f8d..28b0d2b113 100644 --- a/include/openmc/hdf5_interface.h +++ b/include/openmc/hdf5_interface.h @@ -100,8 +100,8 @@ void read_llong(hid_t obj_id, const char* name, long long* buffer, bool indep); void read_string( hid_t obj_id, const char* name, size_t slen, char* buffer, bool indep); -void read_tally_results( - hid_t group_id, hsize_t n_filter, hsize_t n_score, double* results); +void read_tally_results(hid_t group_id, hsize_t n_filter, hsize_t n_score, + hsize_t n_results, double* results); void write_attr_double(hid_t obj_id, int ndim, const hsize_t* dims, const char* name, const double* buffer); void write_attr_int(hid_t obj_id, int ndim, const hsize_t* dims, @@ -114,9 +114,9 @@ void write_int(hid_t group_id, int ndim, const hsize_t* dims, const char* name, void write_llong(hid_t group_id, int ndim, const hsize_t* dims, const char* name, const long long* buffer, bool indep); void write_string(hid_t group_id, int ndim, const hsize_t* dims, size_t slen, - const char* name, char const* buffer, bool indep); -void write_tally_results( - hid_t group_id, hsize_t n_filter, hsize_t n_score, const double* results); + const char* name, const char* buffer, bool indep); +void write_tally_results(hid_t group_id, hsize_t n_filter, hsize_t n_score, + hsize_t n_results, const double* results); } // extern "C" //============================================================================== diff --git a/include/openmc/ifp.h b/include/openmc/ifp.h index 633a262d5f..01904d13c9 100644 --- a/include/openmc/ifp.h +++ b/include/openmc/ifp.h @@ -68,15 +68,14 @@ vector _ifp(const T& value, const vector& data) //! //! Add the IFP information in the IFP banks using the same index //! as the one used to append the fission site to the fission bank. +//! The information stored are the delayed group number and lifetime +//! of the neutron that created the fission event. //! Multithreading protection is guaranteed by the index returned by the //! thread_safe_append call in physics.cpp. //! -//! Needs to be done after the delayed group is found. -//! //! \param[in] p Particle -//! \param[in] site Fission site //! \param[in] idx Bank index from the thread_safe_append call in physics.cpp -void ifp(const Particle& p, const SourceSite& site, int64_t idx); +void ifp(const Particle& p, int64_t idx); //! Resize the IFP banks used in the simulation void resize_simulation_ifp_banks(); diff --git a/include/openmc/material.h b/include/openmc/material.h index fe587a86f9..e36946c71b 100644 --- a/include/openmc/material.h +++ b/include/openmc/material.h @@ -99,6 +99,13 @@ public: //---------------------------------------------------------------------------- // Accessors + //! Get the atom density in [atom/b-cm] + //! \return Density in [atom/b-cm] + double atom_density(int32_t i, double rho_multiplier = 1.0) const + { + return atom_density_(i) * rho_multiplier; + } + //! Get density in [atom/b-cm] //! \return Density in [atom/b-cm] double density() const { return density_; } diff --git a/include/openmc/mcpl_interface.h b/include/openmc/mcpl_interface.h index a76d72e649..a9cce3e69a 100644 --- a/include/openmc/mcpl_interface.h +++ b/include/openmc/mcpl_interface.h @@ -38,6 +38,21 @@ vector mcpl_source_sites(std::string path); void write_mcpl_source_point(const char* filename, span source_bank, const vector& bank_index); +//! Write an MCPL collision track file +//! +//! This function writes collision track data to an MCPL file. Additional +//! collision-specific metadata (such as energy deposition, material info, etc.) +//! is stored in the file header as blob data. +//! +//! \param[in] filename Path to MCPL file +//! \param[in] collision_track_bank Vector of CollisionTrackSites to write to +//! file for this MPI rank. +//! \param[in] bank_index Pointer to vector of site index ranges over all +//! MPI ranks. +void write_mcpl_collision_track(const char* filename, + span collision_track_bank, + const vector& bank_index); + //! Check if MCPL functionality is available bool is_mcpl_interface_available(); diff --git a/include/openmc/mesh.h b/include/openmc/mesh.h index c15e256977..5c9272e93b 100644 --- a/include/openmc/mesh.h +++ b/include/openmc/mesh.h @@ -132,8 +132,14 @@ public: // Constructors and destructor Mesh() = default; Mesh(pugi::xml_node node); + Mesh(hid_t group); virtual ~Mesh() = default; + // Factory method for creating meshes from either an XML node or HDF5 group + template + static const std::unique_ptr& create( + T dataset, const std::string& mesh_type, const std::string& mesh_library); + // Methods //! Perform any preparation needed to support point location within the mesh virtual void prepare_for_point_location() {}; @@ -258,6 +264,7 @@ class StructuredMesh : public Mesh { public: StructuredMesh() = default; StructuredMesh(pugi::xml_node node) : Mesh {node} {}; + StructuredMesh(hid_t group) : Mesh {group} {}; virtual ~StructuredMesh() = default; using MeshIndex = std::array; @@ -423,6 +430,7 @@ class PeriodicStructuredMesh : public StructuredMesh { public: PeriodicStructuredMesh() = default; PeriodicStructuredMesh(pugi::xml_node node) : StructuredMesh {node} {}; + PeriodicStructuredMesh(hid_t group) : StructuredMesh {group} {}; Position local_coords(const Position& r) const override { @@ -442,6 +450,7 @@ public: // Constructors RegularMesh() = default; RegularMesh(pugi::xml_node node); + RegularMesh(hid_t group); // Overridden methods int get_index_in_direction(double r, int i) const override; @@ -481,6 +490,8 @@ public: //! Return the volume for a given mesh index double volume(const MeshIndex& ijk) const override; + int set_grid(); + // Data members double volume_frac_; //!< Volume fraction of each mesh element double element_volume_; //!< Volume of each mesh element @@ -492,6 +503,7 @@ public: // Constructors RectilinearMesh() = default; RectilinearMesh(pugi::xml_node node); + RectilinearMesh(hid_t group); // Overridden methods int get_index_in_direction(double r, int i) const override; @@ -534,6 +546,7 @@ public: // Constructors CylindricalMesh() = default; CylindricalMesh(pugi::xml_node node); + CylindricalMesh(hid_t group); // Overridden methods virtual MeshIndex get_indices(Position r, bool& in_mesh) const override; @@ -598,6 +611,7 @@ public: // Constructors SphericalMesh() = default; SphericalMesh(pugi::xml_node node); + SphericalMesh(hid_t group); // Overridden methods virtual MeshIndex get_indices(Position r, bool& in_mesh) const override; @@ -666,9 +680,9 @@ class UnstructuredMesh : public Mesh { public: // Constructors - UnstructuredMesh() {}; + UnstructuredMesh() { n_dimension_ = 3; }; UnstructuredMesh(pugi::xml_node node); - UnstructuredMesh(const std::string& filename); + UnstructuredMesh(hid_t group); static const std::string mesh_type; virtual std::string get_mesh_type() const override; @@ -775,6 +789,7 @@ public: // Constructors MOABMesh() = default; MOABMesh(pugi::xml_node); + MOABMesh(hid_t group); MOABMesh(const std::string& filename, double length_multiplier = 1.0); MOABMesh(std::shared_ptr external_mbi); @@ -944,6 +959,7 @@ class LibMesh : public UnstructuredMesh { public: // Constructors LibMesh(pugi::xml_node node); + LibMesh(hid_t group); LibMesh(const std::string& filename, double length_multiplier = 1.0); LibMesh(libMesh::MeshBase& input_mesh, double length_multiplier = 1.0); @@ -991,25 +1007,26 @@ public: libMesh::MeshBase* mesh_ptr() const { return m_; }; +protected: + // Methods + + //! Translate a bin value to an element reference + virtual const libMesh::Elem& get_element_from_bin(int bin) const; + + //! Translate an element pointer to a bin index + virtual int get_bin_from_element(const libMesh::Elem* elem) const; + + libMesh::MeshBase* m_; //!< pointer to libMesh MeshBase instance, always set + //!< during intialization private: void initialize() override; void set_mesh_pointer_from_filename(const std::string& filename); void build_eqn_sys(); - // Methods - - //! Translate a bin value to an element reference - const libMesh::Elem& get_element_from_bin(int bin) const; - - //! Translate an element pointer to a bin index - int get_bin_from_element(const libMesh::Elem* elem) const; - // Data members unique_ptr unique_m_ = nullptr; //!< pointer to the libMesh MeshBase instance, only used if mesh is //!< created inside OpenMC - libMesh::MeshBase* m_; //!< pointer to libMesh MeshBase instance, always set - //!< during intialization vector> pl_; //!< per-thread point locators unique_ptr @@ -1023,8 +1040,34 @@ private: libMesh::BoundingBox bbox_; //!< bounding box of the mesh libMesh::dof_id_type first_element_id_; //!< id of the first element in the mesh +}; + +class AdaptiveLibMesh : public LibMesh { +public: + // Constructor + AdaptiveLibMesh( + libMesh::MeshBase& input_mesh, double length_multiplier = 1.0); + + // Overridden methods + int n_bins() const override; + + void add_score(const std::string& var_name) override; + + void set_score_data(const std::string& var_name, const vector& values, + const vector& std_dev) override; + + void write(const std::string& filename) const override; + +protected: + // Overridden methods + int get_bin_from_element(const libMesh::Elem* elem) const override; + + const libMesh::Elem& get_element_from_bin(int bin) const override; + +private: + // Data members + const libMesh::dof_id_type num_active_; //!< cached number of active elements - const bool adaptive_; //!< whether this mesh has adaptivity enabled or not std::vector bin_to_elem_map_; //!< mapping bin indices to dof indices for active //!< elements @@ -1043,6 +1086,11 @@ private: //! \param[in] root XML node void read_meshes(pugi::xml_node root); +//! Read meshes from an HDF5 file +// +//! \param[in] group HDF5 group ("meshes" group) +void read_meshes(hid_t group); + //! Write mesh data to an HDF5 group // //! \param[in] group HDF5 group diff --git a/include/openmc/message_passing.h b/include/openmc/message_passing.h index a1641a9069..ce993776b7 100644 --- a/include/openmc/message_passing.h +++ b/include/openmc/message_passing.h @@ -18,6 +18,7 @@ extern bool master; #ifdef OPENMC_MPI extern MPI_Datatype source_site; +extern MPI_Datatype collision_track_site; extern MPI_Comm intracomm; #endif diff --git a/include/openmc/nuclide.h b/include/openmc/nuclide.h index 329c776d03..60b88a153b 100644 --- a/include/openmc/nuclide.h +++ b/include/openmc/nuclide.h @@ -164,8 +164,8 @@ namespace data { // Minimum/maximum transport energy for each particle type. Order corresponds to // that of the ParticleType enum -extern array energy_min; -extern array energy_max; +extern array energy_min; +extern array energy_max; //! Minimum temperature in [K] that nuclide data is available at extern double temperature_min; diff --git a/include/openmc/particle_data.h b/include/openmc/particle_data.h index 2c00e4e3c2..16d8a71f9d 100644 --- a/include/openmc/particle_data.h +++ b/include/openmc/particle_data.h @@ -56,6 +56,25 @@ struct SourceSite { int64_t progeny_id; }; +struct CollisionTrackSite { + Position r; + Direction u; + double E; + double dE; + double time {0.0}; + double wgt {1.0}; + int event_mt {0}; + int delayed_group {0}; + int cell_id {0}; + int nuclide_id; + int material_id {0}; + int universe_id {0}; + int n_collision {0}; + ParticleType particle; + int64_t parent_id; + int64_t progeny_id; +}; + //! State of a particle used for particle track files struct TrackState { Position r; //!< Position in [cm] @@ -154,9 +173,10 @@ struct NuclideMicroXS { // Energy and temperature last used to evaluate these cross sections. If // these values have changed, then the cross sections must be re-evaluated. - double last_E {0.0}; //!< Last evaluated energy - double last_sqrtkT {0.0}; //!< Last temperature in sqrt(Boltzmann constant - //!< * temperature (eV)) + double last_E {0.0}; //!< Last evaluated energy + double last_sqrtkT {0.0}; //!< Last temperature in sqrt(Boltzmann constant + //!< * temperature (eV)) + double ncrystal_xs {-1.0}; //!< NCrystal cross section }; //============================================================================== @@ -377,47 +397,25 @@ public: #ifdef OPENMC_DAGMC_ENABLED // DagMC state variables - moab::DagMC::RayHistory& history() - { - return history_; - } - Direction& last_dir() - { - return last_dir_; - } + moab::DagMC::RayHistory& history() { return history_; } + Direction& last_dir() { return last_dir_; } #endif // material of current and last cell - int& material() - { - return material_; - } - const int& material() const - { - return material_; - } - int& material_last() - { - return material_last_; - } - const int& material_last() const - { - return material_last_; - } + int& material() { return material_; } + const int& material() const { return material_; } + int& material_last() { return material_last_; } + const int& material_last() const { return material_last_; } // temperature of current and last cell - double& sqrtkT() - { - return sqrtkT_; - } - const double& sqrtkT() const - { - return sqrtkT_; - } - double& sqrtkT_last() - { - return sqrtkT_last_; - } + double& sqrtkT() { return sqrtkT_; } + const double& sqrtkT() const { return sqrtkT_; } + double& sqrtkT_last() { return sqrtkT_last_; } + + // density multiplier of the current and last cell + double& density_mult() { return density_mult_; } + const double& density_mult() const { return density_mult_; } + double& density_mult_last() { return density_mult_last_; } private: int64_t id_ {-1}; //!< Unique ID @@ -447,6 +445,9 @@ private: double sqrtkT_ {-1.0}; //!< sqrt(k_Boltzmann * temperature) in eV double sqrtkT_last_ {0.0}; //!< last temperature + double density_mult_ {1.0}; //!< density multiplier + double density_mult_last_ {1.0}; //!< last density multiplier + double collision_distance_ {INFTY}; #ifdef OPENMC_DAGMC_ENABLED @@ -653,6 +654,7 @@ public: int& event_mt() { return event_mt_; } // MT number of collision const int& event_mt() const { return event_mt_; } int& delayed_group() { return delayed_group_; } // delayed group + const int& delayed_group() const { return delayed_group_; } const int& parent_nuclide() const { return parent_nuclide_; } int& parent_nuclide() { return parent_nuclide_; } // Parent nuclide diff --git a/include/openmc/physics.h b/include/openmc/physics.h index f62f43a02f..2472d97993 100644 --- a/include/openmc/physics.h +++ b/include/openmc/physics.h @@ -10,13 +10,6 @@ namespace openmc { -//============================================================================== -// Constants -//============================================================================== - -// Monoatomic ideal-gas scattering treatment threshold -constexpr double FREE_GAS_THRESHOLD {400.0}; - //============================================================================== // Non-member functions //============================================================================== diff --git a/include/openmc/random_ray/flat_source_domain.h b/include/openmc/random_ray/flat_source_domain.h index 78351fcc5f..4df4e5d8d3 100644 --- a/include/openmc/random_ray/flat_source_domain.h +++ b/include/openmc/random_ray/flat_source_domain.h @@ -27,8 +27,9 @@ public: //---------------------------------------------------------------------------- // Methods - virtual void update_neutron_source(double k_eff); - double compute_k_eff(double k_eff_old) const; + virtual void update_single_neutron_source(SourceRegionHandle& srh); + virtual void update_all_neutron_sources(); + void compute_k_eff(); virtual void normalize_scalar_flux_and_volumes( double total_active_distance_per_iteration); @@ -41,7 +42,7 @@ public: void output_to_vtk() const; void convert_external_sources(); void count_external_source_regions(); - void set_adjoint_sources(const vector& forward_flux); + void set_adjoint_sources(); void flux_swap(); virtual double evaluate_flux_at_point(Position r, int64_t sr, int g) const; double compute_fixed_source_normalization_factor() const; @@ -54,9 +55,8 @@ public: bool is_target_void); void apply_mesh_to_cell_and_children(int32_t i_cell, int32_t mesh_idx, int32_t target_material_id, bool is_target_void); - void prepare_base_source_regions(); SourceRegionHandle get_subdivided_source_region_handle( - int64_t sr, int mesh_bin, Position r, double dist, Direction u); + SourceRegionKey sr_key, Position r, Direction u); void finalize_discovered_source_regions(); void apply_transport_stabilization(); int64_t n_source_regions() const @@ -67,6 +67,10 @@ public: { return source_regions_.n_source_regions() * negroups_; } + int64_t lookup_base_source_region_idx(const GeometryState& p) const; + SourceRegionKey lookup_source_region_key(const GeometryState& p) const; + int64_t lookup_mesh_bin(int64_t sr, Position r) const; + int lookup_mesh_idx(int64_t sr) const; //---------------------------------------------------------------------------- // Static Data members @@ -86,6 +90,7 @@ public: //---------------------------------------------------------------------------- // Public Data members + double k_eff_ {1.0}; // Eigenvalue bool mapped_all_tallies_ {false}; // If all source regions have been visited int64_t n_external_source_regions_ {0}; // Total number of source regions with @@ -110,14 +115,6 @@ public: // The abstract container holding all source region-specific data SourceRegionContainer source_regions_; - // Base source region container. When source region subdivision via mesh - // is in use, this container holds the original (non-subdivided) material - // filled cell instance source regions. These are useful as they can be - // initialized with external source and mesh domain information ahead of time. - // Then, dynamically discovered source regions can be initialized by cloning - // their base region. - SourceRegionContainer base_source_regions_; - // Parallel hash map holding all source regions discovered during // a single iteration. This is a threadsafe data structure that is cleaned // out after each iteration and stored in the "source_regions_" container. @@ -134,8 +131,17 @@ public: // Map that relates a SourceRegionKey to the external source index. This map // is used to check if there are any point sources within a subdivided source // region at the time it is discovered. - std::unordered_map - point_source_map_; + std::unordered_map, SourceRegionKey::HashFunctor> + external_point_source_map_; + + // Map that relates a base source region index to the external source index. + // This map is used to check if there are any volumetric sources within a + // subdivided source region at the time it is discovered. + std::unordered_map> external_volumetric_source_map_; + + // Map that relates a base source region index to a mesh index. This map + // is used to check which subdivision mesh is present in a source region. + std::unordered_map mesh_map_; // If transport corrected MGXS data is being used, there may be negative // in-group scattering cross sections that can result in instability in MOC @@ -147,12 +153,11 @@ protected: //---------------------------------------------------------------------------- // Methods void apply_external_source_to_source_region( - Discrete* discrete, double strength_factor, SourceRegionHandle& srh); - void apply_external_source_to_cell_instances(int32_t i_cell, - Discrete* discrete, double strength_factor, int target_material_id, - const vector& instances); - void apply_external_source_to_cell_and_children(int32_t i_cell, - Discrete* discrete, double strength_factor, int32_t target_material_id); + int src_idx, SourceRegionHandle& srh); + void apply_external_source_to_cell_instances(int32_t i_cell, int src_idx, + int target_material_id, const vector& instances); + void apply_external_source_to_cell_and_children( + int32_t i_cell, int src_idx, int32_t target_material_id); virtual void set_flux_to_flux_plus_source(int64_t sr, double volume, int g); void set_flux_to_source(int64_t sr, int g); virtual void set_flux_to_old_flux(int64_t sr, int g); @@ -165,6 +170,9 @@ protected: simulation_volume_; // Total physical volume of the simulation domain, as // defined by the 3D box of the random ray source + double + fission_rate_; // The system's fission rate (per cm^3), in eigenvalue mode + // Volumes for each tally and bin/score combination. This intermediate data // structure is used when tallying quantities that must be normalized by // volume (i.e., flux). The vector is index by tally index, while the inner 2D diff --git a/include/openmc/random_ray/linear_source_domain.h b/include/openmc/random_ray/linear_source_domain.h index 67fdd99f88..0098c78200 100644 --- a/include/openmc/random_ray/linear_source_domain.h +++ b/include/openmc/random_ray/linear_source_domain.h @@ -20,7 +20,7 @@ class LinearSourceDomain : public FlatSourceDomain { public: //---------------------------------------------------------------------------- // Methods - void update_neutron_source(double k_eff) override; + void update_single_neutron_source(SourceRegionHandle& srh) override; void normalize_scalar_flux_and_volumes( double total_active_distance_per_iteration) override; diff --git a/include/openmc/random_ray/random_ray.h b/include/openmc/random_ray/random_ray.h index abf2a26881..40c67ef954 100644 --- a/include/openmc/random_ray/random_ray.h +++ b/include/openmc/random_ray/random_ray.h @@ -48,7 +48,6 @@ public: static double distance_active_; // Active ray length static unique_ptr ray_source_; // Starting source for ray sampling static RandomRaySourceShape source_shape_; // Flag for linear source - static bool mesh_subdivision_enabled_; // Flag for mesh subdivision static RandomRaySampleMethod sample_method_; // Flag for sampling method //---------------------------------------------------------------------------- diff --git a/include/openmc/random_ray/random_ray_simulation.h b/include/openmc/random_ray/random_ray_simulation.h index b94e7401b3..3dec48bf26 100644 --- a/include/openmc/random_ray/random_ray_simulation.h +++ b/include/openmc/random_ray/random_ray_simulation.h @@ -21,11 +21,7 @@ public: // Methods void compute_segment_correction_factors(); void apply_fixed_sources_and_mesh_domains(); - void prepare_fixed_sources_adjoint(vector& forward_flux, - SourceRegionContainer& forward_source_regions, - SourceRegionContainer& forward_base_source_regions, - std::unordered_map& - forward_source_region_map); + void prepare_fixed_sources_adjoint(); void simulate(); void output_simulation_results() const; void instability_check( @@ -45,9 +41,6 @@ private: // Contains all flat source region data unique_ptr domain_; - // Random ray eigenvalue - double k_eff_ {1.0}; - // Tracks the average FSR miss rate for analysis and reporting double avg_miss_rate_ {0.0}; diff --git a/include/openmc/random_ray/source_region.h b/include/openmc/random_ray/source_region.h index 5c5b31f392..0f5a747fff 100644 --- a/include/openmc/random_ray/source_region.h +++ b/include/openmc/random_ray/source_region.h @@ -308,7 +308,6 @@ public: //---------------------------------------------------------------------------- // Constructors SourceRegion(int negroups, bool is_linear); - SourceRegion(const SourceRegionHandle& handle, int64_t parent_sr); SourceRegion() = default; //---------------------------------------------------------------------------- diff --git a/include/openmc/settings.h b/include/openmc/settings.h index 069d94c3b2..b369c99fef 100644 --- a/include/openmc/settings.h +++ b/include/openmc/settings.h @@ -32,6 +32,24 @@ enum class IFPParameter { GenerationTime, }; +struct CollisionTrackConfig { + bool mcpl_write {false}; //!< Write collision tracks using MCPL? + std::unordered_set + cell_ids; //!< Cell ids where collisions will be written + std::unordered_set + mt_numbers; //!< MT Numbers where collisions will be written + std::unordered_set + universe_ids; //!< Universe IDs where collisions will be written + std::unordered_set + material_ids; //!< Material IDs where collisions will be written + std::unordered_set + nuclides; //!< Nuclides where collisions will be written + double deposited_energy_threshold {0.0}; //!< Minimum deposited energy [eV] + int64_t max_collisions { + 1000}; //!< Maximum events recorded per collision track file + int64_t max_files {1}; //!< Maximum number of collision track files +}; + //============================================================================== // Global variable declarations //============================================================================== @@ -41,6 +59,7 @@ namespace settings { // Boolean flags extern bool assume_separate; //!< assume tallies are spatially separate? extern bool check_overlaps; //!< check overlaps in geometry? +extern bool collision_track; //!< flag to use collision track feature? extern bool confidence_intervals; //!< use confidence intervals for results? extern bool create_fission_neutrons; //!< create fission neutrons (fixed source)? @@ -145,11 +164,15 @@ extern std::unordered_set statepoint_batch; //!< Batches when state should be written extern std::unordered_set source_write_surf_id; //!< Surface ids where sources will be written +extern CollisionTrackConfig collision_track_config; extern double source_rejection_fraction; //!< Minimum fraction of source sites //!< that must be accepted +extern double free_gas_threshold; //!< Threshold multiplier for free gas + //!< scattering treatment extern int max_history_splits; //!< maximum number of particle splits for weight windows +extern int max_secondaries; //!< maximum number of secondaries in the bank extern int64_t ssw_max_particles; //!< maximum number of particles to be //!< banked on surfaces per process extern int64_t ssw_max_files; //!< maximum number of surface source files diff --git a/include/openmc/simulation.h b/include/openmc/simulation.h index 3e4e24e1d0..9a6cf1b213 100644 --- a/include/openmc/simulation.h +++ b/include/openmc/simulation.h @@ -22,6 +22,7 @@ constexpr int STATUS_EXIT_ON_TRIGGER {2}; namespace simulation { +extern int ct_current_file; //!< current collision track file index extern "C" int current_batch; //!< current batch extern "C" int current_gen; //!< current fission generation extern "C" bool initialized; //!< has simulation been initialized? diff --git a/include/openmc/tallies/tally.h b/include/openmc/tallies/tally.h index 8c088c4608..374daff92a 100644 --- a/include/openmc/tallies/tally.h +++ b/include/openmc/tallies/tally.h @@ -106,6 +106,8 @@ public: bool writable() const { return writable_; } + bool higher_moments() const { return higher_moments_; } + //---------------------------------------------------------------------------- // Other methods. @@ -190,6 +192,9 @@ private: //! Whether to multiply by atom density for reaction rates bool multiply_density_ {true}; + //! Whether to accumulate higher moments (third and fourth) + bool higher_moments_ {false}; + int64_t index_; }; @@ -203,11 +208,14 @@ extern vector> tallies; extern vector active_tallies; extern vector active_analog_tallies; extern vector active_tracklength_tallies; +extern vector active_timed_tracklength_tallies; extern vector active_collision_tallies; extern vector active_meshsurf_tallies; extern vector active_surface_tallies; extern vector active_pulse_height_tallies; extern vector pulse_height_cells; +extern vector time_grid; + } // namespace model namespace simulation { @@ -239,6 +247,13 @@ void read_tallies_xml(pugi::xml_node root); //! batch to a new random variable void accumulate_tallies(); +//! Determine distance to next time boundary +// +//! \param time Current time of particle +//! \param speed Speed of particle +//! \return Distance to next time boundary (or INFTY if none) +double distance_to_time_boundary(double time, double speed); + //! Determine which tallies should be active void setup_active_tallies(); diff --git a/include/openmc/tallies/tally_scoring.h b/include/openmc/tallies/tally_scoring.h index 28f1f16223..c3ab779e6a 100644 --- a/include/openmc/tallies/tally_scoring.h +++ b/include/openmc/tallies/tally_scoring.h @@ -91,6 +91,16 @@ void score_analog_tally_mg(Particle& p); //! \param distance The distance in [cm] traveled by the particle void score_tracklength_tally(Particle& p, double distance); +//! Score time filtered tallies using a tracklength estimate of the flux. +// +//! This is triggered at every event (surface crossing, lattice crossing, or +//! collision) and thus cannot be done for tallies that require post-collision +//! information. +// +//! \param p The particle being tracked +//! \param total_distance The distance in [cm] traveled by the particle +void score_timed_tracklength_tally(Particle& p, double total_distance); + //! Score surface or mesh-surface tallies for particle currents. // //! \param p The particle being tracked diff --git a/include/openmc/urr.h b/include/openmc/urr.h index 3978c7b86a..1e60371584 100644 --- a/include/openmc/urr.h +++ b/include/openmc/urr.h @@ -27,10 +27,10 @@ public: double heating; }; - Interpolation interp_; //!< interpolation type - int inelastic_flag_; //!< inelastic competition flag - int absorption_flag_; //!< other absorption flag - bool multiply_smooth_; //!< multiply by smooth cross section? + Interpolation interp_; //!< interpolation type + int inelastic_flag_; //!< inelastic competition flag + int absorption_flag_; //!< other absorption flag + bool multiply_smooth_; //!< multiply by smooth cross section? vector energy_; //!< incident energies auto n_energy() const { return energy_.size(); } diff --git a/man/man1/openmc.1 b/man/man1/openmc.1 index 7826a759a1..30e8b2ce47 100644 --- a/man/man1/openmc.1 +++ b/man/man1/openmc.1 @@ -39,6 +39,9 @@ Use \fIN\fP OpenMP threads. .B "\-t\fR, \fP\-\-track" Write tracks for all particles (up to max_tracks). .TP +.BI \-q " V" "\fR,\fP \-\-verbosity" " V" +Set the output verbosity to \fIV\fP. +.TP .B "\-v\fR, \fP\-\-version" Show version information. .TP diff --git a/openmc/__init__.py b/openmc/__init__.py index bb972b4e6a..c204929c84 100644 --- a/openmc/__init__.py +++ b/openmc/__init__.py @@ -37,7 +37,7 @@ from openmc.tracks import * from .config import * # Import a few names from the model module -from openmc.model import Model +from openmc.model import Model, SearchResult from . import examples diff --git a/openmc/cell.py b/openmc/cell.py index 7d450eb7fe..ebabcf7620 100644 --- a/openmc/cell.py +++ b/openmc/cell.py @@ -72,6 +72,10 @@ class Cell(IDManagerMixin): temperature : float or iterable of float Temperature of the cell in Kelvin. Multiple temperatures can be given to give each distributed cell instance a unique temperature. + density : float or iterable of float + Density of the cell in [g/cm3]. Multiple densities can be given to give + each distributed cell instance a unique density. Densities set here will + override the density set on materials used to fill the cell. translation : Iterable of float If the cell is filled with a universe, this array specifies a vector that is used to translate (shift) the universe. @@ -109,6 +113,7 @@ class Cell(IDManagerMixin): self._rotation = None self._rotation_matrix = None self._temperature = None + self._density = None self._translation = None self._paths = None self._num_instances = None @@ -146,6 +151,7 @@ class Cell(IDManagerMixin): if self.fill_type == 'material': string += '\t{0: <15}=\t{1}\n'.format('Temperature', self.temperature) + string += '\t{0: <15}=\t{1}\n'.format('Density', self.density) string += '{: <16}=\t{}\n'.format('\tTranslation', self.translation) string += '{: <16}=\t{}\n'.format('\tVolume', self.volume) @@ -262,6 +268,30 @@ class Cell(IDManagerMixin): else: self._temperature = temperature + @property + def density(self): + return self._density + + @density.setter + def density(self, density): + # Make sure densities are greater than zero + cv.check_type('cell density', density, (Iterable, Real), none_ok=True) + if isinstance(density, Iterable): + cv.check_type('cell density', density, Iterable, Real) + for rho in density: + cv.check_greater_than('cell density', rho, 0.0, True) + elif isinstance(density, Real): + cv.check_greater_than('cell density', density, 0.0, True) + + # If this cell is filled with a universe or lattice, propagate + # densities to all cells contained. Otherwise, simply assign it. + if self.fill_type in ('universe', 'lattice'): + for c in self.get_all_cells().values(): + if c.fill_type == 'material': + c._density = density + else: + self._density = density + @property def translation(self): return self._translation @@ -530,6 +560,8 @@ class Cell(IDManagerMixin): clone.volume = self.volume if self.temperature is not None: clone.temperature = self.temperature + if self.density is not None: + clone.density = self.density if self.translation is not None: clone.translation = self.translation if self.rotation is not None: @@ -662,6 +694,12 @@ class Cell(IDManagerMixin): else: element.set("temperature", str(self.temperature)) + if self.density is not None: + if isinstance(self.density, Iterable): + element.set("density", ' '.join(str(t) for t in self.density)) + else: + element.set("density", str(self.density)) + if self.translation is not None: element.set("translation", ' '.join(map(str, self.translation))) @@ -723,10 +761,13 @@ class Cell(IDManagerMixin): c.temperature = temperature else: c.temperature = temperature[0] + density = get_elem_list(elem, 'density', float) + if density is not None: + c.density = density if len(density) > 1 else density[0] v = get_text(elem, 'volume') if v is not None: c.volume = float(v) - for key in ('temperature', 'rotation', 'translation'): + for key in ('temperature', 'density', 'rotation', 'translation'): values = get_elem_list(elem, key, float) if values is not None: if key == 'rotation' and len(values) == 9: diff --git a/openmc/checkvalue.py b/openmc/checkvalue.py index 4fa205b14f..5ff2cf9ac5 100644 --- a/openmc/checkvalue.py +++ b/openmc/checkvalue.py @@ -37,7 +37,7 @@ def check_type(name, value, expected_type, expected_iter_type=None, *, none_ok=F [t.__name__ for t in expected_type])) else: msg = (f'Unable to set "{name}" to "{value}" which is not of type "' - f'{expected_type.__name__}"') + f'{expected_type}"') raise TypeError(msg) if expected_iter_type: diff --git a/openmc/dagmc.py b/openmc/dagmc.py index d1265be268..3cb48ddf17 100644 --- a/openmc/dagmc.py +++ b/openmc/dagmc.py @@ -302,6 +302,8 @@ class DAGMCUniverse(openmc.UniverseBase): dagmc_element = ET.Element('dagmc_universe') dagmc_element.set('id', str(self.id)) + if self.name: + dagmc_element.set('name', self.name) if self.auto_geom_ids: dagmc_element.set('auto_geom_ids', 'true') if self.auto_mat_ids: diff --git a/openmc/data/data.py b/openmc/data/data.py index 2142a5dc90..5ecadd37be 100644 --- a/openmc/data/data.py +++ b/openmc/data/data.py @@ -324,7 +324,7 @@ def atomic_mass(isotope): # isotopes of their element (e.g. C0), calculate the atomic mass as # the sum of the atomic mass times the natural abundance of the isotopes # that make up the element. - for element in ['C', 'Zn', 'Pt', 'Os', 'Tl']: + for element in ['C', 'Zn', 'Pt', 'Os', 'Tl', 'V']: isotope_zero = element.lower() + '0' _ATOMIC_MASS[isotope_zero] = 0. for iso, abundance in isotopes(element): diff --git a/openmc/data/decay.py b/openmc/data/decay.py index 1a11d3614f..7cd4bf43d4 100644 --- a/openmc/data/decay.py +++ b/openmc/data/decay.py @@ -13,7 +13,7 @@ import openmc.checkvalue as cv from openmc.exceptions import DataError from openmc.mixin import EqualityMixin from openmc.stats import Discrete, Tabular, Univariate, combine_distributions -from .data import ATOMIC_SYMBOL, ATOMIC_NUMBER +from .data import ATOMIC_NUMBER, gnds_name from .function import INTERPOLATION_SCHEME from .endf import Evaluation, get_head_record, get_list_record, get_tab1_record @@ -126,9 +126,7 @@ class FissionProductYields(EqualityMixin): for j in range(n_products): Z, A = divmod(int(values[4*j]), 1000) isomeric_state = int(values[4*j + 1]) - name = ATOMIC_SYMBOL[Z] + str(A) - if isomeric_state > 0: - name += f'_m{isomeric_state}' + name = gnds_name(Z, A, isomeric_state) yield_j = ufloat(values[4*j + 2], values[4*j + 3]) yields[name] = yield_j @@ -256,10 +254,7 @@ class DecayMode(EqualityMixin): A += delta_A Z += delta_Z - if self._daughter_state > 0: - return f'{ATOMIC_SYMBOL[Z]}{A}_m{self._daughter_state}' - else: - return f'{ATOMIC_SYMBOL[Z]}{A}' + return gnds_name(Z, A, self._daughter_state) @property def parent(self): @@ -348,10 +343,7 @@ class Decay(EqualityMixin): self.nuclide['atomic_number'] = Z self.nuclide['mass_number'] = A self.nuclide['isomeric_state'] = metastable - if metastable > 0: - self.nuclide['name'] = f'{ATOMIC_SYMBOL[Z]}{A}_m{metastable}' - else: - self.nuclide['name'] = f'{ATOMIC_SYMBOL[Z]}{A}' + self.nuclide['name'] = gnds_name(Z, A, metastable) self.nuclide['mass'] = items[1] # AWR self.nuclide['excited_state'] = items[2] # State of the original nuclide self.nuclide['stable'] = (items[4] == 1) # Nucleus stability flag @@ -591,7 +583,7 @@ def decay_photon_energy(nuclide: str) -> Univariate | None: openmc.stats.Univariate or None Distribution of energies in [eV] of photons emitted from decay, or None if no photon source exists. Note that the probabilities represent - intensities, given as [Bq]. + intensities, given as [Bq/atom] (in other words, decay constants). """ if not _DECAY_PHOTON_ENERGY: chain_file = openmc.config.get('chain_file') diff --git a/openmc/data/neutron.py b/openmc/data/neutron.py index 95a3424ea4..628801e5e9 100644 --- a/openmc/data/neutron.py +++ b/openmc/data/neutron.py @@ -11,7 +11,7 @@ import h5py from . import HDF5_VERSION, HDF5_VERSION_MAJOR from .ace import Library, Table, get_table, get_metadata -from .data import ATOMIC_SYMBOL, K_BOLTZMANN, EV_PER_MEV +from .data import ATOMIC_SYMBOL, K_BOLTZMANN, EV_PER_MEV, gnds_name from .endf import ( Evaluation, SUM_RULES, get_head_record, get_tab1_record, get_evaluations) from .fission_energy import FissionEnergyRelease @@ -678,11 +678,7 @@ class IncidentNeutron(EqualityMixin): temperature = ev.target['temperature'] # Determine name - element = ATOMIC_SYMBOL[atomic_number] - if metastable > 0: - name = f'{element}{mass_number}_m{metastable}' - else: - name = f'{element}{mass_number}' + name = gnds_name(atomic_number, mass_number, metastable) # Instantiate incident neutron data data = cls(name, atomic_number, mass_number, metastable, diff --git a/openmc/deplete/__init__.py b/openmc/deplete/__init__.py index 8a9509e900..052e224596 100644 --- a/openmc/deplete/__init__.py +++ b/openmc/deplete/__init__.py @@ -17,6 +17,7 @@ from .stepresult import * from .results import * from .integrators import * from .transfer_rates import * +from .r2s import * from . import abc from . import cram from . import helpers diff --git a/openmc/deplete/abc.py b/openmc/deplete/abc.py index e6d4c15127..32f468306d 100644 --- a/openmc/deplete/abc.py +++ b/openmc/deplete/abc.py @@ -12,6 +12,7 @@ from copy import deepcopy from inspect import signature from numbers import Real, Integral from pathlib import Path +from textwrap import dedent import time from typing import Optional, Union, Sequence from warnings import warn @@ -526,7 +527,7 @@ class Integrator(ABC): r"""Abstract class for solving the time-integration for depletion """ - _params = r""" + _params = dedent(r""" Parameters ---------- operator : openmc.deplete.abc.TransportOperator @@ -617,7 +618,7 @@ class Integrator(ABC): .. versionadded:: 0.15.3 - """ + """) def __init__( self, @@ -630,17 +631,7 @@ class Integrator(ABC): solver: str = "cram48", continue_timesteps: bool = False, ): - # Check number of stages previously used - if operator.prev_res is not None: - res = operator.prev_res[-1] - if res.data.shape[0] != self._num_stages: - raise ValueError( - "{} incompatible with previous restart calculation. " - "Previous scheme used {} intermediate solutions, while " - "this uses {}".format( - self.__class__.__name__, res.data.shape[0], - self._num_stages)) - elif continue_timesteps: + if continue_timesteps and operator.prev_res is None: raise ValueError("Continuation run requires passing prev_results.") self.operator = operator self.chain = operator.chain @@ -774,12 +765,8 @@ class Integrator(ABC): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from intermediate transport - simulations + n_end : list of numpy.ndarray + Concentrations at end of timestep """ @property @@ -810,9 +797,9 @@ class Integrator(ABC): """Get beginning of step concentrations, reaction rates from restart""" res = self.operator.prev_res[-1] # Depletion methods expect list of arrays - bos_conc = list(res.data[0]) - rates = res.rates[0] - k = ufloat(res.k[0, 0], res.k[0, 1]) + bos_conc = list(res.data) + rates = res.rates + k = ufloat(res.k[0], res.k[1]) if res.source_rate != 0.0: # Scale reaction rates by ratio of source rates @@ -854,7 +841,8 @@ class Integrator(ABC): self, final_step: bool = True, output: bool = True, - path: PathLike = 'depletion_results.h5' + path: PathLike = 'depletion_results.h5', + write_rates: bool = False ): """Perform the entire depletion process across all steps @@ -873,6 +861,11 @@ class Integrator(ABC): Path to file to write. Defaults to 'depletion_results.h5'. .. versionadded:: 0.15.0 + write_rates : bool, optional + Whether reaction rates should be written to the results file for + each step. Defaults to ``False`` to reduce file size. + + .. versionadded:: 0.15.3 """ with change_directory(self.operator.output_dir): n = self.operator.initial_condition() @@ -889,18 +882,22 @@ class Integrator(ABC): n, res = self._get_bos_data_from_restart(source_rate, n) # Solve Bateman equations over time interval - proc_time, n_list, res_list = self(n, res.rates, dt, source_rate, i) + proc_time, n_end = self(n, res.rates, dt, source_rate, i) - # Insert BOS concentration, transport results - n_list.insert(0, n) - res_list.insert(0, res) - - # Remove actual EOS concentration for next step - n = n_list.pop() - - StepResult.save(self.operator, n_list, res_list, [t, t + dt], - source_rate, self._i_res + i, proc_time, path) + StepResult.save( + self.operator, + n, + res, + [t, t + dt], + source_rate, + self._i_res + i, + proc_time, + write_rates=write_rates, + path=path + ) + # Update for next step + n = n_end t += dt # Final simulation -- in the case that final_step is False, a zero @@ -909,9 +906,18 @@ class Integrator(ABC): # solve) if output and final_step and comm.rank == 0: print(f"[openmc.deplete] t={t} (final operator evaluation)") - res_list = [self.operator(n, source_rate if final_step else 0.0)] - StepResult.save(self.operator, [n], res_list, [t, t], - source_rate, self._i_res + len(self), proc_time, path) + res_final = self.operator(n, source_rate if final_step else 0.0) + StepResult.save( + self.operator, + n, + res_final, + [t, t], + source_rate, + self._i_res + len(self), + proc_time, + write_rates=write_rates, + path=path + ) self.operator.write_bos_data(len(self) + self._i_res) self.operator.finalize() @@ -1012,6 +1018,36 @@ class Integrator(ABC): material, composition, rate, rate_units, timesteps) + def add_redox(self, material, buffer, oxidation_states, timesteps=None): + """Add redox control to depletable material. + + Parameters + ---------- + material : openmc.Material or str or int + Depletable material + buffer : dict + Dictionary of buffer nuclides used to maintain redox balance. Keys + are nuclide names (strings) and values are their respective + fractions (float) that collectively sum to 1. + oxidation_states : dict + User-defined oxidation states for elements. Keys are element symbols + (e.g., 'H', 'He'), and values are their corresponding oxidation + states as integers (e.g., +1, 0). + timesteps : list of int, optional + List of timestep indices where to set external source rates. + Defaults to None, which means the external source rate is set for + all timesteps. + """ + if self.transfer_rates is None: + if hasattr(self.operator, 'model'): + materials = self.operator.model.materials + elif hasattr(self.operator, 'materials'): + materials = self.operator.materials + self.transfer_rates = TransferRates( + self.operator, materials, len(self.timesteps)) + + self.transfer_rates.set_redox(material, buffer, oxidation_states, timesteps) + @add_params class SIIntegrator(Integrator): r"""Abstract class for the Stochastic Implicit Euler integrators @@ -1020,7 +1056,7 @@ class SIIntegrator(Integrator): the number of particles used in initial transport calculation """ - _params = r""" + _params = dedent(r""" Parameters ---------- operator : openmc.deplete.abc.TransportOperator @@ -1108,7 +1144,7 @@ class SIIntegrator(Integrator): .. versionadded:: 0.12 - """ + """) def __init__( self, @@ -1140,10 +1176,40 @@ class SIIntegrator(Integrator): self.operator.settings.particles //= self.n_steps return inherited + @abstractmethod + def __call__(self, n, rates, dt, source_rate, i): + """Perform the integration across one time step + + Parameters + ---------- + n : list of numpy.ndarray + List of atom number arrays for each material. Each array has + shape ``(n_nucs,)`` where ``n_nucs`` is the number of nuclides + rates : openmc.deplete.ReactionRates + Reaction rates (from transport operator) + dt : float + Time step in [s] + source_rate : float + Power in [W] or source rate in [neutron/sec] + i : int + Current time step index + + Returns + ------- + proc_time : float + Time spent in transport simulation + n_end : list of numpy.ndarray + Updated atom number densities for each material + op_result : OperatorResult + Eigenvalue and reaction rates resulting from transport simulation + + """ + def integrate( self, output: bool = True, - path: PathLike = "depletion_results.h5" + path: PathLike = "depletion_results.h5", + write_rates: bool = False ): """Perform the entire depletion process across all steps @@ -1155,11 +1221,17 @@ class SIIntegrator(Integrator): Path to file to write. Defaults to 'depletion_results.h5'. .. versionadded:: 0.15.0 + write_rates : bool, optional + Whether reaction rates should be written to the results file for + each step. Defaults to ``False`` to reduce file size. + + .. versionadded:: 0.15.3 """ with change_directory(self.operator.output_dir): n = self.operator.initial_condition() t, self._i_res = self._get_start_data() + res_end = None # Will be set in first iteration for i, (dt, p) in enumerate(self): if output: print(f"[openmc.deplete] t={t} s, dt={dt} s, source={p}") @@ -1169,28 +1241,38 @@ class SIIntegrator(Integrator): n, res = self._get_bos_data_from_operator(i, p, n) else: n, res = self._get_bos_data_from_restart(p, n) - else: - # Pull rates, k from previous iteration w/o - # re-running transport - res = res_list[-1] # defined in previous i iteration - proc_time, n_list, res_list = self(n, res.rates, dt, p, i) + proc_time, n_end, res_end = self(n, res.rates, dt, p, i) - # Insert BOS concentration, transport results - n_list.insert(0, n) - res_list.insert(0, res) - - # Remove actual EOS concentration for next step - n = n_list.pop() - - StepResult.save(self.operator, n_list, res_list, [t, t + dt], - p, self._i_res + i, proc_time, path) + StepResult.save( + self.operator, + n, + res, + [t, t + dt], + p, + self._i_res + i, + proc_time, + write_rates=write_rates, + path=path + ) + # Update for next step + n = n_end + res = res_end t += dt # No final simulation for SIE, use last iteration results - StepResult.save(self.operator, [n], [res_list[-1]], [t, t], - p, self._i_res + len(self), proc_time, path) + StepResult.save( + self.operator, + n, + res_end, + [t, t], + p, + self._i_res + len(self), + proc_time, + write_rates=write_rates, + path=path + ) self.operator.write_bos_data(self._i_res + len(self)) self.operator.finalize() diff --git a/openmc/deplete/chain.py b/openmc/deplete/chain.py index f1a23317fb..873d7ca892 100644 --- a/openmc/deplete/chain.py +++ b/openmc/deplete/chain.py @@ -7,6 +7,7 @@ loaded from an .xml file and all the nuclides are linked together. from io import StringIO from itertools import chain import math +import numpy as np import re from collections import defaultdict, namedtuple from collections.abc import Mapping, Iterable @@ -627,9 +628,15 @@ class Chain: """ reactions = set() - # Use DOK matrix as intermediate representation for matrix n = len(self) - matrix = sp.dok_matrix((n, n)) + + # we accumulate indices and value entries for everything and create the matrix + # in one step at the end to avoid expensive index checks scipy otherwise does. + rows, cols, vals = [], [], [] + def setval(i, j, val): + rows.append(i) + cols.append(j) + vals.append(val) if fission_yields is None: fission_yields = self.get_default_fission_yields() @@ -639,7 +646,7 @@ class Chain: if nuc.half_life is not None: decay_constant = math.log(2) / nuc.half_life if decay_constant != 0.0: - matrix[i, i] -= decay_constant + setval(i, i, -decay_constant) # Gain from radioactive decay if nuc.n_decay_modes != 0: @@ -650,19 +657,19 @@ class Chain: if branch_val != 0.0: if target is not None: k = self.nuclide_dict[target] - matrix[k, i] += branch_val + setval(k, i, branch_val) # Produce alphas and protons from decay if 'alpha' in decay_type: k = self.nuclide_dict.get('He4') if k is not None: count = decay_type.count('alpha') - matrix[k, i] += count * branch_val + setval(k, i, count * branch_val) elif 'p' in decay_type: k = self.nuclide_dict.get('H1') if k is not None: count = decay_type.count('p') - matrix[k, i] += count * branch_val + setval(k, i, count * branch_val) if nuc.name in rates.index_nuc: # Extract all reactions for this nuclide in this cell @@ -679,13 +686,13 @@ class Chain: if r_type not in reactions: reactions.add(r_type) if path_rate != 0.0: - matrix[i, i] -= path_rate + setval(i, i, -path_rate) # Gain term; allow for total annihilation for debug purposes if r_type != 'fission': if target is not None and path_rate != 0.0: k = self.nuclide_dict[target] - matrix[k, i] += path_rate * br + setval(k, i, path_rate * br) # Determine light nuclide production, e.g., (n,d) should # produce H2 @@ -693,20 +700,76 @@ class Chain: for light_nuc in light_nucs: k = self.nuclide_dict.get(light_nuc) if k is not None: - matrix[k, i] += path_rate * br + setval(k, i, path_rate * br) else: for product, y in fission_yields[nuc.name].items(): yield_val = y * path_rate if yield_val != 0.0: k = self.nuclide_dict[product] - matrix[k, i] += yield_val + setval(k, i, yield_val) # Clear set of reactions reactions.clear() # Return CSC representation instead of DOK - return matrix.tocsc() + return sp.csc_matrix((vals, (rows, cols)), shape=(n, n)) + + def add_redox_term(self, matrix, buffer, oxidation_states): + r"""Adds a redox term to the depletion matrix from data contained in + the matrix itself and a few user-inputs. + + The redox term to add to the buffer nuclide :math:`N_j` can be written + as: + + .. math:: + \frac{dN_j(t)}{dt} = \cdots - \frac{1}{OS_j}\sum_i N_i a_{ij} + \cdot OS_i + + where :math:`OS` is the oxidation states vector and :math:`a_{ij}` the + corresponding term in the Bateman matrix. + + Parameters + ---------- + matrix : scipy.sparse.csc_matrix + Sparse matrix representing depletion + buffer : dict + Dictionary of buffer nuclides used to maintain anoins net balance. + Keys are nuclide names (strings) and values are their respective + fractions (float) that collectively sum to 1. + oxidation_states : dict + User-defined oxidation states for elements. Keys are element symbols + (e.g., 'H', 'He'), and values are their corresponding oxidation + states as integers (e.g., +1, 0). + Returns + ------- + matrix : scipy.sparse.csc_matrix + Sparse matrix with redox term added + """ + # Elements list with the same size as self.nuclides + elements = [re.split(r'\d+', nuc.name)[0] for nuc in self.nuclides] + + # Match oxidation states with all elements and add 0 if not data + os = np.array([oxidation_states[elm] if elm in oxidation_states else 0 + for elm in elements]) + + # Buffer idx with nuclide index as value + buffer_idx = {nuc: self.nuclide_dict[nuc] for nuc in buffer} + array = matrix.toarray() + redox_change = np.array([]) + + # calculate the redox array + for i in range(len(self)): + # Net redox impact of reaction: multiply the i-th column of the + # depletion matrix by the oxidation states + redox_change = np.append(redox_change, sum(array[:, i]*os)) + + # Subtract redox vector to the buffer nuclides in the matrix scaling by + # their respective oxidation states + for nuc, idx in buffer_idx.items(): + array[idx] -= redox_change * buffer[nuc] / os[idx] + + return sp.csc_matrix(array) def form_rr_term(self, tr_rates, current_timestep, mats): """Function to form the transfer rate term matrices. diff --git a/openmc/deplete/d1s.py b/openmc/deplete/d1s.py index 311bc2d69c..bc99fc42db 100644 --- a/openmc/deplete/d1s.py +++ b/openmc/deplete/d1s.py @@ -5,7 +5,7 @@ shutdown dose rate calculations. """ -from copy import deepcopy +from copy import copy from typing import Sequence from math import log, prod @@ -108,14 +108,15 @@ def time_correction_factors( # Create a 2D array for the time correction factors h = np.zeros((n_timesteps, n_nuclides)) - for i, (dt, rate) in enumerate(zip(timesteps, source_rates)): - # Precompute the exponential terms. Since (1 - exp(-x)) is susceptible to - # roundoff error, use expm1 instead (which computes exp(x) - 1) - g = np.exp(-decay_rate*dt) - one_minus_g = -np.expm1(-decay_rate*dt) + # Precompute all exponential terms with same shape as h + decay_dt = decay_rate[np.newaxis, :] * timesteps[:, np.newaxis] + g = np.exp(-decay_dt) + one_minus_g = -np.expm1(-decay_dt) + # Apply recurrence relation step by step + for i in range(len(timesteps)): # Eq. (4) in doi:10.1016/j.fusengdes.2019.111399 - h[i + 1] = rate*one_minus_g + h[i]*g + h[i + 1] = source_rates[i] * one_minus_g[i] + h[i] * g[i] return {nuclides[i]: h[:, i] for i in range(n_nuclides)} @@ -163,8 +164,12 @@ def apply_time_correction( radionuclides = [str(x) for x in tally.filters[i_filter].bins] tcf = np.array([time_correction_factors[x][index] for x in radionuclides]) - # Create copy of tally - new_tally = deepcopy(tally) + # Force tally results to be read and std_dev to be computed + tally.std_dev + + # Create shallow copy of tally + new_tally = copy(tally) + new_tally._filters = copy(tally._filters) # Determine number of bins in other filters n_bins_before = prod([f.num_bins for f in tally.filters[:i_filter]]) @@ -176,32 +181,33 @@ def apply_time_correction( shape = (n_bins_before, n_radionuclides, n_bins_after, n_nuclides, n_scores) tally_sum = new_tally.sum.reshape(shape) tally_sum_sq = new_tally.sum_sq.reshape(shape) + tally_mean = new_tally.mean.reshape(shape) + tally_std_dev = new_tally.std_dev.reshape(shape) # Apply TCF, broadcasting to the correct dimensions tcf.shape = (1, -1, 1, 1, 1) new_tally._sum = tally_sum * tcf new_tally._sum_sq = tally_sum_sq * (tcf*tcf) - new_tally._mean = None - new_tally._std_dev = None + new_tally._mean = tally_mean * tcf + new_tally._std_dev = tally_std_dev * tcf shape = (-1, n_nuclides, n_scores) if sum_nuclides: - # Query the mean and standard deviation - mean = new_tally.mean - std_dev = new_tally.std_dev - # Sum over parent nuclides (note that when combining different bins for # parent nuclide, we can't work directly on sum_sq) - new_tally._mean = mean.sum(axis=1).reshape(shape) - new_tally._std_dev = np.linalg.norm(std_dev, axis=1).reshape(shape) + new_tally._mean = new_tally.mean.sum(axis=1).reshape(shape) + new_tally._std_dev = np.linalg.norm(new_tally.std_dev, axis=1).reshape(shape) new_tally._derived = True # Remove ParentNuclideFilter new_tally.filters.pop(i_filter) else: + # Change shape back to (filter combinations, nuclides, scores) new_tally._sum.shape = shape new_tally._sum_sq.shape = shape + new_tally._mean.shape = shape + new_tally._std_dev.shape = shape return new_tally diff --git a/openmc/deplete/integrators.py b/openmc/deplete/integrators.py index 000cb2c41c..25e64cb2ef 100644 --- a/openmc/deplete/integrators.py +++ b/openmc/deplete/integrators.py @@ -22,7 +22,6 @@ class PredictorIntegrator(Integrator): .. math:: \mathbf{n}_{i+1} = \exp\left(h\mathbf{A}(\mathbf{n}_i) \right) \mathbf{n}_i - """ _num_stages = 1 @@ -47,15 +46,12 @@ class PredictorIntegrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray + n_end : list of numpy.ndarray Concentrations at end of interval - op_results : empty list - Kept for consistency with API. No intermediate calls to operator - with predictor """ proc_time, n_end = self._timed_deplete(n, rates, dt, _i) - return proc_time, [n_end], [] + return proc_time, n_end @add_params @@ -99,11 +95,8 @@ class CECMIntegrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from transport simulations + n_end : list of numpy.ndarray + Concentrations at end of interval """ # deplete across first half of interval time0, n_middle = self._timed_deplete(n, rates, dt / 2, _i) @@ -113,7 +106,7 @@ class CECMIntegrator(Integrator): # MOS reaction rates time1, n_end = self._timed_deplete(n, res_middle.rates, dt, _i) - return time0 + time1, [n_middle, n_end], [res_middle] + return time0 + time1, n_end @add_params @@ -163,12 +156,8 @@ class CF4Integrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from intermediate transport - simulations + n_end : list of numpy.ndarray + Concentrations at end of interval """ # Step 1: deplete with matrix 1/2*A(y0) time1, n_eos1 = self._timed_deplete( @@ -193,9 +182,7 @@ class CF4Integrator(Integrator): time5, n_eos5 = self._timed_deplete( n_inter, list_rates, dt, _i, matrix_func=cf4_f4) - return (time1 + time2 + time3 + time4 + time5, - [n_eos1, n_eos2, n_eos3, n_eos5], - [res1, res2, res3]) + return time1 + time2 + time3 + time4 + time5, n_eos5 @add_params @@ -241,12 +228,8 @@ class CELIIntegrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from intermediate transport - simulation + n_end : list of numpy.ndarray + Concentrations at end of interval """ # deplete to end using BOS rates proc_time, n_ce = self._timed_deplete(n_bos, rates, dt, _i) @@ -261,7 +244,7 @@ class CELIIntegrator(Integrator): time_le2, n_end = self._timed_deplete( n_inter, list_rates, dt, _i, matrix_func=celi_f2) - return proc_time + time_le1 + time_le1, [n_ce, n_end], [res_ce] + return proc_time + time_le1 + time_le2, n_end @add_params @@ -307,12 +290,8 @@ class EPCRK4Integrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from intermediate transport - simulations + n_end : list of numpy.ndarray + Concentrations at end of interval """ # Step 1: deplete with matrix A(y0) / 2 @@ -331,7 +310,7 @@ class EPCRK4Integrator(Integrator): list_rates = list(zip(rates, res1.rates, res2.rates, res3.rates)) time4, n4 = self._timed_deplete(n, list_rates, dt, _i, matrix_func=rk4_f4) - return (time1 + time2 + time3 + time4, [n1, n2, n3, n4], [res1, res2, res3]) + return time1 + time2 + time3 + time4, n4 @add_params @@ -389,12 +368,8 @@ class LEQIIntegrator(Integrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult - Eigenvalue and reaction rates from intermediate transport - simulation + n_end : list of numpy.ndarray + Concentrations at end of interval """ if i == 0: if self._i_res < 1: # need at least previous transport solution @@ -403,7 +378,7 @@ class LEQIIntegrator(Integrator): self, n_bos, bos_rates, dt, source_rate, i) prev_res = self.operator.prev_res[-2] prev_dt = self.timesteps[i] - prev_res.time[0] - self._prev_rates = prev_res.rates[0] + self._prev_rates = prev_res.rates else: prev_dt = self.timesteps[i - 1] @@ -432,9 +407,7 @@ class LEQIIntegrator(Integrator): # store updated rates self._prev_rates = copy.deepcopy(bos_res.rates) - return ( - time1 + time2 + time3 + time4, [n_eos0, n_eos1], - [bos_res, res_inter]) + return time1 + time2 + time3 + time4, n_eos1 @add_params @@ -471,10 +444,9 @@ class SICELIIntegrator(SIIntegrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_bos_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult + n_end : list of numpy.ndarray + Concentrations at end of interval + op_result : openmc.deplete.OperatorResult Eigenvalue and reaction rates from intermediate transport simulations """ @@ -500,7 +472,7 @@ class SICELIIntegrator(SIIntegrator): proc_time += time1 + time2 # end iteration - return proc_time, [n_eos, n_inter], [res_bar] + return proc_time, n_inter, res_bar @add_params @@ -537,10 +509,9 @@ class SILEQIIntegrator(SIIntegrator): ------- proc_time : float Time spent in CRAM routines for all materials in [s] - n_list : list of list of numpy.ndarray - Concentrations at each of the intermediate points with - the final concentration as the last element - op_results : list of openmc.deplete.OperatorResult + n_end : list of numpy.ndarray + Concentrations at end of interval + op_result : openmc.deplete.OperatorResult Eigenvalue and reaction rates from intermediate transport simulation """ @@ -552,7 +523,7 @@ class SILEQIIntegrator(SIIntegrator): self, n_bos, bos_rates, dt, source_rate, i) prev_res = self.operator.prev_res[-2] prev_dt = self.timesteps[i] - prev_res.time[0] - self._prev_rates = prev_res.rates[0] + self._prev_rates = prev_res.rates else: prev_dt = self.timesteps[i - 1] @@ -585,7 +556,10 @@ class SILEQIIntegrator(SIIntegrator): n_inter, inputs, dt, i, matrix_func=leqi_f4) proc_time += time1 + time2 - return proc_time, [n_eos, n_inter], [res_bar] + # Store updated rates for next step + self._prev_rates = copy.deepcopy(bos_rates) + + return proc_time, n_inter, res_bar integrator_by_name = { diff --git a/openmc/deplete/microxs.py b/openmc/deplete/microxs.py index 4ce199f0cc..879a2d4ee9 100644 --- a/openmc/deplete/microxs.py +++ b/openmc/deplete/microxs.py @@ -8,8 +8,9 @@ from __future__ import annotations from collections.abc import Sequence import shutil from tempfile import TemporaryDirectory -from typing import Union, TypeAlias +from typing import Union, TypeAlias, Self +import h5py import pandas as pd import numpy as np @@ -20,6 +21,7 @@ from openmc.data import REACTION_MT import openmc from .chain import Chain, REACTIONS, _get_chain from .coupled_operator import _find_cross_sections, _get_nuclides_with_data +from ..utility_funcs import h5py_file_or_group import openmc.lib from openmc.mpi import comm @@ -47,6 +49,7 @@ def get_microxs_and_flux( reaction_rate_mode: str = 'direct', chain_file: PathLike | Chain | None = None, path_statepoint: PathLike | None = None, + path_input: PathLike | None = None, run_kwargs=None ) -> tuple[list[np.ndarray], list[MicroXS]]: """Generate microscopic cross sections and fluxes for multiple domains. @@ -59,7 +62,7 @@ def get_microxs_and_flux( .. versionadded:: 0.14.0 .. versionchanged:: 0.15.3 - Added `reaction_rate_mode` and `path_statepoint` arguments. + Added `reaction_rate_mode`, `path_statepoint`, `path_input` arguments. Parameters ---------- @@ -90,6 +93,10 @@ def get_microxs_and_flux( Path to write the statepoint file from the neutron transport solve to. By default, The statepoint file is written to a temporary directory and is not kept. + path_input : path-like, optional + Path to write the model XML file from the neutron transport solve to. + By default, the model XML file is written to a temporary directory and + not kept. run_kwargs : dict, optional Keyword arguments passed to :meth:`openmc.Model.run` @@ -108,7 +115,7 @@ def get_microxs_and_flux( check_value('reaction_rate_mode', reaction_rate_mode, {'direct', 'flux'}) # Save any original tallies on the model - original_tallies = model.tallies + original_tallies = list(model.tallies) # Determine what reactions and nuclides are available in chain chain = _get_chain(chain_file) @@ -163,14 +170,16 @@ def get_microxs_and_flux( # Reinitialize with tallies openmc.lib.init(intracomm=comm) - # create temporary run with TemporaryDirectory() as temp_dir: - if run_kwargs is None: - run_kwargs = {} - else: - run_kwargs = dict(run_kwargs) - run_kwargs.setdefault('cwd', temp_dir) + # Indicate to run in temporary directory unless being executed through + # openmc.lib, in which case we don't need to specify the cwd + run_kwargs = dict(run_kwargs) if run_kwargs else {} + if not openmc.lib.is_initialized: + run_kwargs.setdefault('cwd', temp_dir) + + # Run transport simulation and synchronize statepoint_path = model.run(**run_kwargs) + comm.barrier() if comm.rank == 0: # Move the statepoint file if it is being saved to a specific path @@ -178,15 +187,22 @@ def get_microxs_and_flux( shutil.move(statepoint_path, path_statepoint) statepoint_path = path_statepoint - with StatePoint(statepoint_path) as sp: - if reaction_rate_mode == 'direct': - rr_tally = sp.tallies[rr_tally.id] - rr_tally._read_results() - flux_tally = sp.tallies[flux_tally.id] - flux_tally._read_results() + # Export the model to path_input if provided + if path_input is not None: + model.export_to_model_xml(path_input) + + # Broadcast updated statepoint path to all ranks + statepoint_path = comm.bcast(statepoint_path) + + # Read in tally results (on all ranks) + with StatePoint(statepoint_path) as sp: + if reaction_rate_mode == 'direct': + rr_tally = sp.tallies[rr_tally.id] + rr_tally._read_results() + flux_tally = sp.tallies[flux_tally.id] + flux_tally._read_results() # Get flux values and make energy groups last dimension - flux_tally = comm.bcast(flux_tally) flux = flux_tally.get_reshaped_data() # (domains, groups, 1, 1) flux = np.moveaxis(flux, 1, -1) # (domains, 1, 1, groups) @@ -195,7 +211,6 @@ def get_microxs_and_flux( if reaction_rate_mode == 'direct': # Get reaction rates - rr_tally = comm.bcast(rr_tally) reaction_rates = rr_tally.get_reshaped_data() # (domains, groups, nuclides, reactions) # Make energy groups last dimension @@ -345,13 +360,17 @@ class MicroXS: reactions = chain.reactions mts = [REACTION_MT[name] for name in reactions] - # Normalize multigroup flux - multigroup_flux = np.array(multigroup_flux) - multigroup_flux /= multigroup_flux.sum() - # Create 3D array for microscopic cross sections microxs_arr = np.zeros((len(nuclides), len(mts), 1)) + # If flux is zero, safely return zero cross sections + multigroup_flux = np.array(multigroup_flux) + if (flux_sum := multigroup_flux.sum()) == 0.0: + return cls(microxs_arr, nuclides, reactions) + + # Normalize multigroup flux + multigroup_flux /= flux_sum + # Compute microscopic cross sections within a temporary session with openmc.lib.TemporarySession(**init_kwargs): # For each nuclide and reaction, compute the flux-averaged xs @@ -383,8 +402,7 @@ class MicroXS: MicroXS """ - if 'float_precision' not in kwargs: - kwargs['float_precision'] = 'round_trip' + kwargs.setdefault('float_precision', 'round_trip') df = pd.read_csv(csv_file, **kwargs) df.set_index(['nuclides', 'reactions', 'groups'], inplace=True) @@ -419,3 +437,96 @@ class MicroXS: ) df = pd.DataFrame({'xs': self.data.flatten()}, index=multi_index) df.to_csv(*args, **kwargs) + + def to_hdf5(self, group_or_filename: h5py.Group | PathLike, **kwargs): + """Export microscopic cross section data to HDF5 format + + Parameters + ---------- + group_or_filename : h5py.Group or path-like + HDF5 group or filename to write to + kwargs : dict, optional + Keyword arguments to pass to :meth:`h5py.Group.create_dataset`. + Defaults to {'compression': 'lzf'}. + + """ + kwargs.setdefault('compression', 'lzf') + + with h5py_file_or_group(group_or_filename, 'w') as group: + # Store cross section data as 3D dataset + group.create_dataset('data', data=self.data, **kwargs) + + # Store metadata as datasets using string encoding + group.create_dataset('nuclides', data=np.array(self.nuclides, dtype='S')) + group.create_dataset('reactions', data=np.array(self.reactions, dtype='S')) + + @classmethod + def from_hdf5(cls, group_or_filename: h5py.Group | PathLike) -> Self: + """Load data from an HDF5 file + + Parameters + ---------- + group_or_filename : h5py.Group or str or PathLike + HDF5 group or path to HDF5 file. If given as an h5py.Group, the + data is read from that group. If given as a string, it is assumed + to be the filename for the HDF5 file. + + Returns + ------- + MicroXS + """ + + with h5py_file_or_group(group_or_filename, 'r') as group: + # Read data from HDF5 group + data = group['data'][:] + nuclides = [nuc.decode('utf-8') for nuc in group['nuclides'][:]] + reactions = [rxn.decode('utf-8') for rxn in group['reactions'][:]] + + return cls(data, nuclides, reactions) + + +def write_microxs_hdf5( + micros: Sequence[MicroXS], + filename: PathLike, + names: Sequence[str] | None = None, + **kwargs +): + """Write multiple MicroXS objects to an HDF5 file + + Parameters + ---------- + micros : list of MicroXS + List of MicroXS objects + filename : PathLike + Output HDF5 filename + names : list of str, optional + Names for each MicroXS object. If None, uses 'domain_0', 'domain_1', + etc. + **kwargs + Additional keyword arguments passed to :meth:`h5py.Group.create_dataset` + """ + if names is None: + names = [f'domain_{i}' for i in range(len(micros))] + + # Open file once and write all domains using group interface + with h5py.File(filename, 'w') as f: + for microxs, name in zip(micros, names): + group = f.create_group(name) + microxs.to_hdf5(group, **kwargs) + + +def read_microxs_hdf5(filename: PathLike) -> dict[str, MicroXS]: + """Read multiple MicroXS objects from an HDF5 file + + Parameters + ---------- + filename : path-like + HDF5 filename + + Returns + ------- + dict + Dictionary mapping domain names to MicroXS objects + """ + with h5py.File(filename, 'r') as f: + return {name: MicroXS.from_hdf5(group) for name, group in f.items()} diff --git a/openmc/deplete/pool.py b/openmc/deplete/pool.py index 03b050af38..aa348c02aa 100644 --- a/openmc/deplete/pool.py +++ b/openmc/deplete/pool.py @@ -109,6 +109,13 @@ def deplete(func, chain, n, rates, dt, current_timestep=None, matrix_func=None, matrices = [matrix - transfer for (matrix, transfer) in zip(matrices, transfers)] + if transfer_rates.redox: + for mat_idx, mat_id in enumerate(transfer_rates.local_mats): + if mat_id in transfer_rates.redox: + matrices[mat_idx] = chain.add_redox_term(matrices[mat_idx], + transfer_rates.redox[mat_id][0], + transfer_rates.redox[mat_id][1]) + if current_timestep in transfer_rates.index_transfer: # Gather all on comm.rank 0 matrices = comm.gather(matrices) @@ -125,6 +132,12 @@ def deplete(func, chain, n, rates, dt, current_timestep=None, matrix_func=None, transfer_matrix = chain.form_rr_term(transfer_rates, current_timestep, mat_pair) + + # check if destination material has a redox control + if mat_pair[0] in transfer_rates.redox: + transfer_matrix = chain.add_redox_term(transfer_matrix, + transfer_rates.redox[mat_pair[0]][0], + transfer_rates.redox[mat_pair[0]][1]) transfer_pair[mat_pair] = transfer_matrix # Combine all matrices together in a single matrix of matrices diff --git a/openmc/deplete/r2s.py b/openmc/deplete/r2s.py new file mode 100644 index 0000000000..97277cbda8 --- /dev/null +++ b/openmc/deplete/r2s.py @@ -0,0 +1,693 @@ +from __future__ import annotations +from collections.abc import Sequence +import copy +from datetime import datetime +import json +from pathlib import Path + +import numpy as np +import openmc +from . import IndependentOperator, PredictorIntegrator +from .microxs import get_microxs_and_flux, write_microxs_hdf5, read_microxs_hdf5 +from .results import Results +from ..checkvalue import PathLike +from ..mpi import comm +from openmc.lib import TemporarySession +from openmc.utility_funcs import change_directory + + +def get_activation_materials( + model: openmc.Model, mmv: openmc.MeshMaterialVolumes +) -> openmc.Materials: + """Get a list of activation materials for each mesh element/material. + + When performing a mesh-based R2S calculation, a unique material is needed + for each activation region, which is a combination of a mesh element and a + material within that mesh element. This function generates a list of such + materials, each with a unique name and volume corresponding to the mesh + element and material. + + Parameters + ---------- + model : openmc.Model + The full model containing the geometry and materials. + mmv : openmc.MeshMaterialVolumes + The mesh material volumes object containing the materials and their + volumes for each mesh element. + + Returns + ------- + openmc.Materials + A list of materials, each corresponding to a unique mesh element and + material combination. + + """ + # Get the material ID, volume, and element index for each element-material + # combination + mat_ids = mmv._materials[mmv._materials > -1] + volumes = mmv._volumes[mmv._materials > -1] + elems, _ = np.where(mmv._materials > -1) + + # Get all materials in the model + material_dict = model._get_all_materials() + + # Create a new activation material for each element-material combination + materials = openmc.Materials() + for elem, mat_id, vol in zip(elems, mat_ids, volumes): + mat = material_dict[mat_id] + new_mat = mat.clone() + new_mat.depletable = True + new_mat.name = f'Element {elem}, Material {mat_id}' + new_mat.volume = vol + materials.append(new_mat) + + return materials + + +class R2SManager: + """Manager for Rigorous 2-Step (R2S) method calculations. + + This class is responsible for managing the materials and sources needed for + mesh-based or cell-based R2S calculations. It provides methods to get + activation materials and decay photon sources based on the mesh/cells and + materials in the OpenMC model. + + This class supports the use of a different models for the neutron and photon + transport calculation. However, for cell-based calculations, it assumes that + the only changes in the model are material assignments. For mesh-based + calculations, it checks material assignments in the photon model and any + element--material combinations that don't appear in the photon model are + skipped. + + Parameters + ---------- + neutron_model : openmc.Model + The OpenMC model to use for neutron transport. + domains : openmc.MeshBase or Sequence[openmc.Cell] + The mesh or a sequence of cells that represent the spatial units over + which the R2S calculation will be performed. + photon_model : openmc.Model, optional + The OpenMC model to use for photon transport calculations. If None, a + shallow copy of the neutron_model will be created and used. + + Attributes + ---------- + domains : openmc.MeshBase or Sequence[openmc.Cell] + The mesh or a sequence of cells that represent the spatial units over + which the R2S calculation will be performed. + neutron_model : openmc.Model + The OpenMC model used for neutron transport. + photon_model : openmc.Model + The OpenMC model used for photon transport calculations. + method : {'mesh-based', 'cell-based'} + Indicates whether the R2S calculation uses mesh elements ('mesh-based') + as the spatial discetization or a list of a cells ('cell-based'). + results : dict + A dictionary that stores results from the R2S calculation. + + """ + def __init__( + self, + neutron_model: openmc.Model, + domains: openmc.MeshBase | Sequence[openmc.Cell], + photon_model: openmc.Model | None = None, + ): + self.neutron_model = neutron_model + if photon_model is None: + # Create a shallow copy of the neutron model for photon transport + self.photon_model = openmc.Model( + geometry=copy.copy(neutron_model.geometry), + materials=copy.copy(neutron_model.materials), + settings=copy.copy(neutron_model.settings), + tallies=copy.copy(neutron_model.tallies), + plots=copy.copy(neutron_model.plots), + ) + else: + self.photon_model = photon_model + if isinstance(domains, openmc.MeshBase): + self.method = 'mesh-based' + else: + self.method = 'cell-based' + self.domains = domains + self.results = {} + + def run( + self, + timesteps: Sequence[float] | Sequence[tuple[float, str]], + source_rates: float | Sequence[float], + timestep_units: str = 's', + photon_time_indices: Sequence[int] | None = None, + output_dir: PathLike | None = None, + bounding_boxes: dict[int, openmc.BoundingBox] | None = None, + chain_file: PathLike | None = None, + micro_kwargs: dict | None = None, + mat_vol_kwargs: dict | None = None, + run_kwargs: dict | None = None, + operator_kwargs: dict | None = None, + ): + """Run the R2S calculation. + + Parameters + ---------- + timesteps : Sequence[float] or Sequence[tuple[float, str]] + Sequence of timesteps. Note that values are not cumulative. The + units are specified by the `timestep_units` argument when + `timesteps` is an iterable of float. Alternatively, units can be + specified for each step by passing an iterable of (value, unit) + tuples. + source_rates : float or Sequence[float] + Source rate in [neutron/sec] for each interval in `timesteps`. + timestep_units : {'s', 'min', 'h', 'd', 'a'}, optional + Units for values specified in the `timesteps` argument when passing + float values. 's' means seconds, 'min' means minutes, 'h' means + hours, 'd' means days, and 'a' means years (Julian). + photon_time_indices : Sequence[int], optional + Sequence of time indices at which photon transport should be run; + represented as indices into the array of times formed by the + timesteps. For example, if two timesteps are specified, the array of + times would contain three entries, and [2] would indicate computing + photon results at the last time. A value of None indicates to run + photon transport for each time. + output_dir : PathLike, optional + Path to directory where R2S calculation outputs will be saved. If + not provided, a timestamped directory 'r2s_YYYY-MM-DDTHH-MM-SS' is + created. Subdirectories will be created for the neutron transport, + activation, and photon transport steps. + bounding_boxes : dict[int, openmc.BoundingBox], optional + Dictionary mapping cell IDs to bounding boxes used for spatial + source sampling in cell-based R2S calculations. Required if method + is 'cell-based'. + chain_file : PathLike, optional + Path to the depletion chain XML file to use during activation. If + not provided, the default configured chain file will be used. + micro_kwargs : dict, optional + Additional keyword arguments passed to + :func:`openmc.deplete.get_microxs_and_flux` during the neutron + transport step. + mat_vol_kwargs : dict, optional + Additional keyword arguments passed to + :meth:`openmc.MeshBase.material_volumes`. + run_kwargs : dict, optional + Additional keyword arguments passed to :meth:`openmc.Model.run` + during the neutron and photon transport step. By default, output is + disabled. + operator_kwargs : dict, optional + Additional keyword arguments passed to + :class:`openmc.deplete.IndependentOperator`. + + Returns + ------- + Path + Path to the output directory containing all calculation results + """ + + if output_dir is None: + # Create timestamped output directory and broadcast to all ranks for + # consistency (different ranks may have slightly different times) + stamp = datetime.now().strftime('%Y-%m-%dT%H-%M-%S') + output_dir = Path(comm.bcast(f'r2s_{stamp}')) + + # Set run_kwargs for the neutron transport step + if micro_kwargs is None: + micro_kwargs = {} + if run_kwargs is None: + run_kwargs = {} + if operator_kwargs is None: + operator_kwargs = {} + run_kwargs.setdefault('output', False) + micro_kwargs.setdefault('run_kwargs', run_kwargs) + # If a chain file is provided, prefer it for steps 1 and 2 + if chain_file is not None: + micro_kwargs.setdefault('chain_file', chain_file) + operator_kwargs.setdefault('chain_file', chain_file) + + self.step1_neutron_transport( + output_dir / 'neutron_transport', mat_vol_kwargs, micro_kwargs + ) + self.step2_activation( + timesteps, source_rates, timestep_units, output_dir / 'activation', + operator_kwargs=operator_kwargs + ) + self.step3_photon_transport( + photon_time_indices, bounding_boxes, output_dir / 'photon_transport', + mat_vol_kwargs=mat_vol_kwargs, run_kwargs=run_kwargs + ) + + return output_dir + + def step1_neutron_transport( + self, + output_dir: PathLike = "neutron_transport", + mat_vol_kwargs: dict | None = None, + micro_kwargs: dict | None = None + ): + """Run the neutron transport step. + + This step computes the material volume fractions on the mesh, creates a + mesh-material filter, and retrieves the fluxes and microscopic cross + sections for each mesh/material combination. This step will populate the + 'fluxes' and 'micros' keys in the results dictionary. For a mesh-based + calculation, it will also populate the 'mesh_material_volumes' key. + + Parameters + ---------- + output_dir : PathLike, optional + The directory where the results will be saved. + mat_vol_kwargs : dict, optional + Additional keyword arguments based to + :meth:`openmc.MeshBase.material_volumes`. + micro_kwargs : dict, optional + Additional keyword arguments passed to + :func:`openmc.deplete.get_microxs_and_flux`. + + """ + + output_dir = Path(output_dir).resolve() + output_dir.mkdir(parents=True, exist_ok=True) + + if self.method == 'mesh-based': + # Compute material volume fractions on the mesh + if mat_vol_kwargs is None: + mat_vol_kwargs = {} + self.results['mesh_material_volumes'] = mmv = comm.bcast( + self.domains.material_volumes(self.neutron_model, **mat_vol_kwargs)) + + # Save results to file + if comm.rank == 0: + mmv.save(output_dir / 'mesh_material_volumes.npz') + + # Create mesh-material filter based on what combos were found + domains = openmc.MeshMaterialFilter.from_volumes(self.domains, mmv) + else: + domains: Sequence[openmc.Cell] = self.domains + + # Check to make sure that each cell is filled with a material and + # that the volume has been set + + # TODO: If volumes are not set, run volume calculation for cells + for cell in domains: + if cell.fill is None: + raise ValueError( + f"Cell {cell.id} is not filled with a materials. " + "Please set the fill material for each cell before " + "running the R2S calculation." + ) + if cell.volume is None: + raise ValueError( + f"Cell {cell.id} does not have a volume set. " + "Please set the volume for each cell before running " + "the R2S calculation." + ) + + # Set default keyword arguments for microxs and flux calculation + if micro_kwargs is None: + micro_kwargs = {} + micro_kwargs.setdefault('path_statepoint', output_dir / 'statepoint.h5') + micro_kwargs.setdefault('path_input', output_dir / 'model.xml') + + # Run neutron transport and get fluxes and micros. Run via openmc.lib to + # maintain a consistent parallelism strategy with the activation step. + with TemporarySession(): + self.results['fluxes'], self.results['micros'] = get_microxs_and_flux( + self.neutron_model, domains, **micro_kwargs) + + # Save flux and micros to file + if comm.rank == 0: + np.save(output_dir / 'fluxes.npy', self.results['fluxes']) + write_microxs_hdf5(self.results['micros'], output_dir / 'micros.h5') + + def step2_activation( + self, + timesteps: Sequence[float] | Sequence[tuple[float, str]], + source_rates: float | Sequence[float], + timestep_units: str = 's', + output_dir: PathLike = 'activation', + operator_kwargs: dict | None = None, + ): + """Run the activation step. + + This step creates a unique copy of each activation material based on the + mesh elements or cells, then solves the depletion equations for each + material using the fluxes and microscopic cross sections obtained in the + neutron transport step. This step will populate the 'depletion_results' + and 'activation_materials' keys in the results dictionary. + + Parameters + ---------- + timesteps : Sequence[float] or Sequence[tuple[float, str]] + Sequence of timesteps. Note that values are not cumulative. The + units are specified by the `timestep_units` argument when + `timesteps` is an iterable of float. Alternatively, units can be + specified for each step by passing an iterable of (value, unit) + tuples. + source_rates : float | Sequence[float] + Source rate in [neutron/sec] for each interval in `timesteps`. + timestep_units : {'s', 'min', 'h', 'd', 'a'}, optional + Units for values specified in the `timesteps` argument when passing + float values. 's' means seconds, 'min' means minutes, 'h' means + hours, 'd' means days, and 'a' means years (Julian). + output_dir : PathLike, optional + Path to directory where activation calculation outputs will be + saved. + operator_kwargs : dict, optional + Additional keyword arguments passed to + :class:`openmc.deplete.IndependentOperator`. + """ + + if self.method == 'mesh-based': + # Get unique material for each (mesh, material) combination + mmv = self.results['mesh_material_volumes'] + self.results['activation_materials'] = get_activation_materials(self.neutron_model, mmv) + else: + # Create unique material for each cell + activation_mats = openmc.Materials() + for cell in self.domains: + mat = cell.fill.clone() + mat.name = f'Cell {cell.id}' + mat.depletable = True + mat.volume = cell.volume + activation_mats.append(mat) + self.results['activation_materials'] = activation_mats + + # Save activation materials to file + output_dir = Path(output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + self.results['activation_materials'].export_to_xml( + output_dir / 'materials.xml') + + # Create depletion operator for the activation materials + if operator_kwargs is None: + operator_kwargs = {} + operator_kwargs.setdefault('normalization_mode', 'source-rate') + op = IndependentOperator( + self.results['activation_materials'], + self.results['fluxes'], + self.results['micros'], + **operator_kwargs + ) + + # Create time integrator and solve depletion equations + integrator = PredictorIntegrator( + op, timesteps, source_rates=source_rates, timestep_units=timestep_units + ) + output_path = output_dir / 'depletion_results.h5' + integrator.integrate(final_step=False, path=output_path) + comm.barrier() + + # Get depletion results + self.results['depletion_results'] = Results(output_path) + + def step3_photon_transport( + self, + time_indices: Sequence[int] | None = None, + bounding_boxes: dict[int, openmc.BoundingBox] | None = None, + output_dir: PathLike = 'photon_transport', + mat_vol_kwargs: dict | None = None, + run_kwargs: dict | None = None, + ): + """Run the photon transport step. + + This step performs photon transport calculations using decay photon + sources created from the activated materials. For each specified time, + it creates appropriate photon sources and runs a transport calculation. + In mesh-based mode, the sources are created using the mesh material + volumes, while in cell-based mode, they are created using bounding boxes + for each cell. This step will populate the 'photon_tallies' key in the + results dictionary. + + Parameters + ---------- + time_indices : Sequence[int], optional + Sequence of time indices at which photon transport should be run; + represented as indices into the array of times formed by the + timesteps. For example, if two timesteps are specified, the array of + times would contain three entries, and [2] would indicate computing + photon results at the last time. A value of None indicates to run + photon transport for each time. + bounding_boxes : dict[int, openmc.BoundingBox], optional + Dictionary mapping cell IDs to bounding boxes used for spatial + source sampling in cell-based R2S calculations. Required if method + is 'cell-based'. + output_dir : PathLike, optional + Path to directory where photon transport outputs will be saved. + mat_vol_kwargs : dict, optional + Additional keyword arguments passed to + :meth:`openmc.MeshBase.material_volumes`. + run_kwargs : dict, optional + Additional keyword arguments passed to :meth:`openmc.Model.run` + during the photon transport step. By default, output is disabled. + """ + + # TODO: Automatically determine bounding box for each cell + if bounding_boxes is None and self.method == 'cell-based': + raise ValueError("bounding_boxes must be provided for cell-based " + "R2S calculations.") + + # Set default run arguments if not provided + if run_kwargs is None: + run_kwargs = {} + run_kwargs.setdefault('output', False) + + # Write out JSON file with tally IDs that can be used for loading + # results + output_dir = Path(output_dir) + output_dir.mkdir(parents=True, exist_ok=True) + + # Get default time indices if not provided + if time_indices is None: + n_steps = len(self.results['depletion_results']) + time_indices = list(range(n_steps)) + + # Check whether the photon model is different + neutron_univ = self.neutron_model.geometry.root_universe + photon_univ = self.photon_model.geometry.root_universe + different_photon_model = (neutron_univ != photon_univ) + + # For mesh-based calculations, compute material volume fractions for the + # photon model if it is different from the neutron model to account for + # potential material changes + if self.method == 'mesh-based' and different_photon_model: + self.results['mesh_material_volumes_photon'] = photon_mmv = comm.bcast( + self.domains.material_volumes(self.photon_model, **mat_vol_kwargs)) + + # Save photon MMV results to file + if comm.rank == 0: + photon_mmv.save(output_dir / 'mesh_material_volumes.npz') + + if comm.rank == 0: + tally_ids = [tally.id for tally in self.photon_model.tallies] + with open(output_dir / 'tally_ids.json', 'w') as f: + json.dump(tally_ids, f) + + self.results['photon_tallies'] = {} + + # Get dictionary of cells in the photon model + if different_photon_model: + photon_cells = self.photon_model.geometry.get_all_cells() + + for time_index in time_indices: + # Create decay photon source + if self.method == 'mesh-based': + self.photon_model.settings.source = \ + self.get_decay_photon_source_mesh(time_index) + else: + sources = [] + results = self.results['depletion_results'] + for cell, original_mat in zip(self.domains, self.results['activation_materials']): + # Skip if the cell is not in the photon model or the + # material has changed + if different_photon_model: + if cell.id not in photon_cells or \ + cell.fill.id != photon_cells[cell.id].fill.id: + continue + + # Get bounding box for the cell + bounding_box = bounding_boxes[cell.id] + + # Get activated material composition + activated_mat = results[time_index].get_material(str(original_mat.id)) + + # Create decay photon source source + space = openmc.stats.Box(*bounding_box) + energy = activated_mat.get_decay_photon_energy() + strength = energy.integral() if energy is not None else 0.0 + source = openmc.IndependentSource( + space=space, + energy=energy, + particle='photon', + strength=strength, + constraints={'domains': [cell]} + ) + sources.append(source) + self.photon_model.settings.source = sources + + # Convert time_index (which may be negative) to a normal index + if time_index < 0: + time_index = len(self.results['depletion_results']) + time_index + + # Run photon transport calculation + photon_dir = Path(output_dir) / f'time_{time_index}' + with TemporarySession(self.photon_model, cwd=photon_dir): + statepoint_path = self.photon_model.run(**run_kwargs) + + # Store tally results + with openmc.StatePoint(statepoint_path) as sp: + self.results['photon_tallies'][time_index] = [ + sp.tallies[tally.id] for tally in self.photon_model.tallies + ] + + def get_decay_photon_source_mesh( + self, + time_index: int = -1 + ) -> list[openmc.MeshSource]: + """Create decay photon source for a mesh-based calculation. + + This function creates N :class:`MeshSource` objects where N is the + maximum number of unique materials that appears in a single mesh + element. For each mesh element-material combination, and + IndependentSource instance is created with a spatial constraint limited + the sampled decay photons to the correct region. + + When the photon transport model is different from the neutron model, the + photon MeshMaterialVolumes is used to determine whether an (element, + material) combination exists in the photon model. + + Parameters + ---------- + time_index : int, optional + Time index for the decay photon source. Default is -1 (last time). + + Returns + ------- + list of openmc.MeshSource + A list of MeshSource objects, each containing IndependentSource + instances for the decay photons in the corresponding mesh element. + + """ + mat_dict = self.neutron_model._get_all_materials() + + # Some MeshSource objects will have empty positions; create a "null source" + # that is used for this case + null_source = openmc.IndependentSource(particle='photon', strength=0.0) + + # List to hold sources for each MeshSource (length = N) + source_lists = [] + + # Index in the overall list of activated materials + index_mat = 0 + + # Get various results from previous steps + mat_vols = self.results['mesh_material_volumes'] + materials = self.results['activation_materials'] + results = self.results['depletion_results'] + photon_mat_vols = self.results.get('mesh_material_volumes_photon') + + # Total number of mesh elements + n_elements = mat_vols.num_elements + + for index_elem in range(n_elements): + # Determine which materials exist in the photon model for this element + if photon_mat_vols is not None: + photon_materials = { + mat_id + for mat_id, _ in photon_mat_vols.by_element(index_elem) + if mat_id is not None + } + + for j, (mat_id, _) in enumerate(mat_vols.by_element(index_elem)): + # Skip void volume + if mat_id is None: + continue + + # Skip if this material doesn't exist in photon model + if photon_mat_vols is not None and mat_id not in photon_materials: + index_mat += 1 + continue + + # Check whether a new MeshSource object is needed + if j >= len(source_lists): + source_lists.append([null_source]*n_elements) + + # Get activated material composition + original_mat = materials[index_mat] + activated_mat = results[time_index].get_material(str(original_mat.id)) + + # Create decay photon source source + energy = activated_mat.get_decay_photon_energy() + if energy is not None: + strength = energy.integral() + source_lists[j][index_elem] = openmc.IndependentSource( + energy=energy, + particle='photon', + strength=strength, + constraints={'domains': [mat_dict[mat_id]]} + ) + + # Increment index of activated material + index_mat += 1 + + # Return list of mesh sources + return [openmc.MeshSource(self.domains, sources) for sources in source_lists] + + def load_results(self, path: PathLike): + """Load results from a previous R2S calculation. + + Parameters + ---------- + path : PathLike + Path to the directory containing the R2S calculation results. + + """ + path = Path(path) + + # Load neutron transport results + neutron_dir = path / 'neutron_transport' + if self.method == 'mesh-based': + mmv_file = neutron_dir / 'mesh_material_volumes.npz' + if mmv_file.exists(): + self.results['mesh_material_volumes'] = \ + openmc.MeshMaterialVolumes.from_npz(mmv_file) + fluxes_file = neutron_dir / 'fluxes.npy' + if fluxes_file.exists(): + self.results['fluxes'] = list(np.load(fluxes_file, allow_pickle=True)) + micros_dict = read_microxs_hdf5(neutron_dir / 'micros.h5') + self.results['micros'] = [ + micros_dict[f'domain_{i}'] for i in range(len(micros_dict)) + ] + + # Load activation results + activation_dir = path / 'activation' + activation_results = activation_dir / 'depletion_results.h5' + if activation_results.exists(): + self.results['depletion_results'] = Results(activation_results) + activation_mats_file = activation_dir / 'materials.xml' + if activation_mats_file.exists(): + self.results['activation_materials'] = \ + openmc.Materials.from_xml(activation_mats_file) + + # Load photon transport results + photon_dir = path / 'photon_transport' + + # Load photon mesh material volumes if they exist (for mesh-based calculations) + if self.method == 'mesh-based': + photon_mmv_file = photon_dir / 'mesh_material_volumes.npz' + if photon_mmv_file.exists(): + self.results['mesh_material_volumes_photon'] = \ + openmc.MeshMaterialVolumes.from_npz(photon_mmv_file) + + # Load tally IDs from JSON file + tally_ids_path = photon_dir / 'tally_ids.json' + if tally_ids_path.exists(): + with tally_ids_path.open('r') as f: + tally_ids = json.load(f) + self.results['photon_tallies'] = {} + + # For each photon transport calc, load the statepoint and get the + # tally results based on tally_ids + for time_dir in photon_dir.glob('time_*'): + time_index = int(time_dir.name.split('_')[1]) + for sp_path in time_dir.glob('statepoint.*.h5'): + with openmc.StatePoint(sp_path) as sp: + self.results['photon_tallies'][time_index] = [ + sp.tallies[tally_id] for tally_id in tally_ids + ] diff --git a/openmc/deplete/results.py b/openmc/deplete/results.py index 7427abd735..e1fcb26b6d 100644 --- a/openmc/deplete/results.py +++ b/openmc/deplete/results.py @@ -203,7 +203,7 @@ class Results(list): # Evaluate value in each region for i, result in enumerate(self): times[i] = result.time[0] - concentrations[i] = result[0, mat_id, nuc] + concentrations[i] = result[mat_id, nuc] # Unit conversions times = _get_time_as(times, time_units) @@ -363,7 +363,7 @@ class Results(list): # Evaluate value in each region for i, result in enumerate(self): times[i] = result.time[0] - rates[i] = result.rates[0].get(mat_id, nuc, rx) * result[0, mat, nuc] + rates[i] = result.rates.get(mat_id, nuc, rx) * result[mat, nuc] return times, rates @@ -397,7 +397,7 @@ class Results(list): # Get time/eigenvalue at each point for i, result in enumerate(self): times[i] = result.time[0] - eigenvalues[i] = result.k[0] + eigenvalues[i] = result.k # Convert time units if necessary times = _get_time_as(times, time_units) @@ -630,7 +630,7 @@ class Results(list): for nuc in result.index_nuc: if nuc not in available_cross_sections: continue - atoms = result[0, mat_id, nuc] + atoms = result[mat_id, nuc] if atoms > 0.0: atoms_per_barn_cm = 1e-24 * atoms / mat.volume mat.remove_nuclide(nuc) # Replace if it's there diff --git a/openmc/deplete/stepresult.py b/openmc/deplete/stepresult.py index 1a26cbe346..ff39e9acb6 100644 --- a/openmc/deplete/stepresult.py +++ b/openmc/deplete/stepresult.py @@ -16,7 +16,7 @@ from openmc.mpi import comm, MPI from openmc.checkvalue import PathLike from .reaction_rates import ReactionRates -VERSION_RESULTS = (1, 1) +VERSION_RESULTS = (1, 2) __all__ = ["StepResult"] @@ -30,8 +30,8 @@ class StepResult: Attributes ---------- - k : list of (float, float) - Eigenvalue and uncertainty for each substep. + k : tuple of (float, float) + Eigenvalue and uncertainty at end of step. time : list of float Time at beginning, end of step, in seconds. source_rate : float @@ -40,8 +40,8 @@ class StepResult: Number of mats. n_nuc : int Number of nuclides. - rates : list of ReactionRates - The reaction rates for each substep. + rates : ReactionRates + The reaction rates at end of step. volume : dict of str to float Dictionary mapping mat id to volume. index_mat : dict of str to int @@ -52,10 +52,8 @@ class StepResult: A dictionary mapping mat ID as string to global index. n_hdf5_mats : int Number of materials in entire geometry. - n_stages : int - Number of stages in simulation. data : numpy.ndarray - Atom quantity, stored by stage, mat, then by nuclide. + Atom quantity, stored by mat, then by nuclide. proc_time : int Average time spent depleting a material across all materials and processes @@ -86,17 +84,17 @@ class StepResult: Parameters ---------- pos : tuple - A three-length tuple containing a stage index, mat index and a nuc - index. All can be integers or slices. The second two can be + A two-length tuple containing a mat index and a nuc + index. Both can be integers or slices, or can be strings corresponding to their respective dictionary. Returns ------- float - The atoms for stage, mat, nuc + The atoms for mat, nuc """ - stage, mat, nuc = pos + mat, nuc = pos if isinstance(mat, openmc.Material): mat = str(mat.id) if isinstance(mat, str): @@ -104,7 +102,7 @@ class StepResult: if isinstance(nuc, str): nuc = self.index_nuc[nuc] - return self.data[stage, mat, nuc] + return self.data[mat, nuc] def __setitem__(self, pos, val): """Sets an item from results. @@ -112,21 +110,21 @@ class StepResult: Parameters ---------- pos : tuple - A three-length tuple containing a stage index, mat index and a nuc - index. All can be integers or slices. The second two can be + A two-length tuple containing a mat index and a nuc + index. Both can be integers or slices, or can be strings corresponding to their respective dictionary. val : float The value to set data to. """ - stage, mat, nuc = pos + mat, nuc = pos if isinstance(mat, str): mat = self.index_mat[mat] if isinstance(nuc, str): nuc = self.index_nuc[nuc] - self.data[stage, mat, nuc] = val + self.data[mat, nuc] = val @property def n_mat(self): @@ -140,11 +138,7 @@ class StepResult: def n_hdf5_mats(self): return len(self.mat_to_hdf5_ind) - @property - def n_stages(self): - return self.data.shape[0] - - def allocate(self, volume, nuc_list, burn_list, full_burn_list, stages): + def allocate(self, volume, nuc_list, burn_list, full_burn_list): """Allocate memory for depletion step data Parameters @@ -157,8 +151,6 @@ class StepResult: A list of all mat IDs to be burned. Used for sorting the simulation. full_burn_list : list of str List of all burnable material IDs - stages : int - Number of stages in simulation. """ self.volume = copy.deepcopy(volume) @@ -167,7 +159,7 @@ class StepResult: self.mat_to_hdf5_ind = {mat: i for i, mat in enumerate(full_burn_list)} # Create storage array - self.data = np.zeros((stages, self.n_mat, self.n_nuc)) + self.data = np.zeros((self.n_mat, self.n_nuc)) def distribute(self, local_materials, ranges): """Create a new object containing data for distributed materials @@ -196,8 +188,8 @@ class StepResult: for attr in direct_attrs: setattr(new, attr, getattr(self, attr)) # Get applicable slice of data - new.data = self.data[:, ranges] - new.rates = [r[ranges] for r in self.rates] + new.data = self.data[ranges] + new.rates = self.rates[ranges] return new def get_material(self, mat_id): @@ -232,7 +224,7 @@ class StepResult: f'values are {list(self.volume.keys())}' ) from e for nuc, _ in sorted(self.index_nuc.items(), key=lambda x: x[1]): - atoms = self[0, mat_id, nuc] + atoms = self[mat_id, nuc] if atoms <= 0.0: continue atom_per_bcm = atoms / vol * 1e-24 @@ -240,7 +232,7 @@ class StepResult: material.volume = vol return material - def export_to_hdf5(self, filename, step): + def export_to_hdf5(self, filename, step, write_rates: bool = False): """Export results to an HDF5 file Parameters @@ -249,6 +241,8 @@ class StepResult: The filename to write to step : int What step is this? + write_rates : bool, optional + Whether to include reaction rate datasets in the results file. """ # Write new file if first time step, else add to existing file @@ -259,7 +253,8 @@ class StepResult: kwargs['driver'] = 'mpio' kwargs['comm'] = comm with h5py.File(filename, **kwargs) as handle: - self._to_hdf5(handle, step, parallel=True) + self._to_hdf5(handle, step, parallel=True, + write_rates=write_rates) else: # Gather results at root process all_results = comm.gather(self) @@ -268,15 +263,18 @@ class StepResult: if comm.rank == 0: with h5py.File(filename, **kwargs) as handle: for res in all_results: - res._to_hdf5(handle, step, parallel=False) + res._to_hdf5(handle, step, parallel=False, + write_rates=write_rates) - def _write_hdf5_metadata(self, handle): + def _write_hdf5_metadata(self, handle, write_rates): """Writes result metadata in HDF5 file Parameters ---------- handle : h5py.File or h5py.Group An hdf5 file or group type to store this in. + write_rates : bool + Whether reaction rate datasets are being written. """ # Create and save the 5 dictionaries: @@ -284,8 +282,8 @@ class StepResult: # self.index_mat -> self.volume (TODO: support for changing volumes) # self.index_nuc # reactions - # self.rates[0].index_nuc (can be different from above, above is superset) - # self.rates[0].index_rx + # self.rates.index_nuc (can be different from above, above is superset) + # self.rates.index_rx # these are shared by every step of the simulation, and should be deduplicated. # Store concentration mat and nuclide dictionaries (along with volumes) @@ -295,13 +293,19 @@ class StepResult: mat_list = sorted(self.mat_to_hdf5_ind, key=int) nuc_list = sorted(self.index_nuc) - rxn_list = sorted(self.rates[0].index_rx) + + include_rates = ( + write_rates + and self.rates is not None + and bool(self.rates.index_nuc) + and bool(self.rates.index_rx) + ) + rxn_list = sorted(self.rates.index_rx) if include_rates else [] n_mats = self.n_hdf5_mats n_nuc_number = len(nuc_list) - n_nuc_rxn = len(self.rates[0].index_nuc) + n_nuc_rxn = len(self.rates.index_nuc) if include_rates else 0 n_rxn = len(rxn_list) - n_stages = self.n_stages mat_group = handle.create_group("materials") @@ -315,41 +319,44 @@ class StepResult: for nuc in nuc_list: nuc_single_group = nuc_group.create_group(nuc) nuc_single_group.attrs["atom number index"] = self.index_nuc[nuc] - if nuc in self.rates[0].index_nuc: - nuc_single_group.attrs["reaction rate index"] = self.rates[0].index_nuc[nuc] + if include_rates and nuc in self.rates.index_nuc: + nuc_single_group.attrs["reaction rate index"] = ( + self.rates.index_nuc[nuc]) - rxn_group = handle.create_group("reactions") + if include_rates: + rxn_group = handle.create_group("reactions") - for rxn in rxn_list: - rxn_single_group = rxn_group.create_group(rxn) - rxn_single_group.attrs["index"] = self.rates[0].index_rx[rxn] + for rxn in rxn_list: + rxn_single_group = rxn_group.create_group(rxn) + rxn_single_group.attrs["index"] = ( + self.rates.index_rx[rxn]) # Construct array storage - handle.create_dataset("number", (1, n_stages, n_mats, n_nuc_number), - maxshape=(None, n_stages, n_mats, n_nuc_number), + handle.create_dataset("number", (1, n_mats, n_nuc_number), + maxshape=(None, n_mats, n_nuc_number), chunks=True, dtype='float64') - if n_nuc_rxn > 0 and n_rxn > 0: - handle.create_dataset("reaction rates", (1, n_stages, n_mats, n_nuc_rxn, n_rxn), - maxshape=(None, n_stages, n_mats, n_nuc_rxn, n_rxn), - chunks=True, - dtype='float64') + if include_rates and n_nuc_rxn > 0 and n_rxn > 0: + handle.create_dataset( + "reaction rates", (1, n_mats, n_nuc_rxn, n_rxn), + maxshape=(None, n_mats, n_nuc_rxn, n_rxn), + chunks=True, dtype='float64') - handle.create_dataset("eigenvalues", (1, n_stages, 2), - maxshape=(None, n_stages, 2), dtype='float64') + handle.create_dataset("eigenvalues", (1, 2), + maxshape=(None, 2), dtype='float64') handle.create_dataset("time", (1, 2), maxshape=(None, 2), dtype='float64') - handle.create_dataset("source_rate", (1, n_stages), maxshape=(None, n_stages), + handle.create_dataset("source_rate", (1,), maxshape=(None,), dtype='float64') handle.create_dataset( "depletion time", (1,), maxshape=(None,), dtype="float64") - def _to_hdf5(self, handle, index, parallel=False): + def _to_hdf5(self, handle, index, parallel=False, write_rates: bool = False): """Converts results object into an hdf5 object. Parameters @@ -360,12 +367,14 @@ class StepResult: What step is this? parallel : bool Being called with parallel HDF5? + write_rates : bool, optional + Whether reaction rate datasets are being written. """ if "/number" not in handle: if parallel: comm.barrier() - self._write_hdf5_metadata(handle) + self._write_hdf5_metadata(handle, write_rates) if parallel: comm.barrier() @@ -417,18 +426,14 @@ class StepResult: return # Add data - # Note, for the last step, self.n_stages = 1, even if n_stages != 1. - n_stages = self.n_stages inds = [self.mat_to_hdf5_ind[mat] for mat in self.index_mat] low = min(inds) high = max(inds) - for i in range(n_stages): - number_dset[index, i, low:high+1] = self.data[i] - if has_reactions: - rxn_dset[index, i, low:high+1] = self.rates[i] - if comm.rank == 0: - eigenvalues_dset[index, i] = self.k[i] + number_dset[index, low:high+1] = self.data + if has_reactions: + rxn_dset[index, low:high+1] = self.rates if comm.rank == 0: + eigenvalues_dset[index] = self.k time_dset[index] = self.time source_rate_dset[index] = self.source_rate if self.proc_time is not None: @@ -459,10 +464,24 @@ class StepResult: # Older versions used "power" instead of "source_rate" source_rate_dset = handle["/power"] - results.data = number_dset[step, :, :, :] - results.k = eigenvalues_dset[step, :] + # Check if this is an old format file (with stages dimension) or new format + # Old format: number has shape (n_steps, n_stages, n_mats, n_nucs) + # New format: number has shape (n_steps, n_mats, n_nucs) + has_stages = len(number_dset.shape) == 4 + + if has_stages: + # Old format - extract data from first stage (index 0) + results.data = number_dset[step, 0, :, :] + results.k = eigenvalues_dset[step, 0, :] + # source_rate had shape (n_steps, n_stages) in old format + results.source_rate = source_rate_dset[step, 0] + else: + # New format - no stages dimension + results.data = number_dset[step, :, :] + results.k = eigenvalues_dset[step, :] + results.source_rate = source_rate_dset[step] + results.time = time_dset[step, :] - results.source_rate = source_rate_dset[step, 0] if "depletion time" in handle: proc_time_dset = handle["/depletion time"] @@ -493,33 +512,45 @@ class StepResult: if "reaction rate index" in nuc_handle.attrs: rxn_nuc_to_ind[nuc] = nuc_handle.attrs["reaction rate index"] - for rxn, rxn_handle in handle["/reactions"].items(): - rxn_to_ind[rxn] = rxn_handle.attrs["index"] + if "reactions" in handle: + for rxn, rxn_handle in handle["/reactions"].items(): + rxn_to_ind[rxn] = rxn_handle.attrs["index"] - results.rates = [] - # Reconstruct reactions - for i in range(results.n_stages): - rate = ReactionRates(results.index_mat, rxn_nuc_to_ind, rxn_to_ind, True) - - if "reaction rates" in handle: - rate[:] = handle["/reaction rates"][step, i, :, :, :] - results.rates.append(rate) + # Reconstruct reaction rates + rate = ReactionRates(results.index_mat, rxn_nuc_to_ind, rxn_to_ind, True) + if "reaction rates" in handle: + if has_stages: + # Old format: (n_steps, n_stages, n_mats, n_nucs, n_rxns) + rate[:] = handle["/reaction rates"][step, 0, :, :, :] + else: + # New format: (n_steps, n_mats, n_nucs, n_rxns) + rate[:] = handle["/reaction rates"][step, :, :, :] + results.rates = rate return results @staticmethod - def save(op, x, op_results, t, source_rate, step_ind, proc_time=None, - path: PathLike = "depletion_results.h5"): + def save( + op, + x, + op_results, + t, + source_rate, + step_ind, + proc_time=None, + write_rates: bool = False, + path: PathLike = "depletion_results.h5" + ): """Creates and writes depletion results to disk Parameters ---------- op : openmc.deplete.abc.TransportOperator The operator used to generate these results. - x : list of list of numpy.array - The prior x vectors. Indexed [i][cell] using the above equation. - op_results : list of openmc.deplete.OperatorResult - Results of applying transport operator + x : numpy.array + End-of-step concentrations for each material + op_results : openmc.deplete.OperatorResult + Result of applying transport operator at end of step t : list of float Time indices. source_rate : float @@ -530,7 +561,8 @@ class StepResult: Total process time spent depleting materials. This may be process-dependent and will be reduced across MPI processes. - + write_rates : bool, optional + Whether reaction rates should be written to the results file. path : PathLike Path to file to write. Defaults to 'depletion_results.h5'. @@ -539,26 +571,20 @@ class StepResult: # Get indexing terms vol_dict, nuc_list, burn_list, full_burn_list = op.get_results_info() - stages = len(x) - # Create results results = StepResult() - results.allocate(vol_dict, nuc_list, burn_list, full_burn_list, stages) + results.allocate(vol_dict, nuc_list, burn_list, full_burn_list) n_mat = len(burn_list) - for i in range(stages): - for mat_i in range(n_mat): - results[i, mat_i, :] = x[i][mat_i] + for mat_i in range(n_mat): + results[mat_i, :] = x[mat_i] - ks = [] - for r in op_results: - if isinstance(r.k, type(None)): - ks += [(None, None)] - else: - ks += [(r.k.nominal_value, r.k.std_dev)] - results.k = ks - results.rates = [r.rates for r in op_results] + if isinstance(op_results.k, type(None)): + results.k = (None, None) + else: + results.k = (op_results.k.nominal_value, op_results.k.std_dev) + results.rates = op_results.rates results.time = t results.source_rate = source_rate results.proc_time = proc_time @@ -567,7 +593,7 @@ class StepResult: if not Path(path).is_file(): Path(path).parent.mkdir(parents=True, exist_ok=True) - results.export_to_hdf5(path, step_ind) + results.export_to_hdf5(path, step_ind, write_rates) def transfer_volumes(self, model): """Transfers volumes from depletion results to geometry diff --git a/openmc/deplete/transfer_rates.py b/openmc/deplete/transfer_rates.py index 4c28c7d150..ea9fc9185e 100644 --- a/openmc/deplete/transfer_rates.py +++ b/openmc/deplete/transfer_rates.py @@ -49,9 +49,10 @@ class ExternalRates: self.local_mats = operator.local_mats self.number_of_timesteps = number_of_timesteps - # initialize transfer rates container dict + #initialize transfer rates container dict self.external_rates = {mat: defaultdict(list) for mat in self.burnable_mats} self.external_timesteps = [] + self.redox = {} def _get_material_id(self, val): """Helper method for getting material id from Material obj or name. @@ -300,6 +301,46 @@ class TransferRates(ExternalRates): self.external_timesteps = np.unique(np.concatenate( [self.external_timesteps, timesteps])) + def set_redox(self, material, buffer, oxidation_states, timesteps=None): + """Add redox control to depletable material. + + Parameters + ---------- + material : openmc.Material or str or int + Depletable material + buffer : dict + Dictionary of buffer nuclides used to maintain redox balance. + Keys are nuclide names (strings) and values are their respective + fractions (float) that collectively sum to 1. + oxidation_states : dict + User-defined oxidation states for elements. + Keys are element symbols (e.g., 'H', 'He'), and values are their + corresponding oxidation states as integers (e.g., +1, 0). + timesteps : list of int, optional + List of timestep indices where to set external source rates. + Defaults to None, which means the external source rate is set for + all timesteps. + + """ + material_id = self._get_material_id(material) + if timesteps is not None: + for timestep in timesteps: + check_value('timestep', timestep, range(self.number_of_timesteps)) + timesteps = np.array(timesteps) + else: + timesteps = np.arange(self.number_of_timesteps) + #Check nuclides in buffer exist + for nuc in buffer: + if nuc not in self.chain_nuclides: + raise ValueError(f'{nuc} is not a valid nuclide.') + # Checks element in oxidation states exist + for elm in oxidation_states: + if elm not in ELEMENT_SYMBOL.values(): + raise ValueError(f'{elm} is not a valid element.') + + self.redox[material_id] = (buffer, oxidation_states) + self.external_timesteps = np.unique(np.concatenate( + [self.external_timesteps, timesteps])) class ExternalSourceRates(ExternalRates): """Class for defining external source rates. @@ -366,7 +407,7 @@ class ExternalSourceRates(ExternalRates): rate : float External source rate in units of mass per time. A positive or negative value corresponds to a feed or removal rate, respectively. - units : {'g/s', 'g/min', 'g/h', 'g/d', 'g/a'} + rate_units : {'g/s', 'g/min', 'g/h', 'g/d', 'g/a'} Units for values specified in the `rate` argument. 's' for seconds, 'min' for minutes, 'h' for hours, 'a' for Julian years. timesteps : list of int, optional diff --git a/openmc/examples.py b/openmc/examples.py index 5578d513ea..01dd9d01f9 100644 --- a/openmc/examples.py +++ b/openmc/examples.py @@ -83,7 +83,7 @@ def pwr_pin_cell() -> openmc.Model: constraints={'fissionable': True} ) - plot = openmc.Plot.from_geometry(model.geometry) + plot = openmc.SlicePlot.from_geometry(model.geometry) plot.pixels = (300, 300) plot.color_by = 'material' model.plots.append(plot) @@ -429,7 +429,7 @@ def pwr_core() -> openmc.Model: model.settings.source = openmc.IndependentSource(space=openmc.stats.Box( [-160, -160, -183], [160, 160, 183])) - plot = openmc.Plot() + plot = openmc.SlicePlot() plot.origin = (125, 125, 0) plot.width = (250, 250) plot.pixels = (3000, 3000) @@ -544,7 +544,7 @@ def pwr_assembly() -> openmc.Model: constraints={'fissionable': True} ) - plot = openmc.Plot() + plot = openmc.SlicePlot() plot.origin = (0.0, 0.0, 0) plot.width = (21.42, 21.42) plot.pixels = (300, 300) diff --git a/openmc/executor.py b/openmc/executor.py index aacc48b3fa..9cd2993454 100644 --- a/openmc/executor.py +++ b/openmc/executor.py @@ -164,7 +164,7 @@ def plot_inline(plots, openmc_exec='openmc', cwd='.', path_input=None): Parameters ---------- - plots : Iterable of openmc.Plot + plots : Iterable of openmc.PlotBase Plots to display openmc_exec : str Path to OpenMC executable diff --git a/openmc/filter.py b/openmc/filter.py index 6a666d2a02..550146f85d 100644 --- a/openmc/filter.py +++ b/openmc/filter.py @@ -1839,12 +1839,21 @@ class DistribcellFilter(Filter): @property def paths(self): - return self._paths + if self._paths is None: + if not hasattr(self, '_geometry'): + raise ValueError( + "Model must be exported before the 'paths' attribute is" \ + "available for a DistribcellFilter.") - @paths.setter - def paths(self, paths): - cv.check_iterable_type('paths', paths, str) - self._paths = paths + # Determine paths for cell instances + self._geometry.determine_paths() + + # Get paths for the corresponding cell + cell_id = self.bins[0] + cell = self._geometry.get_all_cells()[cell_id] + self._paths = cell.paths + + return self._paths @Filter.bins.setter def bins(self, bins): diff --git a/openmc/lib/cell.py b/openmc/lib/cell.py index 971a24cba9..dfd09d2f9c 100644 --- a/openmc/lib/cell.py +++ b/openmc/lib/cell.py @@ -34,6 +34,10 @@ _dll.openmc_cell_get_temperature.argtypes = [ c_int32, POINTER(c_int32), POINTER(c_double)] _dll.openmc_cell_get_temperature.restype = c_int _dll.openmc_cell_get_temperature.errcheck = _error_handler +_dll.openmc_cell_get_density.argtypes = [ + c_int32, POINTER(c_int32), POINTER(c_double)] +_dll.openmc_cell_get_density.restype = c_int +_dll.openmc_cell_get_density.errcheck = _error_handler _dll.openmc_cell_get_name.argtypes = [c_int32, POINTER(c_char_p)] _dll.openmc_cell_get_name.restype = c_int _dll.openmc_cell_get_name.errcheck = _error_handler @@ -58,6 +62,10 @@ _dll.openmc_cell_set_temperature.argtypes = [ c_int32, c_double, POINTER(c_int32), c_bool] _dll.openmc_cell_set_temperature.restype = c_int _dll.openmc_cell_set_temperature.errcheck = _error_handler +_dll.openmc_cell_set_density.argtypes = [ + c_int32, c_double, POINTER(c_int32), c_bool] +_dll.openmc_cell_set_density.restype = c_int +_dll.openmc_cell_set_density.errcheck = _error_handler _dll.openmc_cell_set_translation.argtypes = [c_int32, POINTER(c_double)] _dll.openmc_cell_set_translation.restype = c_int _dll.openmc_cell_set_translation.errcheck = _error_handler @@ -236,6 +244,44 @@ class Cell(_FortranObjectWithID): _dll.openmc_cell_set_temperature(self._index, T, instance, set_contained) + def get_density(self, instance: int | None = None): + """Get the density of a cell in [g/cm3] + + Parameters + ---------- + instance : int or None + Which instance of the cell + + """ + + if instance is not None: + instance = c_int32(instance) + + rho = c_double() + _dll.openmc_cell_get_density(self._index, instance, rho) + return rho.value + + def set_density(self, rho: float, instance: int | None = None, + set_contained: bool = False): + """Set the density of a cell + + Parameters + ---------- + rho : float + Density of the cell in [g/cm3] + instance : int or None + Which instance of the cell + set_contained : bool + If cell is not filled by a material, whether to set the density + of all filled cells + + """ + + if instance is not None: + instance = c_int32(instance) + + _dll.openmc_cell_set_density(self._index, rho, instance, set_contained) + @property def translation(self): translation = np.zeros(3) diff --git a/openmc/lib/core.py b/openmc/lib/core.py index 9f8db69d57..02c7784d1c 100644 --- a/openmc/lib/core.py +++ b/openmc/lib/core.py @@ -7,12 +7,14 @@ import os from pathlib import Path from random import getrandbits from tempfile import TemporaryDirectory +import traceback as tb import numpy as np from numpy.ctypeslib import as_array from . import _dll from .error import _error_handler +from ..mpi import comm from openmc.checkvalue import PathLike import openmc.lib import openmc @@ -632,6 +634,9 @@ class TemporarySession: model : openmc.Model, optional OpenMC model to use for the session. If None, a minimal working model is created. + cwd : PathLike, optional + Working directory in which to run OpenMC. If None, a temporary directory + is created and deleted automatically. **init_kwargs Keyword arguments to pass to :func:`openmc.lib.init`. @@ -639,10 +644,13 @@ class TemporarySession: ---------- model : openmc.Model The OpenMC model used for the session. + comm : mpi4py.MPI.Intracomm + The MPI intracommunicator used for the session. """ - def __init__(self, model=None, **init_kwargs): - self.init_kwargs = init_kwargs + def __init__(self, model=None, cwd=None, **init_kwargs): + self.init_kwargs = dict(init_kwargs) + self.cwd = cwd if model is None: surf = openmc.Sphere(boundary_type="vacuum") cell = openmc.Cell(region=-surf) @@ -652,6 +660,10 @@ class TemporarySession: particles=1, batches=1, output={'summary': False}) self.model = model + # Determine MPI intercommunicator + self.init_kwargs.setdefault('intracomm', comm) + self.comm = self.init_kwargs['intracomm'] + def __enter__(self): """Initialize the OpenMC library in a temporary directory.""" # If already initialized, the context manager is a no-op @@ -662,14 +674,24 @@ class TemporarySession: # Store original working directory self.orig_dir = Path.cwd() - # Set up temporary directory - self.tmp_dir = TemporaryDirectory() - working_dir = Path(self.tmp_dir.name) - working_dir.mkdir(parents=True, exist_ok=True) - os.chdir(working_dir) + if self.cwd is None: + # Set up temporary directory on rank 0 + if self.comm.rank == 0: + self._tmp_dir = TemporaryDirectory() + self.cwd = self._tmp_dir.name - # Export model and initialize OpenMC - self.model.export_to_model_xml() + # Broadcast the path so that all ranks use the same directory + self.cwd = self.comm.bcast(self.cwd) + + # Create and change to specified directory + self.cwd = Path(self.cwd) + self.cwd.mkdir(parents=True, exist_ok=True) + os.chdir(self.cwd) + + # Export model on first rank and initialize OpenMC + if self.comm.rank == 0: + self.model.export_to_model_xml() + self.comm.barrier() openmc.lib.init(**self.init_kwargs) return self @@ -679,11 +701,24 @@ class TemporarySession: if self.already_initialized: return + # If an exception occurred, abort all ranks immediately + if exc_type is not None: + # Print exception info on the rank that failed + tb.print_exception(exc_type, exc_value, traceback) + sys.stdout.flush() + + # Abort all MPI processes + self.comm.Abort(1) + try: finalize() finally: os.chdir(self.orig_dir) - self.tmp_dir.cleanup() + + # Make sure all ranks have finalized before deleting temporary dir + self.comm.barrier() + if hasattr(self, '_tmp_dir'): + self._tmp_dir.cleanup() class _DLLGlobal: diff --git a/openmc/lib/plot.py b/openmc/lib/plot.py index f97348b20b..68f61821c5 100644 --- a/openmc/lib/plot.py +++ b/openmc/lib/plot.py @@ -52,7 +52,7 @@ class _PlotBase(Structure): C-Type Attributes ----------------- - origin : openmc.lib.plot._Position + origin_ : openmc.lib.plot._Position A position defining the origin of the plot. width_ : openmc.lib.plot._Position The width of the plot along the x, y, and z axes, respectively @@ -60,6 +60,8 @@ class _PlotBase(Structure): The axes basis of the plot view. pixels_ : c_size_t[3] The resolution of the plot in the horizontal and vertical dimensions + color_overlaps_ : c_bool + Whether to assign unique IDs (-3) to overlapping regions. level_ : c_int The universe level for the plot view @@ -187,14 +189,6 @@ class _PlotBase(Structure): def color_overlaps(self, color_overlaps): self.color_overlaps_ = color_overlaps - @property - def color_overlaps(self): - return self.color_overlaps_ - - @color_overlaps.setter - def color_overlaps(self, val): - self.color_overlaps_ = val - def __repr__(self): out_str = ["-----", "Plot:", diff --git a/openmc/material.py b/openmc/material.py index c7b954b666..735a057432 100644 --- a/openmc/material.py +++ b/openmc/material.py @@ -60,6 +60,26 @@ class Material(IDManagerMixin): temperature : float, optional Temperature of the material in Kelvin. If not specified, the material inherits the default temperature applied to the model. + density : float, optional + Density of the material (units defined separately) + density_units : str + Units used for `density`. Can be one of 'g/cm3', 'g/cc', 'kg/m3', + 'atom/b-cm', 'atom/cm3', 'sum', or 'macro'. The 'macro' unit only + applies in the case of a multi-group calculation. Defaults to 'sum'. + depletable : bool, optional + Indicate whether the material is depletable. Defaults to False. + volume : float, optional + Volume of the material in cm^3. This can either be set manually or + calculated in a stochastic volume calculation and added via the + :meth:`Material.add_volume_information` method. + components : dict of str to float or dict + Dictionary mapping element or nuclide names to their atom or weight + percent. To specify enrichment of an element, the entry of + ``components`` for that element must instead be a dictionary containing + the keyword arguments as well as a value for ``'percent'`` + percent_type : {'ao', 'wo'} + Whether the values in `components` should be interpreted as atom percent + ('ao') or weight percent ('wo'). Attributes ---------- @@ -111,17 +131,28 @@ class Material(IDManagerMixin): next_id = 1 used_ids = set() - def __init__(self, material_id=None, name='', temperature=None): + def __init__( + self, + material_id: int | None = None, + name: str = "", + temperature: float | None = None, + density: float | None = None, + density_units: str = "sum", + depletable: bool | None = False, + volume: float | None = None, + components: dict | None = None, + percent_type: str = "ao", + ): # Initialize class attributes self.id = material_id self.name = name self.temperature = temperature self._density = None - self._density_units = 'sum' - self._depletable = False + self._density_units = density_units + self._depletable = depletable self._paths = None self._num_instances = None - self._volume = None + self._volume = volume self._atoms = {} self._isotropic = [] self._ncrystal_cfg = None @@ -136,6 +167,15 @@ class Material(IDManagerMixin): # If specified, a list of table names self._sab = [] + # Set density if provided + if density is not None: + self.set_density(density_units, density) + + # Add components if provided + if components is not None: + self.add_components(components, percent_type=percent_type) + + def __repr__(self) -> str: string = 'Material\n' string += '{: <16}=\t{}\n'.format('\tID', self._id) @@ -290,11 +330,13 @@ class Material(IDManagerMixin): return self.get_decay_photon_energy(0.0) def get_decay_photon_energy( - self, - clip_tolerance: float = 1e-6, - units: str = 'Bq', - volume: float | None = None - ) -> Univariate | None: + self, + clip_tolerance: float = 1e-6, + units: str = 'Bq', + volume: float | None = None, + exclude_nuclides: list[str] | None = None, + include_nuclides: list[str] | None = None + ) -> Univariate | None: r"""Return energy distribution of decay photons from unstable nuclides. .. versionadded:: 0.14.0 @@ -302,22 +344,31 @@ class Material(IDManagerMixin): Parameters ---------- clip_tolerance : float - Maximum fraction of :math:`\sum_i x_i p_i` for discrete - distributions that will be discarded. + Maximum fraction of :math:`\sum_i x_i p_i` for discrete distributions + that will be discarded. units : {'Bq', 'Bq/g', 'Bq/kg', 'Bq/cm3'} Specifies the units on the integral of the distribution. volume : float, optional Volume of the material. If not passed, defaults to using the :attr:`Material.volume` attribute. + exclude_nuclides : list of str, optional + Nuclides to exclude from the photon source calculation. + include_nuclides : list of str, optional + Nuclides to include in the photon source calculation. If specified, + only these nuclides are used. Returns ------- Univariate or None - Decay photon energy distribution. The integral of this distribution - is the total intensity of the photon source in the requested units. + Decay photon energy distribution. The integral of this distribution is + the total intensity of the photon source in the requested units. """ cv.check_value('units', units, {'Bq', 'Bq/g', 'Bq/kg', 'Bq/cm3'}) + + if exclude_nuclides is not None and include_nuclides is not None: + raise ValueError("Cannot specify both exclude_nuclides and include_nuclides") + if units == 'Bq': multiplier = volume if volume is not None else self.volume if multiplier is None: @@ -332,6 +383,11 @@ class Material(IDManagerMixin): dists = [] probs = [] for nuc, atoms_per_bcm in self.get_nuclide_atom_densities().items(): + if exclude_nuclides is not None and nuc in exclude_nuclides: + continue + if include_nuclides is not None and nuc not in include_nuclides: + continue + source_per_atom = openmc.data.decay_photon_energy(nuc) if source_per_atom is not None and atoms_per_bcm > 0.0: dists.append(source_per_atom) diff --git a/openmc/mesh.py b/openmc/mesh.py index 2e9abd1b65..ce5218b5e9 100644 --- a/openmc/mesh.py +++ b/openmc/mesh.py @@ -5,6 +5,7 @@ from collections.abc import Iterable, Sequence, Mapping from functools import wraps from math import pi, sqrt, atan2 from numbers import Integral, Real +from pathlib import Path from typing import Protocol import h5py @@ -287,6 +288,7 @@ class MeshBase(IDManagerMixin, ABC): model: openmc.Model, n_samples: int | tuple[int, int, int] = 10_000, include_void: bool = True, + material_volumes: MeshMaterialVolumes | None = None, **kwargs ) -> list[openmc.Material]: """Generate homogenized materials over each element in a mesh. @@ -305,8 +307,12 @@ class MeshBase(IDManagerMixin, ABC): the x, y, and z dimensions. include_void : bool, optional Whether homogenization should include voids. + material_volumes : MeshMaterialVolumes, optional + Previously computed mesh material volumes to use for homogenization. + If not provided, they will be computed by calling + :meth:`material_volumes`. **kwargs - Keyword-arguments passed to :meth:`MeshBase.material_volumes`. + Keyword-arguments passed to :meth:`material_volumes`. Returns ------- @@ -314,23 +320,16 @@ class MeshBase(IDManagerMixin, ABC): Homogenized material in each mesh element """ - vols = self.material_volumes(model, n_samples, **kwargs) + if material_volumes is None: + vols = self.material_volumes(model, n_samples, **kwargs) + else: + vols = material_volumes mat_volume_by_element = [vols.by_element(i) for i in range(vols.num_elements)] + # Get dictionary of all materials + materials = model._get_all_materials() + # Create homogenized material for each element - materials = model.geometry.get_all_materials() - - # Account for materials in DAGMC universes - # TODO: This should really get incorporated in lower-level calls to - # get_all_materials, but right now it requires information from the - # Model object - for cell in model.geometry.get_all_cells().values(): - if isinstance(cell.fill, openmc.DAGMCUniverse): - names = cell.fill.material_names - materials.update({ - mat.id: mat for mat in model.materials if mat.name in names - }) - homogenized_materials = [] for mat_volume_list in mat_volume_by_element: material_ids, volumes = [list(x) for x in zip(*mat_volume_list)] @@ -402,7 +401,7 @@ class MeshBase(IDManagerMixin, ABC): # In order to get mesh into model, we temporarily replace the # tallies with a single mesh tally using the current mesh - original_tallies = model.tallies + original_tallies = list(model.tallies) new_tally = openmc.Tally() new_tally.filters = [openmc.MeshFilter(self)] new_tally.scores = ['flux'] @@ -424,7 +423,6 @@ class MeshBase(IDManagerMixin, ABC): # Restore original tallies model.tallies = original_tallies - return volumes @@ -2446,6 +2444,7 @@ class UnstructuredMesh(MeshBase): _UNSUPPORTED_ELEM = -1 _LINEAR_TET = 0 _LINEAR_HEX = 1 + _VTK_TETRA = 10 def __init__(self, filename: PathLike, library: str, mesh_id: int | None = None, name: str = '', length_multiplier: float = 1.0, @@ -2655,7 +2654,8 @@ class UnstructuredMesh(MeshBase): warnings.warn( "The 'UnstructuredMesh.write_vtk_mesh' method has been renamed " "to 'write_data_to_vtk' and will be removed in a future version " - " of OpenMC.", FutureWarning + " of OpenMC.", + FutureWarning, ) self.write_data_to_vtk(**kwargs) @@ -2673,9 +2673,10 @@ class UnstructuredMesh(MeshBase): Parameters ---------- filename : str or pathlib.Path - Name of the VTK file to write. If the filename ends in '.vtu' then a - binary VTU format file will be written, if the filename ends in - '.vtk' then a legacy VTK file will be written. + Name of the VTK file to write. If the filename ends in '.vtkhdf' + then a VTKHDF format file will be written. If the filename ends in + '.vtu' then a binary VTU format file will be written. If the + filename ends in '.vtk' then a legacy VTK file will be written. datasets : dict Dictionary whose keys are the data labels and values are numpy appropriately sized arrays of the data @@ -2683,6 +2684,35 @@ class UnstructuredMesh(MeshBase): Whether or not to normalize the data by the volume of the mesh elements """ + + if Path(filename).suffix == ".vtkhdf": + + self._write_data_to_vtk_hdf5_format( + filename=filename, + datasets=datasets, + volume_normalization=volume_normalization, + ) + + elif Path(filename).suffix == ".vtk" or Path(filename).suffix == ".vtu": + + self._write_data_to_vtk_ascii_format( + filename=filename, + datasets=datasets, + volume_normalization=volume_normalization, + ) + + else: + raise ValueError( + "Unsupported file extension, The filename must end with " + "'.vtkhdf', '.vtu' or '.vtk'" + ) + + def _write_data_to_vtk_ascii_format( + self, + filename: PathLike | None = None, + datasets: dict | None = None, + volume_normalization: bool = True, + ): from vtkmodules.util import numpy_support from vtkmodules import vtkCommonCore from vtkmodules import vtkCommonDataModel @@ -2690,9 +2720,7 @@ class UnstructuredMesh(MeshBase): from vtkmodules import vtkIOXML if self.connectivity is None or self.vertices is None: - raise RuntimeError( - "This mesh has not been loaded from a statepoint file." - ) + raise RuntimeError("This mesh has not been loaded from a statepoint file.") if filename is None: filename = f"mesh_{self.id}.vtk" @@ -2774,29 +2802,128 @@ class UnstructuredMesh(MeshBase): writer.Write() + def _write_data_to_vtk_hdf5_format( + self, + filename: PathLike | None = None, + datasets: dict | None = None, + volume_normalization: bool = True, + ): + def append_dataset(dset, array): + """Convenience function to append data to an HDF5 dataset""" + origLen = dset.shape[0] + dset.resize(origLen + array.shape[0], axis=0) + dset[origLen:] = array + + if self.library != "moab": + raise NotImplementedError("VTKHDF output is only supported for MOAB meshes") + + # the self.connectivity contains arrays of length 8 to support hex + # elements as well, in the case of tetrahedra mesh elements, the + # last 4 values are -1 and are removed + trimmed_connectivity = [] + for cell in self.connectivity: + # Find the index of the first -1 value, if any + first_negative_index = np.where(cell == -1)[0] + if first_negative_index.size > 0: + # Slice the array up to the first -1 value + trimmed_connectivity.append(cell[: first_negative_index[0]]) + else: + # No -1 values, append the whole cell + trimmed_connectivity.append(cell) + trimmed_connectivity = np.array(trimmed_connectivity, dtype="int32").flatten() + + # MOAB meshes supports tet elements only so we know it has 4 points per cell + points_per_cell = 4 + + # offsets are the indices of the first point of each cell in the array of points + offsets = np.arange(0, self.n_elements * points_per_cell + 1, points_per_cell) + + for name, data in datasets.items(): + if data.shape != self.dimension: + raise ValueError( + f'Cannot apply dataset "{name}" with ' + f"shape {data.shape} to mesh {self.id} " + f"with dimensions {self.dimension}" + ) + + with h5py.File(filename, "w") as f: + + root = f.create_group("VTKHDF") + vtk_file_format_version = (2, 1) + root.attrs["Version"] = vtk_file_format_version + ascii_type = "UnstructuredGrid".encode("ascii") + root.attrs.create( + "Type", + ascii_type, + dtype=h5py.string_dtype("ascii", len(ascii_type)), + ) + + # create hdf5 file structure + root.create_dataset("NumberOfPoints", (0,), maxshape=(None,), dtype="i8") + root.create_dataset("Types", (0,), maxshape=(None,), dtype="uint8") + root.create_dataset("Points", (0, 3), maxshape=(None, 3), dtype="f") + root.create_dataset( + "NumberOfConnectivityIds", (0,), maxshape=(None,), dtype="i8" + ) + root.create_dataset("NumberOfCells", (0,), maxshape=(None,), dtype="i8") + root.create_dataset("Offsets", (0,), maxshape=(None,), dtype="i8") + root.create_dataset("Connectivity", (0,), maxshape=(None,), dtype="i8") + + append_dataset(root["NumberOfPoints"], np.array([len(self.vertices)])) + append_dataset(root["Points"], self.vertices) + append_dataset( + root["NumberOfConnectivityIds"], + np.array([len(trimmed_connectivity)]), + ) + append_dataset(root["Connectivity"], trimmed_connectivity) + append_dataset(root["NumberOfCells"], np.array([self.n_elements])) + append_dataset(root["Offsets"], offsets) + + append_dataset( + root["Types"], np.full(self.n_elements, self._VTK_TETRA, dtype="uint8") + ) + + cell_data_group = root.create_group("CellData") + + for name, data in datasets.items(): + + cell_data_group.create_dataset( + name, (0,), maxshape=(None,), dtype="float64", chunks=True + ) + + if volume_normalization: + data /= self.volumes + append_dataset(cell_data_group[name], data) + @classmethod def from_hdf5(cls, group: h5py.Group, mesh_id: int, name: str): - filename = group['filename'][()].decode() - library = group['library'][()].decode() - if 'options' in group.attrs: + filename = group["filename"][()].decode() + library = group["library"][()].decode() + if "options" in group.attrs: options = group.attrs['options'].decode() else: options = None - mesh = cls(filename=filename, library=library, mesh_id=mesh_id, name=name, options=options) + mesh = cls( + filename=filename, + library=library, + mesh_id=mesh_id, + name=name, + options=options, + ) mesh._has_statepoint_data = True - vol_data = group['volumes'][()] + vol_data = group["volumes"][()] mesh.volumes = np.reshape(vol_data, (vol_data.shape[0],)) mesh.n_elements = mesh.volumes.size - vertices = group['vertices'][()] + vertices = group["vertices"][()] mesh._vertices = vertices.reshape((-1, 3)) - connectivity = group['connectivity'][()] + connectivity = group["connectivity"][()] mesh._connectivity = connectivity.reshape((-1, 8)) - mesh._element_types = group['element_types'][()] + mesh._element_types = group["element_types"][()] - if 'length_multiplier' in group: - mesh.length_multiplier = group['length_multiplier'][()] + if "length_multiplier" in group: + mesh.length_multiplier = group["length_multiplier"][()] return mesh @@ -2815,7 +2942,7 @@ class UnstructuredMesh(MeshBase): element.set("library", self._library) if self.options is not None: - element.set('options', self.options) + element.set("options", self.options) subelement = ET.SubElement(element, "filename") subelement.text = str(self.filename) diff --git a/openmc/mgxs/__init__.py b/openmc/mgxs/__init__.py index 5de85afb0e..682b5d5507 100644 --- a/openmc/mgxs/__init__.py +++ b/openmc/mgxs/__init__.py @@ -13,8 +13,8 @@ GROUP_STRUCTURES = {} - "XMAS-172_" designed for LWR analysis ([SAR1990]_, [SAN2004]_) - "SHEM-361_" designed for LWR analysis to eliminate self-shielding calculations of thermal resonances ([HFA2005]_, [SAN2007]_, [HEB2008]_) -- "SCALE-X" (where X is 44 which is designed for criticality analysis - and 252 is designed for thermal reactors) for the SCALE code suite +- "SCALE-X" (where X is 44 which is designed for criticality analysis, 252 is designed + for thermal reactors and 999 for multipurpose activation) for the SCALE code suite ([ZAL1999]_ and [REARDEN2013]_) - "MPACT-X" (where X is 51 (PWR), 60 (BWR), 69 (Magnox)) from the MPACT_ reactor physics code ([KIM2019]_ and [KIM2020]_) @@ -29,6 +29,7 @@ GROUP_STRUCTURES = {} .. _SCALE44: https://www-nds.iaea.org/publications/indc/indc-czr-0001.pdf .. _ECCO-33: https://serpent.vtt.fi/mediawiki/index.php/ECCO_33-group_structure .. _SCALE252: https://oecd-nea.org/science/wpncs/amct/workingarea/meeting2013/EGAMCT2013_08.pdf +.. _SCALE999: https://info.ornl.gov/sites/publications/Files/Pub67728.pdf, https://www.nrc.gov/docs/ML1218/ML12184A002.pdf .. _MPACT: https://vera.ornl.gov/mpact/ .. _XMAS-172: https://www-nds.iaea.org/wimsd/energy.htm .. _SHEM-361: http://merlin.polymtl.ca/downloads/FP214.pdf @@ -593,7 +594,208 @@ GROUP_STRUCTURES['CCFE-709'] = np.array([ 2.4000e8, 2.8000e8, 3.2000e8, 3.6000e8, 4.0000e8, 4.4000e8, 4.8000e8, 5.2000e8, 5.6000e8, 6.0000e8, 6.4000e8, 6.8000e8, 7.2000e8, 7.6000e8, 8.0000e8, - 8.4000e8, 8.8000e8, 9.2000e8, 9.6000e8, 1.0000e9,]) + 8.4000e8, 8.8000e8, 9.2000e8, 9.6000e8, 1.0000e9]) +GROUP_STRUCTURES['SCALE-999'] = np.array([ + 1.000e-5, 1.000e-4, 5.000e-4, 7.500e-4, 1.000e-3, + 1.200e-3, 1.500e-3, 2.000e-3, 2.500e-3, 3.000e-3, + 4.000e-3, 5.000e-3, 7.500e-3, 1.000e-2, 1.450e-2, + 1.850e-2, 2.100e-2, 2.530e-2, 3.000e-2, 4.000e-2, + 5.000e-2, 6.000e-2, 7.000e-2, 8.000e-2, 9.000e-2, + 1.000e-1, 1.250e-1, 1.500e-1, 1.750e-1, 1.840e-1, + 2.000e-1, 2.250e-1, 2.500e-1, 2.750e-1, 3.000e-1, + 3.250e-1, 3.500e-1, 3.668e-1, 3.750e-1, 4.000e-1, + 4.140e-1, 4.500e-1, 5.000e-1, 5.316e-1, 5.500e-1, + 6.000e-1, 6.250e-1, 6.500e-1, 6.826e-1, 7.000e-1, + 7.500e-1, 8.000e-1, 8.500e-1, 8.764e-1, 9.000e-1, + 9.250e-1, 9.500e-1, 9.750e-1, 1.000e+0, 1.010e+0, + 1.020e+0, 1.030e+0, 1.040e+0, 1.050e+0, 1.060e+0, + 1.070e+0, 1.080e+0, 1.090e+0, 1.100e+0, 1.110e+0, + 1.120e+0, 1.130e+0, 1.140e+0, 1.150e+0, 1.175e+0, + 1.200e+0, 1.225e+0, 1.250e+0, 1.300e+0, 1.350e+0, + 1.400e+0, 1.450e+0, 1.500e+0, 1.545e+0, 1.590e+0, + 1.635e+0, 1.680e+0, 1.725e+0, 1.770e+0, 1.815e+0, + 1.860e+0, 1.900e+0, 1.940e+0, 1.970e+0, 2.000e+0, + 2.060e+0, 2.120e+0, 2.165e+0, 2.210e+0, 2.255e+0, + 2.300e+0, 2.340e+0, 2.380e+0, 2.425e+0, 2.470e+0, + 2.520e+0, 2.570e+0, 2.620e+0, 2.670e+0, 2.720e+0, + 2.770e+0, 2.820e+0, 2.870e+0, 2.920e+0, 2.970e+0, + 3.000e+0, 3.100e+0, 3.200e+0, 3.300e+0, 3.500e+0, + 3.620e+0, 3.730e+0, 3.830e+0, 3.928e+0, 4.000e+0, + 4.100e+0, 4.300e+0, 4.500e+0, 4.750e+0, 4.875e+0, + 5.000e+0, 5.044e+0, 5.250e+0, 5.400e+0, 5.550e+0, + 5.700e+0, 5.850e+0, 6.000e+0, 6.250e+0, 6.375e+0, + 6.500e+0, 6.625e+0, 6.750e+0, 6.875e+0, 7.000e+0, + 7.075e+0, 7.150e+0, 7.625e+0, 8.100e+0, 8.208e+0, + 8.315e+0, 8.708e+0, 9.100e+0, 9.550e+0, 1.000e+1, + 1.034e+1, 1.068e+1, 1.109e+1, 1.150e+1, 1.170e+1, + 1.190e+1, 1.240e+1, 1.290e+1, 1.333e+1, 1.375e+1, + 1.408e+1, 1.440e+1, 1.475e+1, 1.510e+1, 1.555e+1, + 1.600e+1, 1.650e+1, 1.700e+1, 1.730e+1, 1.760e+1, + 1.805e+1, 1.850e+1, 1.875e+1, 1.900e+1, 1.940e+1, + 2.000e+1, 2.050e+1, 2.100e+1, 2.175e+1, 2.250e+1, + 2.375e+1, 2.500e+1, 2.625e+1, 2.750e+1, 2.826e+1, + 2.902e+1, 2.951e+1, 3.000e+1, 3.063e+1, 3.125e+1, + 3.150e+1, 3.175e+1, 3.250e+1, 3.325e+1, 3.350e+1, + 3.375e+1, 3.418e+1, 3.460e+1, 3.500e+1, 3.550e+1, + 3.600e+1, 3.700e+1, 3.713e+1, 3.727e+1, 3.763e+1, + 3.800e+1, 3.855e+1, 3.910e+1, 3.935e+1, 3.960e+1, + 4.030e+1, 4.100e+1, 4.170e+1, 4.240e+1, 4.320e+1, + 4.400e+1, 4.460e+1, 4.520e+1, 4.610e+1, 4.700e+1, + 4.743e+1, 4.785e+1, 4.808e+1, 4.830e+1, 4.875e+1, + 4.920e+1, 4.990e+1, 5.060e+1, 5.130e+1, 5.200e+1, + 5.270e+1, 5.340e+1, 5.620e+1, 5.800e+1, 6.000e+1, + 6.100e+1, 6.122e+1, 6.144e+1, 6.300e+1, 6.500e+1, + 6.625e+1, 6.750e+1, 6.975e+1, 7.200e+1, 7.400e+1, + 7.600e+1, 7.745e+1, 7.889e+1, 7.945e+1, 8.000e+1, + 8.170e+1, 8.200e+1, 8.400e+1, 8.600e+1, 8.800e+1, + 9.000e+1, 9.250e+1, 9.500e+1, 9.700e+1, 1.000e+2, + 1.012e+2, 1.038e+2, 1.050e+2, 1.080e+2, 1.105e+2, + 1.130e+2, 1.160e+2, 1.175e+2, 1.190e+2, 1.205e+2, + 1.220e+2, 1.240e+2, 1.260e+2, 1.280e+2, 1.301e+2, + 1.325e+2, 1.350e+2, 1.375e+2, 1.400e+2, 1.430e+2, + 1.450e+2, 1.475e+2, 1.500e+2, 1.525e+2, 1.550e+2, + 1.575e+2, 1.600e+2, 1.625e+2, 1.650e+2, 1.670e+2, + 1.700e+2, 1.716e+2, 1.739e+2, 1.763e+2, 1.786e+2, + 1.800e+2, 1.877e+2, 1.885e+2, 1.915e+2, 1.930e+2, + 1.962e+2, 1.999e+2, 2.020e+2, 2.074e+2, 2.088e+2, + 2.095e+2, 2.122e+2, 2.145e+2, 2.175e+2, 2.200e+2, + 2.237e+2, 2.269e+2, 2.301e+2, 2.333e+2, 2.367e+2, + 2.400e+2, 2.442e+2, 2.484e+2, 2.527e+2, 2.571e+2, + 2.615e+2, 2.661e+2, 2.707e+2, 2.754e+2, 2.801e+2, + 2.850e+2, 2.899e+2, 2.948e+2, 2.999e+2, 3.050e+2, + 3.107e+2, 3.165e+2, 3.224e+2, 3.284e+2, 3.345e+2, + 3.408e+2, 3.471e+2, 3.536e+2, 3.591e+2, 3.648e+2, + 3.705e+2, 3.764e+2, 3.823e+2, 3.883e+2, 3.944e+2, + 4.007e+2, 4.070e+2, 4.134e+2, 4.199e+2, 4.265e+2, + 4.332e+2, 4.400e+2, 4.470e+2, 4.540e+2, 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1.878e+5, 1.902e+5, + 1.926e+5, 1.962e+5, 2.000e+5, 2.024e+5, 2.050e+5, + 2.076e+5, 2.102e+5, 2.128e+5, 2.155e+5, 2.182e+5, + 2.209e+5, 2.237e+5, 2.265e+5, 2.294e+5, 2.323e+5, + 2.352e+5, 2.381e+5, 2.411e+5, 2.442e+5, 2.472e+5, + 2.500e+5, 2.527e+5, 2.555e+5, 2.584e+5, 2.612e+5, + 2.641e+5, 2.670e+5, 2.700e+5, 2.732e+5, 2.767e+5, + 2.802e+5, 2.837e+5, 2.873e+5, 2.909e+5, 2.945e+5, + 2.972e+5, 2.985e+5, 3.020e+5, 3.053e+5, 3.088e+5, + 3.122e+5, 3.157e+5, 3.192e+5, 3.228e+5, 3.264e+5, + 3.300e+5, 3.337e+5, 3.379e+5, 3.422e+5, 3.465e+5, + 3.508e+5, 3.553e+5, 3.597e+5, 3.643e+5, 3.688e+5, + 3.735e+5, 3.782e+5, 3.829e+5, 3.877e+5, 3.938e+5, + 4.000e+5, 4.076e+5, 4.138e+5, 4.200e+5, 4.249e+5, + 4.299e+5, 4.349e+5, 4.400e+5, 4.452e+5, 4.505e+5, + 4.553e+5, 4.601e+5, 4.650e+5, 4.700e+5, 4.772e+5, + 4.845e+5, 4.920e+5, 4.995e+5, 5.054e+5, 5.113e+5, + 5.173e+5, 5.234e+5, 5.299e+5, 5.365e+5, 5.432e+5, + 5.500e+5, 5.557e+5, 5.614e+5, 5.672e+5, 5.730e+5, + 5.784e+5, 5.891e+5, 6.000e+5, 6.081e+5, 6.158e+5, + 6.235e+5, 6.313e+5, 6.393e+5, 6.468e+5, 6.545e+5, + 6.622e+5, 6.700e+5, 6.790e+5, 6.926e+5, 7.065e+5, + 7.154e+5, 7.244e+5, 7.335e+5, 7.427e+5, 7.500e+5, + 7.576e+5, 7.653e+5, 7.730e+5, 7.808e+5, 7.904e+5, + 8.002e+5, 8.100e+5, 8.200e+5, 8.301e+5, 8.403e+5, + 8.506e+5, 8.611e+5, 8.750e+5, 8.874e+5, 9.000e+5, + 9.072e+5, 9.200e+5, 9.400e+5, 9.616e+5, 9.800e+5, + 1.003e+6, 1.010e+6, 1.040e+6, 1.070e+6, 1.100e+6, + 1.108e+6, 1.136e+6, 1.165e+6, 1.200e+6, 1.225e+6, + 1.250e+6, 1.287e+6, 1.317e+6, 1.356e+6, 1.400e+6, + 1.423e+6, 1.461e+6, 1.500e+6, 1.536e+6, 1.572e+6, + 1.612e+6, 1.653e+6, 1.695e+6, 1.738e+6, 1.782e+6, + 1.827e+6, 1.850e+6, 1.921e+6, 1.969e+6, 2.019e+6, + 2.070e+6, 2.123e+6, 2.176e+6, 2.231e+6, 2.307e+6, + 2.354e+6, 2.365e+6, 2.385e+6, 2.466e+6, 2.479e+6, + 2.535e+6, 2.592e+6, 2.658e+6, 2.725e+6, 2.794e+6, + 2.865e+6, 2.932e+6, 3.000e+6, 3.080e+6, 3.166e+6, + 3.247e+6, 3.329e+6, 3.413e+6, 3.499e+6, 3.588e+6, + 3.679e+6, 3.772e+6, 3.867e+6, 3.965e+6, 4.066e+6, + 4.183e+6, 4.304e+6, 4.398e+6, 4.493e+6, 4.607e+6, + 4.724e+6, 4.800e+6, 4.882e+6, 4.966e+6, 5.092e+6, + 5.221e+6, 5.353e+6, 5.488e+6, 5.627e+6, 5.770e+6, + 5.916e+6, 6.065e+6, 6.219e+6, 6.376e+6, 6.434e+6, + 6.592e+6, 6.703e+6, 6.873e+6, 7.047e+6, 7.225e+6, + 7.408e+6, 7.596e+6, 7.788e+6, 7.985e+6, 8.187e+6, + 8.395e+6, 8.607e+6, 8.825e+6, 9.048e+6, 9.278e+6, + 9.512e+6, 9.753e+6, 1.000e+7, 1.025e+7, 1.051e+7, + 1.078e+7, 1.105e+7, 1.133e+7, 1.162e+7, 1.191e+7, + 1.221e+7, 1.252e+7, 1.284e+7, 1.317e+7, 1.350e+7, + 1.384e+7, 1.419e+7, 1.455e+7, 1.492e+7, 1.530e+7, + 1.568e+7, 1.608e+7, 1.649e+7, 1.691e+7, 1.733e+7, + 1.790e+7, 1.845e+7, 1.900e+7, 1.964e+7, 2.000e+7]) GROUP_STRUCTURES['UKAEA-1102'] = np.array([ 1.0000e-5, 1.0471e-5, 1.0965e-5, 1.1482e-5, 1.2023e-5, 1.2589e-5, 1.3183e-5, 1.3804e-5, 1.4454e-5, 1.5136e-5, diff --git a/openmc/mgxs/library.py b/openmc/mgxs/library.py index 12a4630bdc..b476de9020 100644 --- a/openmc/mgxs/library.py +++ b/openmc/mgxs/library.py @@ -10,6 +10,7 @@ import numpy as np import openmc import openmc.mgxs import openmc.checkvalue as cv +from openmc.checkvalue import PathLike from ..tallies import ESTIMATOR_TYPES @@ -555,14 +556,14 @@ class Library: self.all_mgxs[domain.id][mgxs_type] = mgxs - def add_to_tallies_file(self, tallies_file, merge=True): - """Add all tallies from all MGXS objects to a tallies file. + def add_to_tallies(self, tallies, merge=True): + """Add tallies from all MGXS objects to a tallies object. NOTE: This assumes that :meth:`Library.build_library` has been called Parameters ---------- - tallies_file : openmc.Tallies + tallies : openmc.Tallies A Tallies collection to add each MGXS' tallies to generate a 'tallies.xml' input file for OpenMC merge : bool @@ -571,7 +572,7 @@ class Library: """ - cv.check_type('tallies_file', tallies_file, openmc.Tallies) + cv.check_type('tallies', tallies, openmc.Tallies) # Add tallies from each MGXS for each domain and mgxs type for domain in self.domains: @@ -586,7 +587,15 @@ class Library: = list(range(1, self.num_delayed_groups + 1)) for tally in mgxs.tallies.values(): - tallies_file.append(tally, merge=merge) + tallies.append(tally, merge=merge) + + def add_to_tallies_file(self, tallies_file, merge=True): + warn( + "The Library.add_to_tallies_file(...) method has been renamed to" + "add_to_tallies(...) and will be removed in a future version of " + "OpenMC.", FutureWarning + ) + self.add_to_tallies(tallies_file, merge=merge) def load_from_statepoint(self, statepoint): """Extracts tallies in an OpenMC StatePoint with the data needed to @@ -851,7 +860,7 @@ class Library: 'since a statepoint has not yet been loaded' raise ValueError(msg) - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) cv.check_type('directory', directory, str) import h5py @@ -894,7 +903,7 @@ class Library: """ - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) cv.check_type('directory', directory, str) # Make directory if it does not exist @@ -930,7 +939,7 @@ class Library: """ - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) cv.check_type('directory', directory, str) # Make directory if it does not exist diff --git a/openmc/mgxs/mdgxs.py b/openmc/mgxs/mdgxs.py index b95a4fbc0e..c12c1a9abe 100644 --- a/openmc/mgxs/mdgxs.py +++ b/openmc/mgxs/mdgxs.py @@ -7,6 +7,7 @@ import numpy as np import openmc import openmc.checkvalue as cv +from openmc.checkvalue import PathLike from openmc.mgxs import MGXS from .mgxs import _DOMAIN_TO_FILTER @@ -722,7 +723,7 @@ class MDGXS(MGXS): """ - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) cv.check_type('directory', directory, str) cv.check_value('format', format, ['csv', 'excel', 'pickle', 'latex']) cv.check_value('xs_type', xs_type, ['macro', 'micro']) diff --git a/openmc/mgxs/mgxs.py b/openmc/mgxs/mgxs.py index 1bc7f93878..f621db092f 100644 --- a/openmc/mgxs/mgxs.py +++ b/openmc/mgxs/mgxs.py @@ -2,6 +2,7 @@ import copy from numbers import Integral import os import warnings +from textwrap import dedent import h5py import numpy as np @@ -9,6 +10,7 @@ import numpy as np import openmc from openmc.data import REACTION_MT, REACTION_NAME, FISSION_MTS import openmc.checkvalue as cv +from openmc.checkvalue import PathLike from ..tallies import ESTIMATOR_TYPES from . import EnergyGroups @@ -164,7 +166,7 @@ class MGXS: """ - _params = """ + _params = dedent(""" Parameters ---------- domain : openmc.Material or openmc.Cell or openmc.Universe or openmc.RegularMesh @@ -251,7 +253,7 @@ class MGXS: .. versionadded:: 0.13.1 - """ + """) # Store whether or not the number density should be removed for microscopic # values of this data @@ -1981,7 +1983,7 @@ class MGXS: """ - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) cv.check_type('directory', directory, str) cv.check_value('format', format, ['csv', 'excel', 'pickle', 'latex']) cv.check_value('xs_type', xs_type, ['macro', 'micro']) @@ -2125,8 +2127,8 @@ class MGXS: df['std. dev.'] /= np.tile(densities, tile_factor) # Replace NaNs by zeros (happens if nuclide density is zero) - df['mean'].replace(np.nan, 0.0, inplace=True) - df['std. dev.'].replace(np.nan, 0.0, inplace=True) + df['mean'] = df['mean'].replace(np.nan, 0.0) + df['std. dev.'] = df['std. dev.'].replace(np.nan, 0.0) # Sort the dataframe by domain type id (e.g., distribcell id) and # energy groups such that data is from fast to thermal diff --git a/openmc/mgxs_library.py b/openmc/mgxs_library.py index b840563cff..4bc2d4a5a7 100644 --- a/openmc/mgxs_library.py +++ b/openmc/mgxs_library.py @@ -11,7 +11,7 @@ import openmc import openmc.mgxs from openmc.mgxs import SCATTER_TABULAR, SCATTER_LEGENDRE, SCATTER_HISTOGRAM from .checkvalue import check_type, check_value, check_greater_than, \ - check_iterable_type, check_less_than, check_filetype_version + check_iterable_type, check_less_than, check_filetype_version, PathLike ROOM_TEMPERATURE_KELVIN = 294.0 @@ -2506,7 +2506,7 @@ class MGXSLibrary: Parameters ---------- - filename : str + filename : str or PathLike Filename of file, default is mgxs.h5. libver : {'earliest', 'latest'} Compatibility mode for the HDF5 file. 'latest' will produce files @@ -2514,8 +2514,7 @@ class MGXSLibrary: """ - check_type('filename', filename, str) - + check_type('filename', filename, (str, PathLike)) # Create and write to the HDF5 file file = h5py.File(filename, "w", libver=libver) file.attrs['filetype'] = np.bytes_(_FILETYPE_MGXS_LIBRARY) @@ -2554,7 +2553,7 @@ class MGXSLibrary: raise ValueError("Either path or openmc.config['mg_cross_sections']" "must be set") - check_type('filename', filename, str) + check_type('filename', filename, (str, PathLike)) file = h5py.File(filename, 'r') # Check filetype and version diff --git a/openmc/model/funcs.py b/openmc/model/funcs.py index 41aa920eae..e076b080a9 100644 --- a/openmc/model/funcs.py +++ b/openmc/model/funcs.py @@ -39,8 +39,8 @@ def borated_water(boron_ppm, temperature=293., pressure=0.1013, temp_unit='K', press_unit : {'MPa', 'psi'} The units used for the `pressure` argument. density : float - Water density in [g / cm^3]. If specified, this value overrides the - temperature and pressure arguments. + Water density in [g / cm^3]. If specified, this value overrides + the value that is computed from the temperature and pressure arguments. **kwargs All keyword arguments are passed to the created Material object. @@ -95,10 +95,7 @@ def borated_water(boron_ppm, temperature=293., pressure=0.1013, temp_unit='K', frac_B = boron_ppm * 1e-6 / M_B # Build the material. - if density is None: - out = openmc.Material(temperature=T, **kwargs) - else: - out = openmc.Material(**kwargs) + out = openmc.Material(temperature=T, **kwargs) out.add_element('H', frac_H, 'ao') out.add_element('O', frac_O, 'ao') out.add_element('B', frac_B, 'ao') diff --git a/openmc/model/model.py b/openmc/model/model.py index 03fdcda1fc..a9aaa481d5 100644 --- a/openmc/model/model.py +++ b/openmc/model/model.py @@ -1,18 +1,21 @@ from __future__ import annotations -from collections.abc import Iterable, Sequence +from collections.abc import Callable, Iterable, Sequence import copy -from functools import lru_cache +from dataclasses import dataclass, field +from functools import cache from pathlib import Path import math from numbers import Integral, Real import random import re from tempfile import NamedTemporaryFile, TemporaryDirectory +from typing import Any, Protocol import warnings import h5py import lxml.etree as ET import numpy as np +from scipy.optimize import curve_fit import openmc import openmc._xml as xml @@ -24,6 +27,12 @@ from openmc.plots import add_plot_params, _BASIS_INDICES from openmc.utility_funcs import change_directory +# Protocol for a function that is passed to search_keff +class ModelModifier(Protocol): + def __call__(self, val: float, **kwargs: Any) -> None: + ... + + class Model: """Model container. @@ -160,7 +169,7 @@ class Model: return False @property - @lru_cache(maxsize=None) + @cache def _materials_by_id(self) -> dict: """Dictionary mapping material ID --> material""" if self.materials: @@ -170,14 +179,14 @@ class Model: return {mat.id: mat for mat in mats} @property - @lru_cache(maxsize=None) + @cache def _cells_by_id(self) -> dict: """Dictionary mapping cell ID --> cell""" cells = self.geometry.get_all_cells() return {cell.id: cell for cell in cells.values()} @property - @lru_cache(maxsize=None) + @cache def _cells_by_name(self) -> dict[int, openmc.Cell]: # Get the names maps, but since names are not unique, store a set for # each name key. In this way when the user requests a change by a name, @@ -190,7 +199,7 @@ class Model: return result @property - @lru_cache(maxsize=None) + @cache def _materials_by_name(self) -> dict[int, openmc.Material]: if self.materials is None: mats = self.geometry.get_all_materials().values() @@ -203,6 +212,60 @@ class Model: result[mat.name].add(mat) return result + # TODO: This should really get incorporated in lower-level calls to + # get_all_materials, but right now it requires information from the Model object + def _get_all_materials(self) -> dict[int, openmc.Material]: + """Get all materials including those in DAGMC universes + + Returns + ------- + dict + Dictionary mapping material ID to material instances + """ + # Get all materials from the Geometry object + materials = self.geometry.get_all_materials() + + # Account for materials in DAGMC universes + for cell in self.geometry.get_all_cells().values(): + if isinstance(cell.fill, openmc.DAGMCUniverse): + names = cell.fill.material_names + materials.update({ + mat.id: mat for mat in self.materials if mat.name in names + }) + + return materials + + def add_kinetics_parameters_tallies(self, num_groups: int | None = None): + """Add tallies for calculating kinetics parameters using the IFP method. + + This method adds tallies to the model for calculating two kinetics + parameters, the generation time and the effective delayed neutron + fraction (beta effective). After a model is run, these parameters can be + determined through the :meth:`openmc.StatePoint.ifp_results` method. + + Parameters + ---------- + num_groups : int, optional + Number of precursor groups to filter the delayed neutron fraction. + If None, only the total effective delayed neutron fraction is + tallied. + + """ + if not any('ifp-time-numerator' in t.scores for t in self.tallies): + gen_time_tally = openmc.Tally(name='IFP time numerator') + gen_time_tally.scores = ['ifp-time-numerator'] + self.tallies.append(gen_time_tally) + if not any('ifp-beta-numerator' in t.scores for t in self.tallies): + beta_tally = openmc.Tally(name='IFP beta numerator') + beta_tally.scores = ['ifp-beta-numerator'] + if num_groups is not None: + beta_tally.filters = [openmc.DelayedGroupFilter(list(range(1, num_groups + 1)))] + self.tallies.append(beta_tally) + if not any('ifp-denominator' in t.scores for t in self.tallies): + denom_tally = openmc.Tally(name='IFP denominator') + denom_tally.scores = ['ifp-denominator'] + self.tallies.append(denom_tally) + @classmethod def from_xml( cls, @@ -483,6 +546,13 @@ class Model: depletion_operator.cleanup_when_done = True depletion_operator.finalize() + def _link_geometry_to_filters(self): + """Establishes a link between distribcell filters and the geometry""" + for tally in self.tallies: + for f in tally.filters: + if isinstance(f, openmc.DistribcellFilter): + f._geometry = self.geometry + def export_to_xml(self, directory: PathLike = '.', remove_surfs: bool = False, nuclides_to_ignore: Iterable[str] | None = None): """Export model to separate XML files. @@ -524,6 +594,8 @@ class Model: if self.plots: self.plots.export_to_xml(d) + self._link_geometry_to_filters() + def export_to_model_xml(self, path: PathLike = 'model.xml', remove_surfs: bool = False, nuclides_to_ignore: Iterable[str] | None = None): """Export model to a single XML file. @@ -603,6 +675,8 @@ class Model: fh.write(ET.tostring(plots_element, encoding="unicode")) fh.write("\n") + self._link_geometry_to_filters() + def import_properties(self, filename: PathLike): """Import physical properties @@ -633,7 +707,7 @@ class Model: raise ValueError("Number of cells in properties file doesn't " "match current model.") - # Update temperatures for cells filled with materials + # Update temperatures and densities for cells filled with materials for name, group in cells_group.items(): cell_id = int(name.split()[1]) cell = cells[cell_id] @@ -648,6 +722,20 @@ class Model: else: lib_cell.set_temperature(temperature[0]) + if group['density']: + density = group['density'][()] + if density.size > 1: + cell.density = [rho for rho in density] + else: + cell.density = density + if self.is_initialized: + lib_cell = openmc.lib.cells[cell_id] + if density.size > 1: + for i, rho in enumerate(density): + lib_cell.set_density(rho, i) + else: + lib_cell.set_density(density[0]) + # Make sure number of materials matches mats_group = fh['materials'] n_cells = mats_group.attrs['n_materials'] @@ -949,6 +1037,7 @@ class Model: width: Sequence[float] | None = None, pixels: int | Sequence[int] = 40000, basis: str = 'xy', + color_overlaps: bool = False, **init_kwargs ) -> np.ndarray: """Generate an ID map for domains based on the plot parameters @@ -977,6 +1066,10 @@ class Model: total and the image aspect ratio based on the width argument. basis : {'xy', 'yz', 'xz'}, optional Basis of the plot. + color_overlaps : bool, optional + Whether to assign unique IDs (-3) to overlapping regions. If False, + overlapping regions will be assigned the ID of the lowest-numbered + cell that occupies that region. Defaults to False. **init_kwargs Keyword arguments passed to :meth:`Model.init_lib`. @@ -1001,6 +1094,7 @@ class Model: plot_obj.h_res = pixels[0] plot_obj.v_res = pixels[1] plot_obj.basis = basis + plot_obj.color_overlaps = color_overlaps # Silence output by default. Also set arguments to start in volume # calculation mode to avoid loading cross sections @@ -1082,7 +1176,7 @@ class Model: self.settings.plot_seed = seed # Create plot object matching passed arguments - plot = openmc.Plot() + plot = openmc.SlicePlot() plot.origin = origin plot.width = width plot.pixels = pixels @@ -1199,8 +1293,8 @@ class Model: tol = plane_tolerance for particle in particles: if (slice_value - tol < particle.r[z] < slice_value + tol): - xs.append(particle.r[x]) - ys.append(particle.r[y]) + xs.append(particle.r[x] * axis_scaling_factor[axis_units]) + ys.append(particle.r[y] * axis_scaling_factor[axis_units]) axes.scatter(xs, ys, **source_kwargs) return axes @@ -1610,6 +1704,91 @@ class Model: self.geometry.get_all_materials().values() ) + def _create_mgxs_sources( + self, + groups: openmc.mgxs.EnergyGroups, + spatial_dist: openmc.stats.Spatial, + source_energy: openmc.stats.Univariate | None = None, + ) -> list[openmc.IndependentSource]: + """Create a list of independent sources to use with MGXS generation. + + Note that in all cases, a discrete source that is uniform over all + energy groups is created (strength = 0.01) to ensure that total cross + sections are generated for all energy groups. In the case that the user + has provided a source_energy distribution as an argument, an additional + source (strength = 0.99) is created using that energy distribution. If + the user has not provided a source_energy distribution, but the model + has sources defined, and all of those sources are of IndependentSource + type, then additional sources are created based on the model's existing + sources, keeping their energy distributions but replacing their + spatial/angular distributions, with their combined strength being 0.99. + If the user has not provided a source_energy distribution and no sources + are defined on the model and the run mode is 'eigenvalue', then a + default Watt spectrum source (strength = 0.99) is added. + + Parameters + ---------- + groups : openmc.mgxs.EnergyGroups + Energy group structure for the MGXS. + spatial_dist : openmc.stats.Spatial + Spatial distribution to use for all sources. + source_energy : openmc.stats.Univariate, optional + Energy distribution to use when generating MGXS data, replacing any + existing sources in the model. + + Returns + ------- + list[openmc.IndependentSource] + A list of independent sources to use for MGXS generation. + """ + # Make a discrete source that is uniform over the bins of the group structure + midpoints = [] + strengths = [] + for i in range(groups.num_groups): + bounds = groups.get_group_bounds(i+1) + midpoints.append((bounds[0] + bounds[1]) / 2.0) + strengths.append(1.0) + + uniform_energy = openmc.stats.Discrete(x=midpoints, p=strengths) + uniform_distribution = openmc.IndependentSource(spatial_dist, energy=uniform_energy, strength=0.01) + sources = [uniform_distribution] + + # If the user provided an energy distribution, use that + if source_energy is not None: + user_energy = openmc.IndependentSource( + space=spatial_dist, energy=source_energy, strength=0.99) + sources.append(user_energy) + + # If the user did not provide an energy distribution, create sources + # based on what is in their model, keeping the energy spectrum but + # replacing the spatial/angular distributions. We only do this if ALL + # sources are of IndependentSource type, as we can't pull the energy + # distribution from e.g. CompiledSource or FileSource types. + else: + if self.settings.source is not None: + for src in self.settings.source: + if not isinstance(src, openmc.IndependentSource): + break + else: + n_user_sources = len(self.settings.source) + for src in self.settings.source: + # Create a new IndependentSource with adjusted strength, space, and angle + user_source = openmc.IndependentSource( + space=spatial_dist, + energy=src.energy, + strength=0.99 / n_user_sources + ) + sources.append(user_source) + else: + # No user sources defined. If we are in eigenvalue mode, then use the default Watt spectrum. + if self.settings.run_mode == 'eigenvalue': + watt_energy = openmc.stats.Watt() + watt_source = openmc.IndependentSource( + space=spatial_dist, energy=watt_energy, strength=0.99) + sources.append(watt_source) + + return sources + def _generate_infinite_medium_mgxs( self, groups: openmc.mgxs.EnergyGroups, @@ -1617,6 +1796,7 @@ class Model: mgxs_path: PathLike, correction: str | None, directory: PathLike, + source_energy: openmc.stats.Univariate | None = None, ): """Generate a MGXS library by running multiple OpenMC simulations, each representing an infinite medium simulation of a single isolated @@ -1625,6 +1805,20 @@ class Model: method that ignores all spatial self shielding effects and all resonance shielding effects between materials. + Note that in all cases, a discrete source that is uniform over all + energy groups is created (strength = 0.01) to ensure that total cross + sections are generated for all energy groups. In the case that the user + has provided a source_energy distribution as an argument, an additional + source (strength = 0.99) is created using that energy distribution. If + the user has not provided a source_energy distribution, but the model + has sources defined, and all of those sources are of IndependentSource + type, then additional sources are created based on the model's existing + sources, keeping their energy distributions but replacing their + spatial/angular distributions, with their combined strength being 0.99. + If the user has not provided a source_energy distribution and no sources + are defined on the model and the run mode is 'eigenvalue', then a + default Watt spectrum source (strength = 0.99) is added. + Parameters ---------- groups : openmc.mgxs.EnergyGroups @@ -1638,9 +1832,10 @@ class Model: "P0". directory : str Directory to run the simulation in, so as to contain XML files. + source_energy : openmc.stats.Univariate, optional + Energy distribution to use when generating MGXS data, replacing any + existing sources in the model. """ - warnings.warn("The infinite medium method of generating MGXS may hang " - "if a material has a k-infinity > 1.0.") mgxs_sets = [] for material in self.materials: model = openmc.Model() @@ -1651,20 +1846,16 @@ class Model: # Settings model.settings.batches = 100 model.settings.particles = nparticles + + model.settings.source = self._create_mgxs_sources( + groups, + spatial_dist=openmc.stats.Point(), + source_energy=source_energy + ) + model.settings.run_mode = 'fixed source' + model.settings.create_fission_neutrons = False - # Make a discrete source that is uniform over the bins of the group structure - n_groups = groups.num_groups - midpoints = [] - strengths = [] - for i in range(n_groups): - bounds = groups.get_group_bounds(i+1) - midpoints.append((bounds[0] + bounds[1]) / 2.0) - strengths.append(1.0) - - energy_distribution = openmc.stats.Discrete(x=midpoints, p=strengths) - model.settings.source = openmc.IndependentSource( - space=openmc.stats.Point(), energy=energy_distribution) model.settings.output = {'summary': True, 'tallies': False} # Geometry @@ -1714,7 +1905,7 @@ class Model: mgxs_lib.build_library() # Create a "tallies.xml" file for the MGXS Library - mgxs_lib.add_to_tallies_file(model.tallies, merge=True) + mgxs_lib.add_to_tallies(model.tallies, merge=True) # Run statepoint_filename = model.run(cwd=directory) @@ -1814,6 +2005,7 @@ class Model: mgxs_path: PathLike, correction: str | None, directory: PathLike, + source_energy: openmc.stats.Univariate | None = None, ) -> None: """Generate MGXS assuming a stochastic "sandwich" of materials in a layered slab geometry. While geometry-specific spatial shielding effects are not @@ -1838,6 +2030,23 @@ class Model: "P0". directory : str Directory to run the simulation in, so as to contain XML files. + source_energy : openmc.stats.Univariate, optional + Energy distribution to use when generating MGXS data, replacing any + existing sources in the model. In all cases, a discrete source that + is uniform over all energy groups is created (strength = 0.01) to + ensure that total cross sections are generated for all energy + groups. In the case that the user has provided a source_energy + distribution as an argument, an additional source (strength = 0.99) + is created using that energy distribution. If the user has not + provided a source_energy distribution, but the model has sources + defined, and all of those sources are of IndependentSource type, + then additional sources are created based on the model's existing + sources, keeping their energy distributions but replacing their + spatial/angular distributions, with their combined strength being + 0.99. If the user has not provided a source_energy distribution and + no sources are defined on the model and the run mode is + 'eigenvalue', then a default Watt spectrum source (strength = 0.99) + is added. """ model = openmc.Model() model.materials = self.materials @@ -1847,24 +2056,20 @@ class Model: model.settings.inactive = 100 model.settings.particles = nparticles model.settings.output = {'summary': True, 'tallies': False} - model.settings.run_mode = self.settings.run_mode # Stochastic slab geometry model.geometry, spatial_distribution = Model._create_stochastic_slab_geometry( model.materials) - # Make a discrete source that is uniform over the bins of the group structure - n_groups = groups.num_groups - midpoints = [] - strengths = [] - for i in range(n_groups): - bounds = groups.get_group_bounds(i+1) - midpoints.append((bounds[0] + bounds[1]) / 2.0) - strengths.append(1.0) + # Define the sources + model.settings.source = self._create_mgxs_sources( + groups, + spatial_dist=spatial_distribution, + source_energy=source_energy + ) - energy_distribution = openmc.stats.Discrete(x=midpoints, p=strengths) - model.settings.source = [openmc.IndependentSource( - space=spatial_distribution, energy=energy_distribution, strength=1.0)] + model.settings.run_mode = 'fixed source' + model.settings.create_fission_neutrons = False model.settings.output = {'summary': True, 'tallies': False} @@ -1903,7 +2108,7 @@ class Model: mgxs_lib.build_library() # Create a "tallies.xml" file for the MGXS Library - mgxs_lib.add_to_tallies_file(model.tallies, merge=True) + mgxs_lib.add_to_tallies(model.tallies, merge=True) # Run statepoint_filename = model.run(cwd=directory) @@ -1998,7 +2203,7 @@ class Model: mgxs_lib.build_library() # Create a "tallies.xml" file for the MGXS Library - mgxs_lib.add_to_tallies_file(model.tallies, merge=True) + mgxs_lib.add_to_tallies(model.tallies, merge=True) # Run statepoint_filename = model.run(cwd=directory) @@ -2022,6 +2227,7 @@ class Model: overwrite_mgxs_library: bool = False, mgxs_path: PathLike = "mgxs.h5", correction: str | None = None, + source_energy: openmc.stats.Univariate | None = None, ): """Convert all materials from continuous energy to multigroup. @@ -2035,11 +2241,33 @@ class Model: groups : openmc.mgxs.EnergyGroups or str, optional Energy group structure for the MGXS or the name of the group structure (based on keys from openmc.mgxs.GROUP_STRUCTURES). + nparticles : int, optional + Number of particles to simulate per batch when generating MGXS. + overwrite_mgxs_library : bool, optional + Whether to overwrite an existing MGXS library file. mgxs_path : str, optional - Filename of the mgxs.h5 library file. + Path to the mgxs.h5 library file. correction : str, optional Transport correction to apply to the MGXS. Options are None and "P0". + source_energy : openmc.stats.Univariate, optional + Energy distribution to use when generating MGXS data, replacing any + existing sources in the model. In all cases, a discrete source that + is uniform over all energy groups is created (strength = 0.01) to + ensure that total cross sections are generated for all energy + groups. In the case that the user has provided a source_energy + distribution as an argument, an additional source (strength = 0.99) + is created using that energy distribution. If the user has not + provided a source_energy distribution, but the model has sources + defined, and all of those sources are of IndependentSource type, + then additional sources are created based on the model's existing + sources, keeping their energy distributions but replacing their + spatial/angular distributions, with their combined strength being + 0.99. If the user has not provided a source_energy distribution and + no sources are defined on the model and the run mode is + 'eigenvalue', then a default Watt spectrum source (strength = 0.99) + is added. Note that this argument is only used when using the + "stochastic_slab" or "infinite_medium" MGXS generation methods. """ if isinstance(groups, str): groups = openmc.mgxs.EnergyGroups(groups) @@ -2069,13 +2297,13 @@ class Model: if not Path(mgxs_path).is_file() or overwrite_mgxs_library: if method == "infinite_medium": self._generate_infinite_medium_mgxs( - groups, nparticles, mgxs_path, correction, tmpdir) + groups, nparticles, mgxs_path, correction, tmpdir, source_energy) elif method == "material_wise": self._generate_material_wise_mgxs( groups, nparticles, mgxs_path, correction, tmpdir) elif method == "stochastic_slab": self._generate_stochastic_slab_mgxs( - groups, nparticles, mgxs_path, correction, tmpdir) + groups, nparticles, mgxs_path, correction, tmpdir, source_energy) else: raise ValueError( f'MGXS generation method "{method}" not recognized') @@ -2151,3 +2379,262 @@ class Model: # Take a wild guess as to how many rays are needed self.settings.particles = 2 * int(max_length) + + def keff_search( + self, + func: ModelModifier, + x0: float, + x1: float, + target: float = 1.0, + k_tol: float = 1e-4, + sigma_final: float = 3e-4, + p: float = 0.5, + q: float = 0.95, + memory: int = 4, + x_min: float | None = None, + x_max: float | None = None, + b0: int | None = None, + b_min: int = 20, + b_max: int | None = None, + maxiter: int = 50, + output: bool = False, + func_kwargs: dict[str, Any] | None = None, + run_kwargs: dict[str, Any] | None = None, + ) -> SearchResult: + r"""Perform a keff search on a model parametrized by a single variable. + + This method uses the GRsecant method described in a paper by `Price and + Roskoff `_. The GRsecant + method is a modification of the secant method that accounts for + uncertainties in the function evaluations. The method uses a weighted + linear fit of the most recent function evaluations to predict the next + point to evaluate. It also adaptively changes the number of batches to + meet the target uncertainty value at each iteration. + + The target uncertainty for iteration :math:`n+1` is determined by the + following equation (following Eq. (8) in the paper): + + .. math:: + \sigma_{i+1} = q \sigma_\text{final} \left ( \frac{ \min \left \{ + \left\lvert k_i - k_\text{target} \right\rvert : k=0,1,\dots,n + \right \} }{k_\text{tol}} \right )^p + + where :math:`q` is a multiplicative factor less than 1, given as the + ``sigma_factor`` parameter below. + + Parameters + ---------- + func : ModelModifier + Function that takes the parameter to be searched and makes a + modification to the model. + x0 : float + First guess for the parameter passed to `func` + x1 : float + Second guess for the parameter passed to `func` + target : float, optional + keff value to search for + k_tol : float, optional + Stopping criterion on the function value; the absolute value must be + within ``k_tol`` of zero to be accepted. + sigma_final : float, optional + Maximum accepted k-effective uncertainty for the stopping criterion. + p : float, optional + Exponent used in the stopping criterion. + q : float, optional + Multiplicative factor used in the stopping criterion. + memory : int, optional + Number of most-recent points used in the weighted linear fit of + ``f(x) = a + b x`` to predict the next point. + x_min : float, optional + Minimum allowed value for the parameter ``x``. + x_max : float, optional + Maximum allowed value for the parameter ``x``. + b0 : int, optional + Number of active batches to use for the initial function + evaluations. If None, uses the model's current setting. + b_min : int, optional + Minimum number of active batches to use in a function evaluation. + b_max : int, optional + Maximum number of active batches to use in a function evaluation. + maxiter : int, optional + Maximum number of iterations to perform. + output : bool, optional + Whether or not to display output showing iteration progress. + func_kwargs : dict, optional + Keyword-based arguments to pass to the `func` function. + run_kwargs : dict, optional + Keyword arguments to pass to :meth:`openmc.Model.run` or + :meth:`openmc.lib.run`. + + Returns + ------- + SearchResult + Result object containing the estimated root (parameter value) and + evaluation history (parameters, means, standard deviations, and + batches), plus convergence status and termination reason. + + """ + import openmc.lib + + check_type('model modifier', func, Callable) + check_type('target', target, Real) + if memory < 2: + raise ValueError("memory must be ≥ 2") + func_kwargs = {} if func_kwargs is None else dict(func_kwargs) + run_kwargs = {} if run_kwargs is None else dict(run_kwargs) + run_kwargs.setdefault('output', False) + + # Create lists to store the history of evaluations + xs: list[float] = [] + fs: list[float] = [] + ss: list[float] = [] + gs: list[int] = [] + count = 0 + + # Helper function to evaluate f and store results + def eval_at(x: float, batches: int) -> tuple[float, float]: + # Modify the model with the current guess + func(x, **func_kwargs) + + # Change the number of batches and run the model + batches += self.settings.inactive + if openmc.lib.is_initialized: + openmc.lib.settings.set_batches(batches) + openmc.lib.reset() + openmc.lib.run(**run_kwargs) + sp_filepath = f'statepoint.{batches}.h5' + else: + self.settings.batches = batches + sp_filepath = self.run(**run_kwargs) + + # Extract keff and its uncertainty + with openmc.StatePoint(sp_filepath) as sp: + keff = sp.keff + + if output: + nonlocal count + count += 1 + print(f'Iteration {count}: {batches=}, {x=:.6g}, {keff=:.5f}') + + xs.append(float(x)) + fs.append(float(keff.n - target)) + ss.append(float(keff.s)) + gs.append(int(batches)) + return fs[-1], ss[-1] + + # Default b0 to current model settings if not explicitly provided + if b0 is None: + b0 = self.settings.batches - self.settings.inactive + + # Perform the search (inlined GRsecant) in a temporary directory + with TemporaryDirectory() as tmpdir: + if not openmc.lib.is_initialized: + run_kwargs.setdefault('cwd', tmpdir) + + # ---- Seed with two evaluations + f0, s0 = eval_at(x0, b0) + if abs(f0) <= k_tol and s0 <= sigma_final: + return SearchResult(x0, xs, fs, ss, gs, True, "converged") + f1, s1 = eval_at(x1, b0) + if abs(f1) <= k_tol and s1 <= sigma_final: + return SearchResult(x1, xs, fs, ss, gs, True, "converged") + + for _ in range(maxiter - 2): + # ------ Step 1: propose next x via GRsecant + m = min(memory, len(xs)) + + # Perform a curve fit on f(x) = a + bx accounting for + # uncertainties. This is equivalent to minimizing the function + # in Equation (A.14) + (a, b), _ = curve_fit( + lambda x, a, b: a + b*x, + xs[-m:], fs[-m:], sigma=ss[-m:], absolute_sigma=True + ) + x_new = float(-a / b) + + # Clamp x_new to the bounds if provided + if x_min is not None: + x_new = max(x_new, x_min) + if x_max is not None: + x_new = min(x_new, x_max) + + # ------ Step 2: choose target σ for next run (Eq. 8 + clamp) + + min_abs_f = float(np.min(np.abs(fs))) + base = q * sigma_final + ratio = min_abs_f / k_tol if k_tol > 0 else 1.0 + sig = base * (ratio ** p) + sig_target = max(sig, base) + + # ------ Step 3: choose generations to hit σ_target (Appendix C) + + # Use at least two past points for regression + if len(gs) >= 2 and np.var(np.log(gs)) > 0.0: + # Perform a curve fit based on Eq. (C.3) to solve for ln(k). + # Note that unlike in the paper, we do not leave r as an + # undetermined parameter and choose r=0.5. + (ln_k,), _ = curve_fit( + lambda ln_b, ln_k: ln_k - 0.5*ln_b, + np.log(gs[-4:]), np.log(ss[-4:]), + ) + k = float(np.exp(ln_k)) + else: + k = float(ss[-1] * math.sqrt(gs[-1])) + + b_new = (k / sig_target) ** 2 + + # Clamp and round up to integer + b_new = max(b_min, math.ceil(b_new)) + if b_max is not None: + b_new = min(b_new, b_max) + + # Evaluate at proposed x with batches determined above + f_new, s_new = eval_at(x_new, b_new) + + # Termination based on both criteria (|f| and σ) + if abs(f_new) <= k_tol and s_new <= sigma_final: + return SearchResult(x_new, xs, fs, ss, gs, True, "converged") + + return SearchResult(xs[-1], xs, fs, ss, gs, False, "maxiter") + + +@dataclass +class SearchResult: + """Result of a GRsecant keff search. + + Attributes + ---------- + root : float + Estimated parameter value where f(x) = 0 at termination. + parameters : list[float] + Parameter values (x) evaluated during the search, in order. + keffs : list[float] + Estimated keff values for each evaluation. + stdevs : list[float] + One-sigma uncertainties of keff for each evaluation. + batches : list[int] + Number of active batches used for each evaluation. + converged : bool + Whether both |f| <= k_tol and sigma <= sigma_final were met. + flag : str + Reason for termination (e.g., "converged", "maxiter"). + """ + root: float + parameters: list[float] = field(repr=False) + means: list[float] = field(repr=False) + stdevs: list[float] = field(repr=False) + batches: list[int] = field(repr=False) + converged: bool + flag: str + + @property + def function_calls(self) -> int: + """Number of function evaluations performed.""" + return len(self.parameters) + + @property + def total_batches(self) -> int: + """Total number of active batches used across all evaluations.""" + return sum(self.batches) + + diff --git a/openmc/plots.py b/openmc/plots.py index 072a9a319e..cb722abc6e 100644 --- a/openmc/plots.py +++ b/openmc/plots.py @@ -1,6 +1,8 @@ from collections.abc import Iterable, Mapping from numbers import Integral, Real from pathlib import Path +from textwrap import dedent +import warnings import h5py import lxml.etree as ET @@ -167,7 +169,8 @@ _SVG_COLORS = { 'yellowgreen': (154, 205, 50) } -_PLOT_PARAMS = """ +_PLOT_PARAMS = dedent("""\ + Parameters ---------- origin : iterable of float @@ -249,7 +252,7 @@ _PLOT_PARAMS = """ ------- matplotlib.axes.Axes Axes containing resulting image -""" +""") # Decorator for consistently adding plot parameters to docstrings (Model.plot, @@ -437,7 +440,7 @@ class PlotBase(IDManagerMixin): @filename.setter def filename(self, filename): - cv.check_type('filename', filename, str) + cv.check_type('filename', filename, (str, PathLike)) self._filename = filename @property @@ -624,14 +627,15 @@ class PlotBase(IDManagerMixin): return element -class Plot(PlotBase): - """Definition of a finite region of space to be plotted. +class SlicePlot(PlotBase): + """Definition of a 2D slice plot of the geometry. - OpenMC is capable of generating two-dimensional slice plots, or - three-dimensional voxel or projection plots. Colors that are used in plots can be given as - RGB tuples, e.g. (255, 255, 255) would be white, or by a string indicating a + Colors that are used in plots can be given as RGB tuples, e.g. + (255, 255, 255) would be white, or by a string indicating a valid `SVG color `_. + .. versionadded:: 0.15.4 + Parameters ---------- plot_id : int @@ -646,7 +650,7 @@ class Plot(PlotBase): name : str Name of the plot pixels : Iterable of int - Number of pixels to use in each direction + Number of pixels to use in each direction (2 values) filename : str Path to write the plot to color_by : {'cell', 'material'} @@ -669,11 +673,9 @@ class Plot(PlotBase): level : int Universe depth to plot at width : Iterable of float - Width of the plot in each basis direction + Width of the plot in each basis direction (2 values) origin : tuple or list of ndarray - Origin (center) of the plot - type : {'slice', 'voxel'} - The type of the plot + Origin (center) of the plot (3 values) basis : {'xy', 'xz', 'yz'} The basis directions for the plot meshlines : dict @@ -686,10 +688,37 @@ class Plot(PlotBase): super().__init__(plot_id, name) self._width = [4.0, 4.0] self._origin = [0., 0., 0.] - self._type = 'slice' self._basis = 'xy' self._meshlines = None + @property + def type(self): + warnings.warn( + "The 'type' attribute is deprecated and will be removed in a future version. " + "This is a SlicePlot instance.", + FutureWarning, stacklevel=2 + ) + return 'slice' + + @type.setter + def type(self, value): + raise TypeError( + "Setting plot.type is no longer supported. " + "Use openmc.SlicePlot() for 2D slice plots or openmc.VoxelPlot() for 3D voxel plots." + ) + + @property + def pixels(self): + return self._pixels + + @pixels.setter + def pixels(self, pixels): + cv.check_type('plot pixels', pixels, Iterable, Integral) + cv.check_length('plot pixels', pixels, 2, 2) + for dim in pixels: + cv.check_greater_than('plot pixels', dim, 0) + self._pixels = pixels + @property def width(self): return self._width @@ -697,7 +726,7 @@ class Plot(PlotBase): @width.setter def width(self, width): cv.check_type('plot width', width, Iterable, Real) - cv.check_length('plot width', width, 2, 3) + cv.check_length('plot width', width, 2, 2) self._width = width @property @@ -710,15 +739,6 @@ class Plot(PlotBase): cv.check_length('plot origin', origin, 3) self._origin = origin - @property - def type(self): - return self._type - - @type.setter - def type(self, plottype): - cv.check_value('plot type', plottype, ['slice', 'voxel']) - self._type = plottype - @property def basis(self): return self._basis @@ -761,11 +781,10 @@ class Plot(PlotBase): self._meshlines = meshlines def __repr__(self): - string = 'Plot\n' + string = 'SlicePlot\n' string += '{: <16}=\t{}\n'.format('\tID', self._id) string += '{: <16}=\t{}\n'.format('\tName', self._name) string += '{: <16}=\t{}\n'.format('\tFilename', self._filename) - string += '{: <16}=\t{}\n'.format('\tType', self._type) string += '{: <16}=\t{}\n'.format('\tBasis', self._basis) string += '{: <16}=\t{}\n'.format('\tWidth', self._width) string += '{: <16}=\t{}\n'.format('\tOrigin', self._origin) @@ -881,7 +900,7 @@ class Plot(PlotBase): self._colors[domain] = (r, g, b) def to_xml_element(self): - """Return XML representation of the slice/voxel plot + """Return XML representation of the slice plot Returns ------- @@ -891,10 +910,8 @@ class Plot(PlotBase): """ element = super().to_xml_element() - element.set("type", self._type) - - if self._type == 'slice': - element.set("basis", self._basis) + element.set("type", "slice") + element.set("basis", self._basis) subelement = ET.SubElement(element, "origin") subelement.text = ' '.join(map(str, self._origin)) @@ -940,8 +957,8 @@ class Plot(PlotBase): Returns ------- - openmc.Plot - Plot object + openmc.SlicePlot + SlicePlot object """ plot_id = int(get_text(elem, "id")) @@ -950,9 +967,7 @@ class Plot(PlotBase): if "filename" in elem.keys(): plot.filename = get_text(elem, "filename") plot.color_by = get_text(elem, "color_by") - plot.type = get_text(elem, "type") - if plot.type == 'slice': - plot.basis = get_text(elem, "basis") + plot.basis = get_text(elem, "basis") plot.origin = tuple(get_elem_list(elem, "origin", float)) plot.width = tuple(get_elem_list(elem, "width", float)) @@ -1034,9 +1049,215 @@ class Plot(PlotBase): # Return produced image return _get_plot_image(self, cwd) + + +class VoxelPlot(PlotBase): + """Definition of a 3D voxel plot of the geometry. + + Colors that are used in plots can be given as RGB tuples, e.g. + (255, 255, 255) would be white, or by a string indicating a + valid `SVG color `_. + + .. versionadded:: 0.15.1 + + Parameters + ---------- + plot_id : int + Unique identifier for the plot + name : str + Name of the plot + + Attributes + ---------- + id : int + Unique identifier + name : str + Name of the plot + pixels : Iterable of int + Number of pixels to use in each direction (3 values) + filename : str + Path to write the plot to + color_by : {'cell', 'material'} + Indicate whether the plot should be colored by cell or by material + background : Iterable of int or str + Color of the background + mask_components : Iterable of openmc.Cell or openmc.Material or int + The cells or materials (or corresponding IDs) to mask + mask_background : Iterable of int or str + Color to apply to all cells/materials listed in mask_components + show_overlaps : bool + Indicate whether or not overlapping regions are shown + overlap_color : Iterable of int or str + Color to apply to overlapping regions + colors : dict + Dictionary indicating that certain cells/materials should be + displayed with a particular color. The keys can be of type + :class:`~openmc.Cell`, :class:`~openmc.Material`, or int (ID for a + cell/material). + level : int + Universe depth to plot at + width : Iterable of float + Width of the plot in each dimension (3 values) + origin : tuple or list of ndarray + Origin (center) of the plot (3 values) + + """ + + def __init__(self, plot_id=None, name=''): + super().__init__(plot_id, name) + self._width = [4.0, 4.0, 4.0] + self._origin = [0., 0., 0.] + self._pixels = [400, 400, 400] + + @property + def pixels(self): + return self._pixels + + @pixels.setter + def pixels(self, pixels): + cv.check_type('plot pixels', pixels, Iterable, Integral) + cv.check_length('plot pixels', pixels, 3, 3) + for dim in pixels: + cv.check_greater_than('plot pixels', dim, 0) + self._pixels = pixels + + @property + def width(self): + return self._width + + @width.setter + def width(self, width): + cv.check_type('plot width', width, Iterable, Real) + cv.check_length('plot width', width, 3, 3) + self._width = width + + @property + def origin(self): + return self._origin + + @origin.setter + def origin(self, origin): + cv.check_type('plot origin', origin, Iterable, Real) + cv.check_length('plot origin', origin, 3) + self._origin = origin + + def __repr__(self): + string = 'VoxelPlot\n' + string += '{: <16}=\t{}\n'.format('\tID', self._id) + string += '{: <16}=\t{}\n'.format('\tName', self._name) + string += '{: <16}=\t{}\n'.format('\tFilename', self._filename) + string += '{: <16}=\t{}\n'.format('\tWidth', self._width) + string += '{: <16}=\t{}\n'.format('\tOrigin', self._origin) + string += '{: <16}=\t{}\n'.format('\tPixels', self._pixels) + string += '{: <16}=\t{}\n'.format('\tColor by', self._color_by) + string += '{: <16}=\t{}\n'.format('\tBackground', self._background) + string += '{: <16}=\t{}\n'.format('\tMask components', + self._mask_components) + string += '{: <16}=\t{}\n'.format('\tMask background', + self._mask_background) + string += '{: <16}=\t{}\n'.format('\tOverlap Color', + self._overlap_color) + string += '{: <16}=\t{}\n'.format('\tColors', self._colors) + string += '{: <16}=\t{}\n'.format('\tLevel', self._level) + return string + + def to_xml_element(self): + """Return XML representation of the voxel plot + + Returns + ------- + element : lxml.etree._Element + XML element containing plot data + + """ + + element = super().to_xml_element() + element.set("type", "voxel") + + subelement = ET.SubElement(element, "origin") + subelement.text = ' '.join(map(str, self._origin)) + + subelement = ET.SubElement(element, "width") + subelement.text = ' '.join(map(str, self._width)) + + if self._colors: + self._colors_to_xml(element) + + if self._show_overlaps: + subelement = ET.SubElement(element, "show_overlaps") + subelement.text = "true" + + if self._overlap_color is not None: + color = self._overlap_color + if isinstance(color, str): + color = _SVG_COLORS[color.lower()] + subelement = ET.SubElement(element, "overlap_color") + subelement.text = ' '.join(str(x) for x in color) + + return element + + @classmethod + def from_xml_element(cls, elem): + """Generate plot object from an XML element + + Parameters + ---------- + elem : lxml.etree._Element + XML element + + Returns + ------- + openmc.VoxelPlot + VoxelPlot object + + """ + plot_id = int(get_text(elem, "id")) + name = get_text(elem, 'name', '') + plot = cls(plot_id, name) + if "filename" in elem.keys(): + plot.filename = get_text(elem, "filename") + plot.color_by = get_text(elem, "color_by") + + plot.origin = tuple(get_elem_list(elem, "origin", float)) + plot.width = tuple(get_elem_list(elem, "width", float)) + plot.pixels = tuple(get_elem_list(elem, "pixels")) + background = get_elem_list(elem, "background") + if background is not None: + plot._background = tuple(background) + + # Set plot colors + colors = {} + for color_elem in elem.findall("color"): + uid = int(get_text(color_elem, "id")) + colors[uid] = tuple(get_elem_list(color_elem, "rgb", int)) + plot.colors = colors + + # Set masking information + mask_elem = elem.find("mask") + if mask_elem is not None: + plot.mask_components = get_elem_list(mask_elem, "components", int) + background = get_elem_list(mask_elem, "background", int) + if background is not None: + plot.mask_background = tuple(background) + + # show overlaps + overlap = get_text(elem, "show_overlaps") + if overlap is not None: + plot.show_overlaps = (overlap in ('true', '1')) + overlap_color = get_elem_list(elem, "overlap_color", int) + if overlap_color is not None: + plot.overlap_color = tuple(overlap_color) + + # Set universe level + level = get_text(elem, "level") + if level is not None: + plot.level = int(level) + + return plot + def to_vtk(self, output: PathLike | None = None, openmc_exec: str = 'openmc', cwd: str = '.'): - """Render plot as an voxel image + """Render plot as a voxel image This method runs OpenMC in plotting mode to produce a .vti file. @@ -1057,10 +1278,6 @@ class Plot(PlotBase): Path of the .vti file produced """ - if self.type != 'voxel': - raise ValueError( - 'Generating a VTK file only works for voxel plots') - # Create plots.xml Plots([self]).export_to_xml(cwd) @@ -1080,6 +1297,20 @@ class Plot(PlotBase): return voxel_to_vtk(h5_voxel_file, output) +def Plot(plot_id=None, name=''): + """Legacy Plot class for backward compatibility. + + .. deprecated:: 0.15.4 + Use :class:`SlicePlot` for 2D slice plots or :class:`VoxelPlot` for 3D voxel plots. + + """ + warnings.warn( + "The Plot class is deprecated. Use SlicePlot for 2D slice plots " + "or VoxelPlot for 3D voxel plots.", FutureWarning + ) + return SlicePlot(plot_id, name) + + class RayTracePlot(PlotBase): """Definition of a camera's view of OpenMC geometry @@ -1735,16 +1966,16 @@ class SolidRayTracePlot(RayTracePlot): class Plots(cv.CheckedList): - """Collection of Plots used for an OpenMC simulation. + """Collection of plots used for an OpenMC simulation. This class corresponds directly to the plots.xml input file. It can be thought of as a normal Python list where each member is inherits from :class:`PlotBase`. It behaves like a list as the following example demonstrates: - >>> xz_plot = openmc.Plot() - >>> big_plot = openmc.Plot() - >>> small_plot = openmc.Plot() + >>> xz_plot = openmc.SlicePlot() + >>> big_plot = openmc.VoxelPlot() + >>> small_plot = openmc.SlicePlot() >>> p = openmc.Plots((xz_plot, big_plot)) >>> p.append(small_plot) >>> small_plot = p.pop() @@ -1780,7 +2011,7 @@ class Plots(cv.CheckedList): ---------- index : int Index in list - plot : openmc.Plot + plot : openmc.PlotBase Plot to insert """ @@ -1901,8 +2132,13 @@ class Plots(cv.CheckedList): plots.append(WireframeRayTracePlot.from_xml_element(e)) elif plot_type == 'solid_raytrace': plots.append(SolidRayTracePlot.from_xml_element(e)) - elif plot_type in ('slice', 'voxel'): - plots.append(Plot.from_xml_element(e)) + elif plot_type == 'slice': + plots.append(SlicePlot.from_xml_element(e)) + elif plot_type == 'voxel': + plots.append(VoxelPlot.from_xml_element(e)) + elif plot_type is None: + # For backward compatibility, assume slice if no type specified + plots.append(SlicePlot.from_xml_element(e)) else: raise ValueError("Unknown plot type: {}".format(plot_type)) return plots diff --git a/openmc/plotter.py b/openmc/plotter.py index 85c4963a76..abd8ab6dd4 100644 --- a/openmc/plotter.py +++ b/openmc/plotter.py @@ -413,7 +413,8 @@ def _calculate_cexs_nuclide(this, types, temperature=294., sab_name=None, # Prep S(a,b) data if needed if sab_name: - sab = openmc.data.ThermalScattering.from_hdf5(sab_name) + sab = openmc.data.ThermalScattering.from_hdf5( + library.get_by_material(sab_name, data_type='thermal')['path']) # Obtain the nearest temperature if strT in sab.temperatures: sabT = strT @@ -500,7 +501,7 @@ def _calculate_cexs_nuclide(this, types, temperature=294., sab_name=None, elif ncrystal_cfg: import NCrystal nc_scatter = NCrystal.createScatter(ncrystal_cfg) - nc_func = nc_scatter.crossSectionNonOriented + nc_func = nc_scatter.xsect nc_emax = 5 # eV # this should be obtained from NCRYSTAL_MAX_ENERGY energy_grid = np.union1d(np.geomspace(min(energy_grid), 1.1*nc_emax, @@ -640,14 +641,13 @@ def _calculate_cexs_elem_mat(this, types, temperature=294., sab = openmc.data.ThermalScattering.from_hdf5( library.get_by_material(sab_name, data_type='thermal')['path']) for nuc in sab.nuclides: - sabs[nuc] = library.get_by_material(sab_name, - data_type='thermal')['path'] + sabs[nuc] = sab_name else: if sab_name: - sab = openmc.data.ThermalScattering.from_hdf5(sab_name) + sab = openmc.data.ThermalScattering.from_hdf5( + library.get_by_material(sab_name, data_type='thermal')['path']) for nuc in sab.nuclides: - sabs[nuc] = library.get_by_material(sab_name, - data_type='thermal')['path'] + sabs[nuc] = sab_name # Now we can create the data sets to be plotted xs = {} @@ -655,8 +655,8 @@ def _calculate_cexs_elem_mat(this, types, temperature=294., for nuclide in nuclides.items(): name = nuclide[0] nuc = nuclide[1] - sab_tab = sabs[name] - temp_E, temp_xs = calculate_cexs(nuc, types, T, sab_tab, cross_sections, + sab_name = sabs[name] + temp_E, temp_xs = calculate_cexs(nuc, types, T, sab_name, cross_sections, ncrystal_cfg=ncrystal_cfg ) E.append(temp_E) diff --git a/openmc/settings.py b/openmc/settings.py index ce3743ff5d..76e191c5e0 100644 --- a/openmc/settings.py +++ b/openmc/settings.py @@ -6,7 +6,7 @@ from numbers import Integral, Real from pathlib import Path import lxml.etree as ET - +import warnings import openmc import openmc.checkvalue as cv from openmc.checkvalue import PathLike @@ -47,6 +47,21 @@ class Settings: half-width of the 95% two-sided confidence interval. If False, uncertainties on tally results will be reported as the sample standard deviation. + collision_track : dict + Options for writing collision information. Acceptable keys are: + + :max_collisions: Maximum number of collisions to be banked per file. (int) + :max_collision_track_files: Maximum number of collision_track files. (int) + :mcpl: Output in the form of an MCPL-file. (bool) + :cell_ids: List of cell IDs to define cells in which collisions should be banked. (list of int) + :universe_ids: List of universe IDs to define universes in which collisions should be banked. (list of int) + :material_ids: List of material IDs to define materials in which collisions should be banked. (list of int) + :nuclides: List of nuclides to define nuclides in which collisions should be banked. + (ex: ["I135m", "U233"] ). (list of str) + :reactions: List of reaction to define specific reactions that should be banked + (ex: ["(n,fission)", 2, "(n,2n)"] ). (list of str or int) + :deposited_E_threshold: Number to define the minimum deposited energy during + per collision to trigger banking. (float) create_fission_neutrons : bool Indicate whether fission neutrons should be created or not. cutoff : dict @@ -84,6 +99,10 @@ class Settings: history-based parallelism. .. versionadded:: 0.12 + free_gas_threshold : float + Energy multiplier (in units of :math:`kT`) below which the free gas + scattering treatment is applied for elastic scattering. If not + specified, a value of 400.0 is used. generations_per_batch : int Number of generations per batch ifp_n_generation : int @@ -128,6 +147,10 @@ class Settings: Maximum number of times a particle can split during a history .. versionadded:: 0.13 + max_secondaries : int + Maximum secondary bank size + + .. versionadded:: 0.15.3 max_tracks : int Maximum number of tracks written to a track file (per MPI process). @@ -159,7 +182,7 @@ class Settings: Options for configuring the random ray solver. Acceptable keys are: :distance_inactive: - Indicates the total active distance in [cm] a ray should travel + Indicates the total inactive distance in [cm] a ray should travel :distance_active: Indicates the total active distance in [cm] a ray should travel :ray_source: @@ -372,6 +395,7 @@ class Settings: self._seed = None self._stride = None self._survival_biasing = None + self._free_gas_threshold = None # Shannon entropy mesh self._entropy_mesh = None @@ -386,6 +410,9 @@ class Settings: # Iterated Fission Probability self._ifp_n_generation = None + # Collision track feature + self._collision_track = {} + # Output options self._statepoint = {} self._sourcepoint = {} @@ -425,12 +452,14 @@ class Settings: self._max_particle_events = None self._write_initial_source = None self._weight_windows = WeightWindowsList() - self._weight_window_generators = cv.CheckedList(WeightWindowGenerator, 'weight window generators') + self._weight_window_generators = cv.CheckedList( + WeightWindowGenerator, 'weight window generators') self._weight_windows_on = None self._weight_windows_file = None self._weight_window_checkpoints = {} self._max_history_splits = None self._max_tracks = None + self._max_secondaries = None self._use_decay_photons = None self._random_ray = {} @@ -465,8 +494,9 @@ class Settings: @generations_per_batch.setter def generations_per_batch(self, generations_per_batch: int): - cv.check_type('generations per patch', generations_per_batch, Integral) - cv.check_greater_than('generations per batch', generations_per_batch, 0) + cv.check_type('generations per batch', generations_per_batch, Integral) + cv.check_greater_than('generations per batch', + generations_per_batch, 0) self._generations_per_batch = generations_per_batch @property @@ -496,7 +526,8 @@ class Settings: @rel_max_lost_particles.setter def rel_max_lost_particles(self, rel_max_lost_particles: float): cv.check_type('rel_max_lost_particles', rel_max_lost_particles, Real) - cv.check_greater_than('rel_max_lost_particles', rel_max_lost_particles, 0) + cv.check_greater_than('rel_max_lost_particles', + rel_max_lost_particles, 0) cv.check_less_than('rel_max_lost_particles', rel_max_lost_particles, 1) self._rel_max_lost_particles = rel_max_lost_particles @@ -506,8 +537,10 @@ class Settings: @max_write_lost_particles.setter def max_write_lost_particles(self, max_write_lost_particles: int): - cv.check_type('max_write_lost_particles', max_write_lost_particles, Integral) - cv.check_greater_than('max_write_lost_particles', max_write_lost_particles, 0) + cv.check_type('max_write_lost_particles', + max_write_lost_particles, Integral) + cv.check_greater_than('max_write_lost_particles', + max_write_lost_particles, 0) self._max_write_lost_particles = max_write_lost_particles @property @@ -528,12 +561,12 @@ class Settings: def keff_trigger(self, keff_trigger: dict): if not isinstance(keff_trigger, dict): msg = f'Unable to set a trigger on keff from "{keff_trigger}" ' \ - 'which is not a Python dictionary' + 'which is not a Python dictionary' raise ValueError(msg) elif 'type' not in keff_trigger: msg = f'Unable to set a trigger on keff from "{keff_trigger}" ' \ - 'which does not have a "type" key' + 'which does not have a "type" key' raise ValueError(msg) elif keff_trigger['type'] not in ['variance', 'std_dev', 'rel_err']: @@ -543,7 +576,7 @@ class Settings: elif 'threshold' not in keff_trigger: msg = f'Unable to set a trigger on keff from "{keff_trigger}" ' \ - 'which does not have a "threshold" key' + 'which does not have a "threshold" key' raise ValueError(msg) elif not isinstance(keff_trigger['threshold'], Real): @@ -560,7 +593,7 @@ class Settings: @energy_mode.setter def energy_mode(self, energy_mode: str): cv.check_value('energy mode', energy_mode, - ['continuous-energy', 'multi-group']) + ['continuous-energy', 'multi-group']) self._energy_mode = energy_mode @property @@ -583,7 +616,8 @@ class Settings: def source(self, source: SourceBase | Iterable[SourceBase]): if not isinstance(source, MutableSequence): source = [source] - self._source = cv.CheckedList(SourceBase, 'source distributions', source) + self._source = cv.CheckedList( + SourceBase, 'source distributions', source) @property def confidence_intervals(self) -> bool: @@ -600,7 +634,8 @@ class Settings: @electron_treatment.setter def electron_treatment(self, electron_treatment: str): - cv.check_value('electron treatment', electron_treatment, ['led', 'ttb']) + cv.check_value('electron treatment', + electron_treatment, ['led', 'ttb']) self._electron_treatment = electron_treatment @property @@ -694,7 +729,8 @@ class Settings: @trigger_max_batches.setter def trigger_max_batches(self, trigger_max_batches: int): cv.check_type('trigger maximum batches', trigger_max_batches, Integral) - cv.check_greater_than('trigger maximum batches', trigger_max_batches, 0) + cv.check_greater_than('trigger maximum batches', + trigger_max_batches, 0) self._trigger_max_batches = trigger_max_batches @property @@ -703,8 +739,10 @@ class Settings: @trigger_batch_interval.setter def trigger_batch_interval(self, trigger_batch_interval: int): - cv.check_type('trigger batch interval', trigger_batch_interval, Integral) - cv.check_greater_than('trigger batch interval', trigger_batch_interval, 0) + cv.check_type('trigger batch interval', + trigger_batch_interval, Integral) + cv.check_greater_than('trigger batch interval', + trigger_batch_interval, 0) self._trigger_batch_interval = trigger_batch_interval @property @@ -788,19 +826,22 @@ class Settings: @surf_source_write.setter def surf_source_write(self, surf_source_write: dict): - cv.check_type("surface source writing options", surf_source_write, Mapping) + cv.check_type("surface source writing options", + surf_source_write, Mapping) for key, value in surf_source_write.items(): cv.check_value( "surface source writing key", key, - ("surface_ids", "max_particles", "max_source_files", "mcpl", "cell", "cellfrom", "cellto"), + ("surface_ids", "max_particles", "max_source_files", + "mcpl", "cell", "cellfrom", "cellto"), ) if key == "surface_ids": cv.check_type( "surface ids for source banking", value, Iterable, Integral ) for surf_id in value: - cv.check_greater_than("surface id for source banking", surf_id, 0) + cv.check_greater_than( + "surface id for source banking", surf_id, 0) elif key == "mcpl": cv.check_type("write to an MCPL-format file", value, bool) @@ -817,6 +858,79 @@ class Settings: self._surf_source_write = surf_source_write + @property + def collision_track(self) -> dict: + return self._collision_track + + @collision_track.setter + def collision_track(self, collision_track: dict): + cv.check_type('Collision tracking options', collision_track, Mapping) + for key, value in collision_track.items(): + cv.check_value('collision_track key', key, + ('cell_ids', 'reactions', 'universe_ids', 'material_ids', 'nuclides', + 'deposited_E_threshold', 'max_collisions', 'max_collision_track_files', 'mcpl')) + if key == 'cell_ids': + cv.check_type('cell ids for collision tracking data banking', value, + Iterable, Integral) + for cell_id in value: + cv.check_greater_than('cell id for collision tracking data banking', + cell_id, 0) + elif key == 'reactions': + cv.check_type('MT numbers for collision tracking data banking', value, + Iterable) + for reaction in value: + if isinstance(reaction, int): + cv.check_greater_than( + 'MT number for collision tracking data banking', reaction, 0 + ) + elif isinstance(reaction, str): + # check against allowed strings? so far let C++ code handle it + pass + else: + raise TypeError( + f"MT number for collision tracking data banking must be a positive int or string, " + f"got {type(reaction).__name__}") + elif key == 'universe_ids': + cv.check_type('universe ids for collision tracking data banking', value, + Iterable, Integral) + for universe_id in value: + cv.check_greater_than('universe id for collision tracking data banking', + universe_id, 0) + elif key == 'material_ids': + cv.check_type('material ids for collision tracking data banking', value, + Iterable, Integral) + for material_id in value: + cv.check_greater_than('material id for collision tracking data banking', + material_id, 0) + elif key == 'nuclides': + cv.check_type('nuclides for collision tracking data banking', value, + Iterable, str) + for nuclide in value: + # If nuclide name doesn't look valid, give a warning + try: + openmc.data.zam(nuclide) + except ValueError: + warnings.warn(f"Nuclide {nuclide} is not valid") + elif key == 'deposited_E_threshold': + cv.check_type('Deposited Energy Threshold for collision tracking data banking', + value, Real) + cv.check_greater_than('Deposited Energy Threshold for collision tracking data banking', + value, 0) + elif key == 'max_collisions': + cv.check_type('maximum collisions banks per file', + value, Integral) + cv.check_greater_than('maximum collisions banks in collision tracking', + value, 0) + elif key == 'max_collision_track_files': + cv.check_type('maximum collisions banks', + value, Integral) + cv.check_greater_than('maximum number of collision_track files ', + value, 0) + elif key == 'mcpl': + cv.check_type('write to an MCPL-format file', value, bool) + + self._collision_track = collision_track + @property def no_reduce(self) -> bool: return self._no_reduce @@ -933,7 +1047,7 @@ class Settings: def cutoff(self, cutoff: dict): if not isinstance(cutoff, Mapping): msg = f'Unable to set cutoff from "{cutoff}" which is not a '\ - 'Python dictionary' + 'Python dictionary' raise ValueError(msg) for key in cutoff: if key == 'weight': @@ -951,7 +1065,7 @@ class Settings: cv.check_greater_than('energy cutoff', cutoff[key], 0.0) else: msg = f'Unable to set cutoff to "{key}" which is unsupported ' \ - 'by OpenMC' + 'by OpenMC' self._cutoff = cutoff @@ -1120,12 +1234,14 @@ class Settings: @weight_window_checkpoints.setter def weight_window_checkpoints(self, weight_window_checkpoints: dict): for key in weight_window_checkpoints.keys(): - cv.check_value('weight_window_checkpoints', key, ('collision', 'surface')) + cv.check_value('weight_window_checkpoints', + key, ('collision', 'surface')) self._weight_window_checkpoints = weight_window_checkpoints @property def max_splits(self): - raise AttributeError('max_splits has been deprecated. Please use max_history_splits instead') + raise AttributeError( + 'max_splits has been deprecated. Please use max_history_splits instead') @property def max_history_splits(self) -> int: @@ -1137,6 +1253,16 @@ class Settings: cv.check_greater_than('max particle splits', value, 0) self._max_history_splits = value + @property + def max_secondaries(self) -> int: + return self._max_secondaries + + @max_secondaries.setter + def max_secondaries(self, value: int): + cv.check_type('maximum secondary bank size', value, Integral) + cv.check_greater_than('max secondary bank size', value, 0) + self._max_secondaries = value + @property def max_tracks(self) -> int: return self._max_tracks @@ -1152,9 +1278,12 @@ class Settings: return self._weight_windows_file @weight_windows_file.setter - def weight_windows_file(self, value: PathLike): - cv.check_type('weight windows file', value, PathLike) - self._weight_windows_file = input_path(value) + def weight_windows_file(self, value: PathLike | None): + if value is None: + self._weight_windows_file = None + else: + cv.check_type('weight windows file', value, PathLike) + self._weight_windows_file = input_path(value) @property def weight_window_generators(self) -> list[WeightWindowGenerator]: @@ -1164,7 +1293,8 @@ class Settings: def weight_window_generators(self, wwgs): if not isinstance(wwgs, MutableSequence): wwgs = [wwgs] - self._weight_window_generators = cv.CheckedList(WeightWindowGenerator, 'weight window generators', wwgs) + self._weight_window_generators = cv.CheckedList( + WeightWindowGenerator, 'weight window generators', wwgs) @property def random_ray(self) -> dict: @@ -1201,7 +1331,8 @@ class Settings: for mesh, domains in value: cv.check_type('mesh', mesh, MeshBase) cv.check_type('domains', domains, Iterable) - valid_types = (openmc.Material, openmc.Cell, openmc.Universe) + valid_types = (openmc.Material, + openmc.Cell, openmc.Universe) for domain in domains: if not isinstance(domain, valid_types): raise ValueError( @@ -1235,11 +1366,25 @@ class Settings: @source_rejection_fraction.setter def source_rejection_fraction(self, source_rejection_fraction: float): - cv.check_type('source_rejection_fraction', source_rejection_fraction, Real) - cv.check_greater_than('source_rejection_fraction', source_rejection_fraction, 0) - cv.check_less_than('source_rejection_fraction', source_rejection_fraction, 1) + cv.check_type('source_rejection_fraction', + source_rejection_fraction, Real) + cv.check_greater_than('source_rejection_fraction', + source_rejection_fraction, 0) + cv.check_less_than('source_rejection_fraction', + source_rejection_fraction, 1) self._source_rejection_fraction = source_rejection_fraction + @property + def free_gas_threshold(self) -> float | None: + return self._free_gas_threshold + + @free_gas_threshold.setter + def free_gas_threshold(self, free_gas_threshold: float | None): + if free_gas_threshold is not None: + cv.check_type('free gas threshold', free_gas_threshold, Real) + cv.check_greater_than('free gas threshold', free_gas_threshold, 0.0) + self._free_gas_threshold = free_gas_threshold + def _create_run_mode_subelement(self, root): elem = ET.SubElement(root, "run_mode") elem.text = self._run_mode.value @@ -1391,6 +1536,45 @@ class Settings: subelement = ET.SubElement(element, key) subelement.text = str(self._surf_source_write[key]) + def _create_collision_track_subelement(self, root): + if self._collision_track: + element = ET.SubElement(root, "collision_track") + if 'cell_ids' in self._collision_track: + subelement = ET.SubElement(element, "cell_ids") + subelement.text = ' '.join( + str(x) for x in self._collision_track['cell_ids']) + if 'reactions' in self._collision_track: + subelement = ET.SubElement(element, "reactions") + subelement.text = ' '.join( + str(x) for x in self._collision_track['reactions']) + if 'universe_ids' in self._collision_track: + subelement = ET.SubElement(element, "universe_ids") + subelement.text = ' '.join( + str(x) for x in self._collision_track['universe_ids']) + if 'material_ids' in self._collision_track: + subelement = ET.SubElement(element, "material_ids") + subelement.text = ' '.join( + str(x) for x in self._collision_track['material_ids']) + if 'nuclides' in self._collision_track: + subelement = ET.SubElement(element, "nuclides") + subelement.text = ' '.join( + str(x) for x in self._collision_track['nuclides']) + if 'deposited_E_threshold' in self._collision_track: + subelement = ET.SubElement(element, "deposited_E_threshold") + subelement.text = str( + self._collision_track['deposited_E_threshold']) + if 'max_collisions' in self._collision_track: + subelement = ET.SubElement(element, "max_collisions") + subelement.text = str(self._collision_track['max_collisions']) + if 'max_collision_track_files' in self._collision_track: + subelement = ET.SubElement( + element, "max_collision_track_files") + subelement.text = str( + self._collision_track['max_collision_track_files']) + if 'mcpl' in self._collision_track: + subelement = ET.SubElement(element, "mcpl") + subelement.text = str(self._collision_track['mcpl']).lower() + def _create_confidence_intervals(self, root): if self._confidence_intervals is not None: element = ET.SubElement(root, "confidence_intervals") @@ -1446,8 +1630,8 @@ class Settings: # use default heuristic for entropy mesh if not set by user if self.entropy_mesh.dimension is None: if self.particles is None: - raise RuntimeError("Number of particles must be set in order to " \ - "use entropy mesh dimension heuristic") + raise RuntimeError("Number of particles must be set in order to " + "use entropy mesh dimension heuristic") else: n = ceil((self.particles / 20.0)**(1.0 / 3.0)) d = len(self.entropy_mesh.lower_left) @@ -1537,7 +1721,8 @@ class Settings: path = f"./mesh[@id='{self.ufs_mesh.id}']" if root.find(path) is None: root.append(self.ufs_mesh.to_xml_element()) - if mesh_memo is not None: mesh_memo.add(self.ufs_mesh.id) + if mesh_memo is not None: + mesh_memo.add(self.ufs_mesh.id) def _create_use_decay_photons_subelement(self, root): if self._use_decay_photons is not None: @@ -1626,6 +1811,7 @@ class Settings: if mesh_memo is not None: mesh_memo.add(ww.mesh.id) + def _create_weight_windows_on_subelement(self, root): if self._weight_windows_on is not None: elem = ET.SubElement(root, "weight_windows_on") elem.text = str(self._weight_windows_on).lower() @@ -1662,17 +1848,24 @@ class Settings: if 'collision' in self._weight_window_checkpoints: subelement = ET.SubElement(element, "collision") - subelement.text = str(self._weight_window_checkpoints['collision']).lower() + subelement.text = str( + self._weight_window_checkpoints['collision']).lower() if 'surface' in self._weight_window_checkpoints: subelement = ET.SubElement(element, "surface") - subelement.text = str(self._weight_window_checkpoints['surface']).lower() + subelement.text = str( + self._weight_window_checkpoints['surface']).lower() def _create_max_history_splits_subelement(self, root): if self._max_history_splits is not None: elem = ET.SubElement(root, "max_history_splits") elem.text = str(self._max_history_splits) + def _create_max_secondaries_subelement(self, root): + if self._max_secondaries is not None: + elem = ET.SubElement(root, "max_secondaries") + elem.text = str(self._max_secondaries) + def _create_max_tracks_subelement(self, root): if self._max_tracks is not None: elem = ET.SubElement(root, "max_tracks") @@ -1693,10 +1886,19 @@ class Settings: for domain in domains: domain_elem = ET.SubElement(mesh_elem, 'domain') domain_elem.set('id', str(domain.id)) - domain_elem.set('type', domain.__class__.__name__.lower()) + domain_elem.set( + 'type', domain.__class__.__name__.lower()) if mesh_memo is not None and mesh.id not in mesh_memo: + domain_elem.set('type', domain.__class__.__name__.lower()) + # See if a element already exists -- if not, add it + path = f"./mesh[@id='{mesh.id}']" + if root.find(path) is None: root.append(mesh.to_xml_element()) - mesh_memo.add(mesh.id) + if mesh_memo is not None: + mesh_memo.add(mesh.id) + elif isinstance(value, bool): + subelement = ET.SubElement(element, key) + subelement.text = str(value).lower() else: subelement = ET.SubElement(element, key) subelement.text = str(value) @@ -1706,6 +1908,11 @@ class Settings: element = ET.SubElement(root, "source_rejection_fraction") element.text = str(self._source_rejection_fraction) + def _create_free_gas_threshold_subelement(self, root): + if self._free_gas_threshold is not None: + element = ET.SubElement(root, "free_gas_threshold") + element.text = str(self._free_gas_threshold) + def _eigenvalue_from_xml_element(self, root): elem = root.find('eigenvalue') if elem is not None: @@ -1833,6 +2040,25 @@ class Settings: value = int(value) self.surf_source_write[key] = value + def _collision_track_from_xml_element(self, root): + elem = root.find('collision_track') + if elem is not None: + for key in ('cell_ids', 'reactions', 'universe_ids', 'material_ids', 'nuclides', + 'deposited_E_threshold', 'max_collisions', "max_collision_track_files", 'mcpl'): + value = get_text(elem, key) + if value is not None: + if key in ('cell_ids', 'universe_ids', 'material_ids'): + value = [int(x) for x in value.split()] + elif key in ('reactions', 'nuclides'): + value = value.split() + elif key in ('max_collisions', 'max_collision_track_files'): + value = int(value) + elif key == 'deposited_E_threshold': + value = float(value) + elif key == 'mcpl': + value = value in ('true', '1') + self.collision_track[key] = value + def _confidence_intervals_from_xml_element(self, root): text = get_text(root, 'confidence_intervals') if text is not None: @@ -2054,10 +2280,16 @@ class Settings: ww = WeightWindows.from_xml_element(elem, meshes) self.weight_windows.append(ww) + def _weight_windows_on_from_xml_element(self, root): text = get_text(root, 'weight_windows_on') if text is not None: self.weight_windows_on = text in ('true', '1') + def _weight_windows_file_from_xml_element(self, root): + text = get_text(root, 'weight_windows_file') + if text is not None: + self.weight_windows_file = text + def _weight_window_checkpoints_from_xml_element(self, root): elem = root.find('weight_window_checkpoints') if elem is None: @@ -2073,12 +2305,17 @@ class Settings: if text is not None: self.max_history_splits = int(text) + def _max_secondaries_from_xml_element(self, root): + text = get_text(root, 'max_secondaries') + if text is not None: + self.max_secondaries = int(text) + def _max_tracks_from_xml_element(self, root): text = get_text(root, 'max_tracks') if text is not None: self.max_tracks = int(text) - def _random_ray_from_xml_element(self, root): + def _random_ray_from_xml_element(self, root, meshes=None): elem = root.find('random_ray') if elem is not None: self.random_ray = {} @@ -2105,7 +2342,11 @@ class Settings: elif child.tag == 'source_region_meshes': self.random_ray['source_region_meshes'] = [] for mesh_elem in child.findall('mesh'): - mesh = MeshBase.from_xml_element(mesh_elem) + mesh_id = int(get_text(mesh_elem, 'id')) + if meshes and mesh_id in meshes: + mesh = meshes[mesh_id] + else: + mesh = MeshBase.from_xml_element(mesh_elem) domains = [] for domain_elem in mesh_elem.findall('domain'): domain_id = int(get_text(domain_elem, "id")) @@ -2117,7 +2358,8 @@ class Settings: elif domain_type == 'universe': domain = openmc.Universe(domain_id) domains.append(domain) - self.random_ray['source_region_meshes'].append((mesh, domains)) + self.random_ray['source_region_meshes'].append( + (mesh, domains)) def _use_decay_photons_from_xml_element(self, root): text = get_text(root, 'use_decay_photons') @@ -2129,6 +2371,11 @@ class Settings: if text is not None: self.source_rejection_fraction = float(text) + def _free_gas_threshold_from_xml_element(self, root): + text = get_text(root, 'free_gas_threshold') + if text is not None: + self.free_gas_threshold = float(text) + def to_xml_element(self, mesh_memo=None): """Create a 'settings' element to be written to an XML file. @@ -2155,6 +2402,7 @@ class Settings: self._create_sourcepoint_subelement(element) self._create_surf_source_read_subelement(element) self._create_surf_source_write_subelement(element) + self._create_collision_track_subelement(element) self._create_confidence_intervals(element) self._create_electron_treatment_subelement(element) self._create_energy_mode_subelement(element) @@ -2189,14 +2437,17 @@ class Settings: self._create_log_grid_bins_subelement(element) self._create_write_initial_source_subelement(element) self._create_weight_windows_subelement(element, mesh_memo) + self._create_weight_windows_on_subelement(element) self._create_weight_window_generators_subelement(element, mesh_memo) self._create_weight_windows_file_element(element) self._create_weight_window_checkpoints_subelement(element) self._create_max_history_splits_subelement(element) self._create_max_tracks_subelement(element) + self._create_max_secondaries_subelement(element) self._create_random_ray_subelement(element, mesh_memo) self._create_use_decay_photons_subelement(element) self._create_source_rejection_fraction_subelement(element) + self._create_free_gas_threshold_subelement(element) # Clean the indentation in the file to be user-readable clean_indentation(element) @@ -2265,6 +2516,7 @@ class Settings: settings._sourcepoint_from_xml_element(elem) settings._surf_source_read_from_xml_element(elem) settings._surf_source_write_from_xml_element(elem) + settings._collision_track_from_xml_element(elem) settings._confidence_intervals_from_xml_element(elem) settings._electron_treatment_from_xml_element(elem) settings._energy_mode_from_xml_element(elem) @@ -2298,13 +2550,17 @@ class Settings: settings._log_grid_bins_from_xml_element(elem) settings._write_initial_source_from_xml_element(elem) settings._weight_windows_from_xml_element(elem, meshes) + settings._weight_windows_on_from_xml_element(elem) + settings._weight_windows_file_from_xml_element(elem) settings._weight_window_generators_from_xml_element(elem, meshes) settings._weight_window_checkpoints_from_xml_element(elem) settings._max_history_splits_from_xml_element(elem) settings._max_tracks_from_xml_element(elem) - settings._random_ray_from_xml_element(elem) + settings._max_secondaries_from_xml_element(elem) + settings._random_ray_from_xml_element(elem, meshes) settings._use_decay_photons_from_xml_element(elem) settings._source_rejection_fraction_from_xml_element(elem) + settings._free_gas_threshold_from_xml_element(elem) return settings diff --git a/openmc/source.py b/openmc/source.py index c463ccb275..84d8a9619d 100644 --- a/openmc/source.py +++ b/openmc/source.py @@ -6,7 +6,6 @@ from numbers import Real from pathlib import Path import warnings from typing import Any -from pathlib import Path import lxml.etree as ET import numpy as np @@ -107,10 +106,12 @@ class SourceBase(ABC): cv.check_type('fissionable', value, bool) self._constraints['fissionable'] = value elif key == 'rejection_strategy': - cv.check_value('rejection strategy', value, ('resample', 'kill')) + cv.check_value('rejection strategy', + value, ('resample', 'kill')) self._constraints['rejection_strategy'] = value else: - raise ValueError(f'Unknown key in constraints dictionary: {key}') + raise ValueError( + f'Unknown key in constraints dictionary: {key}') @abstractmethod def populate_xml_element(self, element): @@ -144,13 +145,16 @@ class SourceBase(ABC): dt_elem = ET.SubElement(constraints_elem, "domain_type") dt_elem.text = constraints["domain_type"] id_elem = ET.SubElement(constraints_elem, "domain_ids") - id_elem.text = ' '.join(str(uid) for uid in constraints["domain_ids"]) + id_elem.text = ' '.join(str(uid) + for uid in constraints["domain_ids"]) if "time_bounds" in constraints: dt_elem = ET.SubElement(constraints_elem, "time_bounds") - dt_elem.text = ' '.join(str(t) for t in constraints["time_bounds"]) + dt_elem.text = ' '.join(str(t) + for t in constraints["time_bounds"]) if "energy_bounds" in constraints: dt_elem = ET.SubElement(constraints_elem, "energy_bounds") - dt_elem.text = ' '.join(str(E) for E in constraints["energy_bounds"]) + dt_elem.text = ' '.join(str(E) + for E in constraints["energy_bounds"]) if "fissionable" in constraints: dt_elem = ET.SubElement(constraints_elem, "fissionable") dt_elem.text = str(constraints["fissionable"]).lower() @@ -199,7 +203,8 @@ class SourceBase(ABC): elif source_type == 'mesh': return MeshSource.from_xml_element(elem, meshes) else: - raise ValueError(f'Source type {source_type} is not recognized') + raise ValueError( + f'Source type {source_type} is not recognized') @staticmethod def _get_constraints(elem: ET.Element) -> dict[str, Any]: @@ -260,7 +265,7 @@ class IndependentSource(SourceBase): time distribution of source sites strength : float Strength of the source - particle : {'neutron', 'photon'} + particle : {'neutron', 'photon', 'electron', 'positron'} Source particle type domains : iterable of openmc.Cell, openmc.Material, or openmc.Universe Domains to reject based on, i.e., if a sampled spatial location is not @@ -299,7 +304,7 @@ class IndependentSource(SourceBase): .. versionadded:: 0.14.0 - particle : {'neutron', 'photon'} + particle : {'neutron', 'photon', 'electron', 'positron'} Source particle type constraints : dict Constraints on sampled source particles. Valid keys include @@ -316,7 +321,8 @@ class IndependentSource(SourceBase): time: openmc.stats.Univariate | None = None, strength: float = 1.0, particle: str = 'neutron', - domains: Sequence[openmc.Cell | openmc.Material | openmc.Universe] | None = None, + domains: Sequence[openmc.Cell | openmc.Material | + openmc.Universe] | None = None, constraints: dict[str, Any] | None = None ): if domains is not None: @@ -404,7 +410,8 @@ class IndependentSource(SourceBase): @particle.setter def particle(self, particle): - cv.check_value('source particle', particle, ['neutron', 'photon']) + cv.check_value('source particle', particle, + ['neutron', 'photon', 'electron', 'positron']) self._particle = particle def populate_xml_element(self, element): @@ -526,11 +533,12 @@ class MeshSource(SourceBase): 'fissionable', and 'rejection_strategy'. """ + def __init__( self, mesh: MeshBase, sources: Sequence[SourceBase], - constraints: dict[str, Any] | None = None, + constraints: dict[str, Any] | None = None, ): super().__init__(strength=None, constraints=constraints) self.mesh = mesh @@ -576,7 +584,8 @@ class MeshSource(SourceBase): elif isinstance(self.mesh, UnstructuredMesh): if s.ndim > 1: - raise ValueError('Sources must be a 1-D array for unstructured mesh') + raise ValueError( + 'Sources must be a 1-D array for unstructured mesh') self._sources = s for src in self._sources: @@ -645,7 +654,8 @@ class MeshSource(SourceBase): mesh_id = int(get_text(elem, 'mesh')) mesh = meshes[mesh_id] - sources = [SourceBase.from_xml_element(e) for e in elem.iterchildren('source')] + sources = [SourceBase.from_xml_element( + e) for e in elem.iterchildren('source')] constraints = cls._get_constraints(elem) return cls(mesh, sources, constraints=constraints) @@ -655,7 +665,8 @@ def Source(*args, **kwargs): A function for backward compatibility of sources. Will be removed in the future. Please update to IndependentSource. """ - warnings.warn("This class is deprecated in favor of 'IndependentSource'", FutureWarning) + warnings.warn( + "This class is deprecated in favor of 'IndependentSource'", FutureWarning) return openmc.IndependentSource(*args, **kwargs) @@ -702,6 +713,7 @@ class CompiledSource(SourceBase): 'fissionable', and 'rejection_strategy'. """ + def __init__( self, library: PathLike, @@ -913,7 +925,8 @@ class ParticleType(IntEnum): try: return cls[value.upper()] except KeyError: - raise ValueError(f"Invalid string for creation of {cls.__name__}: {value}") + raise ValueError( + f"Invalid string for creation of {cls.__name__}: {value}") @classmethod def from_pdg_number(cls, pdg_number: int) -> ParticleType: @@ -983,6 +996,7 @@ class SourceParticle: Type of the particle """ + def __init__( self, r: Iterable[float] = (0., 0., 0.), @@ -1041,7 +1055,8 @@ def write_source_file( openmc.SourceParticle """ - cv.check_iterable_type("source particles", source_particles, SourceParticle) + cv.check_iterable_type( + "source particles", source_particles, SourceParticle) pl = ParticleList(source_particles) pl.export_to_hdf5(filename, **kwargs) @@ -1103,7 +1118,8 @@ class ParticleList(list): for particle in f.particles: # Determine particle type based on the PDG number try: - particle_type = ParticleType.from_pdg_number(particle.pdgcode) + particle_type = ParticleType.from_pdg_number( + particle.pdgcode) except ValueError: particle_type = "UNKNOWN" @@ -1240,3 +1256,133 @@ def read_source_file(filename: PathLike) -> ParticleList: return ParticleList.from_hdf5(filename) else: return ParticleList.from_mcpl(filename) + + +def read_collision_track_hdf5(filename): + """Read a collision track file in HDF5 format. + + Parameters + ---------- + filename : str or path-like + Path to the HDF5 collision track file. + + Returns + ------- + numpy.ndarray + Structured array containing collision track data. + + See Also + -------- + read_collision_track_mcpl + read_collision_track_file + """ + + with h5py.File(filename, 'r') as file: + data = file['collision_track_bank'][:] + + return data + + +def read_collision_track_mcpl(file_path): + """Read a collision track file in MCPL format. + + Parameters + ---------- + file_path : str or path-like + Path to the MCPL collision track file. + + Returns + ------- + numpy.ndarray + Structured array of particle collision track information, including + position, direction, energy, weight, reaction data, and identifiers. + + See Also + -------- + read_collision_track_hdf5 + read_collision_track_file + """ + import mcpl + myfile = mcpl.MCPLFile(file_path) + data = { + 'r': [], # for position (x, y, z) + 'u': [], # for direction (ux, uy, uz) + 'E': [], 'dE': [], 'time': [], + 'wgt': [], 'event_mt': [], 'delayed_group': [], + 'cell_id': [], 'nuclide_id': [], 'material_id': [], + 'universe_id': [], 'n_collision': [], 'particle': [], + 'parent_id': [], 'progeny_id': [] + } + + # Read and collect data from the MCPL file + for i, p in enumerate(myfile.particles): + if f'blob_{i}' in myfile.blobs: + blob_data = myfile.blobs[f'blob_{i}'] + decoded_str = blob_data.decode('utf-8') + pairs = decoded_str.split(';') + values_dict = {k.strip(): v.strip() + for k, v in (pair.split(':') for pair in pairs if pair.strip())} + + data['r'].append((p.x, p.y, p.z)) # Append as tuple + data['u'].append((p.ux, p.uy, p.uz)) # Append as tuple + data['E'].append(p.ekin * 1e6) + data['dE'].append(float(values_dict.get('dE', 0))) + data['time'].append(p.time * 1e-3) + data['wgt'].append(p.weight) + data['event_mt'].append(int(values_dict.get('event_mt', 0))) + data['delayed_group'].append( + int(values_dict.get('delayed_group', 0))) + data['cell_id'].append(int(values_dict.get('cell_id', 0))) + data['nuclide_id'].append(int(values_dict.get('nuclide_id', 0))) + data['material_id'].append(int(values_dict.get('material_id', 0))) + data['universe_id'].append(int(values_dict.get('universe_id', 0))) + data['n_collision'].append(int(values_dict.get('n_collision', 0))) + data['particle'].append(ParticleType.from_pdg_number(p.pdgcode)) + data['parent_id'].append(int(values_dict.get('parent_id', 0))) + data['progeny_id'].append(int(values_dict.get('progeny_id', 0))) + + dtypes = [ + ('r', [('x', 'f8'), ('y', 'f8'), ('z', 'f8')]), + ('u', [('x', 'f8'), ('y', 'f8'), ('z', 'f8')]), + ('E', 'f8'), ('dE', 'f8'), ('time', 'f8'), ('wgt', 'f8'), + ('event_mt', 'f8'), ('delayed_group', 'i4'), ('cell_id', 'i4'), + ('nuclide_id', 'i4'), ('material_id', 'i4'), ('universe_id', 'i4'), + ('n_collision', 'i4'), ('particle', 'i4'), + ('parent_id', 'i8'), ('progeny_id', 'i8') + ] + + structured_array = np.zeros(len(data['r']), dtype=dtypes) + for key in data: + structured_array[key] = data[key] # Assign data + + return structured_array + + +def read_collision_track_file(filename): + """Read a collision track file (HDF5 or MCPL) and return its data. + + Parameters + ---------- + filename : str or path-like + Path to the collision track file to read. Must end with + ``.h5`` or ``.mcpl``. + + Returns + ------- + numpy.ndarray + Structured array containing collision track data. + + See Also + -------- + read_collision_track_hdf5 + read_collision_track_mcpl + """ + + filename = Path(filename) + if filename.suffix not in ('.h5', '.mcpl'): + raise ValueError('Collision track file must have a .h5 or .mcpl extension.') + + if filename.suffix == '.h5': + return read_collision_track_hdf5(filename) + else: + return read_collision_track_mcpl(filename) diff --git a/openmc/statepoint.py b/openmc/statepoint.py index 715becf488..a10ec3a839 100644 --- a/openmc/statepoint.py +++ b/openmc/statepoint.py @@ -1,4 +1,5 @@ from datetime import datetime +from collections import namedtuple import glob import re import os @@ -8,6 +9,7 @@ import h5py import numpy as np from pathlib import Path from uncertainties import ufloat +from uncertainties.unumpy import uarray import openmc import openmc.checkvalue as cv @@ -15,6 +17,9 @@ import openmc.checkvalue as cv _VERSION_STATEPOINT = 18 +KineticsParameters = namedtuple("KineticsParameters", ["generation_time", "beta_effective"]) + + class StatePoint: """State information on a simulation at a certain point in time (at the end of a given batch). Statepoints can be used to analyze tally results as well @@ -429,6 +434,10 @@ class StatePoint: if "multiply_density" in group.attrs: tally.multiply_density = group.attrs["multiply_density"].item() > 0 + # Check if tally has higher_moments attribute + if 'higher_moments' in group.attrs: + tally.higher_moments = bool(group.attrs['higher_moments'][()]) + # Read the number of realizations n_realizations = group['n_realizations'][()] @@ -531,7 +540,7 @@ class StatePoint: def get_tally(self, scores=[], filters=[], nuclides=[], name=None, id=None, estimator=None, exact_filters=False, exact_nuclides=False, exact_scores=False, - multiply_density=None, derivative=None): + multiply_density=None, derivative=None, filter_type=None): """Finds and returns a Tally object with certain properties. This routine searches the list of Tallies and returns the first Tally @@ -575,6 +584,9 @@ class StatePoint: to the same value as this parameter. derivative : openmc.TallyDerivative, optional TallyDerivative object to match. + filter_type : type, optional + If not None, the Tally must have at least one Filter that is an + instance of this type. For example `openmc.MeshFilter`. Returns ------- @@ -648,6 +660,10 @@ class StatePoint: if not contains_filters: continue + if filter_type is not None: + if not any(isinstance(f, filter_type) for f in test_tally.filters): + continue + # Determine if Tally has the queried Nuclide(s) if nuclides: if not all(nuclide in test_tally.nuclides for nuclide in nuclides): @@ -707,6 +723,59 @@ class StatePoint: cell = cells[cell_id] if not cell._paths: summary.geometry.determine_paths() - tally_filter.paths = cell.paths + tally_filter._paths = cell.paths self._summary = summary + + def get_kinetics_parameters(self) -> KineticsParameters: + """Get kinetics parameters from IFP tallies. + + This method searches the tallies in the statepoint for the tallies + required to compute kinetics parameters using the Iterated Fission + Probability (IFP) method. + + Returns + ------- + KineticsParameters + A named tuple containing the generation time and effective delayed + neutron fraction. If the necessary tallies for one or both + parameters are not found, that parameter is returned as None. + + """ + + denom_tally = None + gen_time_tally = None + beta_tally = None + for tally in self.tallies.values(): + if 'ifp-denominator' in tally.scores: + denom_tally = self.get_tally(scores=['ifp-denominator']) + if 'ifp-time-numerator' in tally.scores: + gen_time_tally = self.get_tally(scores=['ifp-time-numerator']) + if 'ifp-beta-numerator' in tally.scores: + beta_tally = self.get_tally(scores=['ifp-beta-numerator']) + + if denom_tally is None: + return KineticsParameters(None, None) + + def get_ufloat(tally, score): + return uarray(tally.get_values(scores=[score]), + tally.get_values(scores=[score], value='std_dev')) + + denom_values = get_ufloat(denom_tally, 'ifp-denominator') + if gen_time_tally is None: + generation_time = None + else: + gen_time_values = get_ufloat(gen_time_tally, 'ifp-time-numerator') + gen_time_values /= denom_values*self.keff + generation_time = gen_time_values.flatten()[0] + + if beta_tally is None: + beta_effective = None + else: + beta_values = get_ufloat(beta_tally, 'ifp-beta-numerator') + beta_values /= denom_values + beta_effective = beta_values.flatten() + if beta_effective.size == 1: + beta_effective = beta_effective[0] + + return KineticsParameters(generation_time, beta_effective) diff --git a/openmc/stats/multivariate.py b/openmc/stats/multivariate.py index 222d2d18a5..1ce998758a 100644 --- a/openmc/stats/multivariate.py +++ b/openmc/stats/multivariate.py @@ -79,6 +79,9 @@ class PolarAzimuthal(UnitSphere): reference_uvw : Iterable of float Direction from which polar angle is measured. Defaults to the positive z-direction. + reference_vwu : Iterable of float + Direction from which azimuthal angle is measured. Defaults to the positive + x-direction. Attributes ---------- @@ -89,8 +92,9 @@ class PolarAzimuthal(UnitSphere): """ - def __init__(self, mu=None, phi=None, reference_uvw=(0., 0., 1.)): + def __init__(self, mu=None, phi=None, reference_uvw=(0., 0., 1.), reference_vwu=(1., 0., 0.)): super().__init__(reference_uvw) + self.reference_vwu = reference_vwu if mu is not None: self.mu = mu else: @@ -100,6 +104,20 @@ class PolarAzimuthal(UnitSphere): self.phi = phi else: self.phi = Uniform(0., 2*pi) + + @property + def reference_vwu(self): + return self._reference_vwu + + @reference_vwu.setter + def reference_vwu(self, vwu): + cv.check_type('reference v direction', vwu, Iterable, Real) + vwu = np.asarray(vwu) + uvw = self.reference_uvw + cv.check_greater_than('reference v direction must not be parallel to reference u direction', np.linalg.norm(np.cross(vwu,uvw)), 1e-6*np.linalg.norm(vwu)) + vwu -= vwu.dot(uvw)*uvw + cv.check_less_than('reference v direction must be orthogonal to reference u direction', np.abs(vwu.dot(uvw)), 1e-6) + self._reference_vwu = vwu/np.linalg.norm(vwu) @property def mu(self): @@ -132,6 +150,8 @@ class PolarAzimuthal(UnitSphere): element.set("type", "mu-phi") if self.reference_uvw is not None: element.set("reference_uvw", ' '.join(map(str, self.reference_uvw))) + if self.reference_vwu is not None: + element.set("reference_vwu", ' '.join(map(str, self.reference_vwu))) element.append(self.mu.to_xml_element('mu')) element.append(self.phi.to_xml_element('phi')) return element @@ -155,6 +175,9 @@ class PolarAzimuthal(UnitSphere): uvw = get_elem_list(elem, "reference_uvw", float) if uvw is not None: mu_phi.reference_uvw = uvw + vwu = get_elem_list(elem, "reference_vwu", float) + if vwu is not None: + mu_phi.reference_vwu = vwu mu_phi.mu = Univariate.from_xml_element(elem.find('mu')) mu_phi.phi = Univariate.from_xml_element(elem.find('phi')) return mu_phi diff --git a/openmc/stats/univariate.py b/openmc/stats/univariate.py index 28d5e87ef9..c48cc00757 100644 --- a/openmc/stats/univariate.py +++ b/openmc/stats/univariate.py @@ -295,6 +295,20 @@ class Discrete(Univariate): """ return np.sum(self.p) + def mean(self) -> float: + """Return mean of the discrete distribution + + The mean is the weighted average of the discrete values. + + .. versionadded:: 0.15.3 + + Returns + ------- + float + Mean of discrete distribution + """ + return np.sum(self.x * self.p) / np.sum(self.p) + def clip(self, tolerance: float = 1e-6, inplace: bool = False) -> Discrete: r"""Remove low-importance points from discrete distribution. @@ -413,6 +427,18 @@ class Uniform(Univariate): rng = np.random.RandomState(seed) return rng.uniform(self.a, self.b, n_samples) + def mean(self) -> float: + """Return mean of the uniform distribution + + .. versionadded:: 0.15.3 + + Returns + ------- + float + Mean of uniform distribution + """ + return 0.5 * (self.a + self.b) + def to_xml_element(self, element_name: str): """Return XML representation of the uniform distribution @@ -480,6 +506,9 @@ class PowerLaw(Univariate): """ def __init__(self, a: float = 0.0, b: float = 1.0, n: float = 0.): + if a >= b: + raise ValueError( + "Lower bound of sampling interval must be less than upper bound.") self.a = a self.b = b self.n = n @@ -494,6 +523,9 @@ class PowerLaw(Univariate): @a.setter def a(self, a): cv.check_type('interval lower bound', a, Real) + if a < 0: + raise ValueError( + "PowerLaw sampling is restricted to positive-valued intervals.") self._a = a @property @@ -503,6 +535,9 @@ class PowerLaw(Univariate): @b.setter def b(self, b): cv.check_type('interval upper bound', b, Real) + if b < 0: + raise ValueError( + "PowerLaw sampling is restricted to positive-valued intervals.") self._b = b @property @@ -1114,7 +1149,7 @@ class Tabular(Univariate): """ interpolation = get_text(elem, 'interpolation') - params = get_elem_list(elem, "parameters", float) + params = get_elem_list(elem, "parameters", float) m = (len(params) + 1)//2 # +1 for when len(params) is odd x = params[:m] p = params[m:] @@ -1338,6 +1373,30 @@ class Mixture(Univariate): for p, dist in zip(self.probability, self.distribution) ]) + def mean(self) -> float: + """Return mean of the mixture distribution + + The mean is the weighted average of the means of the component + distributions, weighted by probability * integral. + + .. versionadded:: 0.15.3 + + Returns + ------- + float + Mean of the mixture distribution + """ + # Weight each component by its probability and integral + weights = [p*dist.integral() for p, dist in + zip(self.probability, self.distribution)] + total_weight = sum(weights) + + if total_weight == 0: + return 0.0 + + return sum([w*dist.mean() for w, dist in + zip(weights, self.distribution)]) / total_weight + def clip(self, tolerance: float = 1e-6, inplace: bool = False) -> Mixture: r"""Remove low-importance points / distributions @@ -1360,14 +1419,14 @@ class Mixture(Univariate): Distribution with low-importance points / distributions removed """ - # Determine integral of original distribution to compare later - original_integral = self.integral() + # Calculate mean * integral for original distribution to compare later. + original_mean_integral = self.mean() * self.integral() # Determine indices for any distributions that contribute non-negligibly - # to overall intensity - intensities = [prob*dist.integral() for prob, dist in - zip(self.probability, self.distribution)] - indices = _intensity_clip(intensities, tolerance=tolerance) + # to overall mean * integral + mean_integrals = [prob*dist.mean()*dist.integral() for prob, dist in + zip(self.probability, self.distribution)] + indices = _intensity_clip(mean_integrals, tolerance=tolerance) # Clip mixture of distributions probability = self.probability[indices] @@ -1388,12 +1447,14 @@ class Mixture(Univariate): # Create new distribution new_dist = type(self)(probability, distribution) - # Show warning if integral of new distribution is not within - # tolerance of original - diff = (original_integral - new_dist.integral())/original_integral + # Show warning if mean * integral of new distribution is not within + # tolerance of original. For energy distributions, mean * integral + # represents total energy. + new_mean_integral = new_dist.mean() * new_dist.integral() + diff = (original_mean_integral - new_mean_integral)/original_mean_integral if diff > tolerance: - warn("Clipping mixture distribution resulted in an integral that is " - f"lower by a fraction of {diff} when tolerance={tolerance}.") + warn("Clipping mixture distribution resulted in a mean*integral " + f"that is lower by a fraction of {diff} when tolerance={tolerance}.") return new_dist diff --git a/openmc/surface.py b/openmc/surface.py index 4839783ffa..1fe5fabdf7 100644 --- a/openmc/surface.py +++ b/openmc/surface.py @@ -123,9 +123,8 @@ class Surface(IDManagerMixin, ABC): boundary_type : {'transmission', 'vacuum', 'reflective', 'periodic', 'white'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. Note that periodic boundary conditions - can only be applied to x-, y-, and z-planes, and only axis-aligned - periodicity is supported. + freely pass through the surface. Note that only axis-aligned + periodicity is supported around the x-, y-, and z-axes. albedo : float, optional Albedo of the surfaces as a ratio of particle weight after interaction with the surface to the initial weight. Values must be positive. Only @@ -822,8 +821,7 @@ class XPlane(PlaneMixin, Surface): boundary_type : {'transmission', 'vacuum', 'reflective', 'periodic', 'white'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. Only axis-aligned periodicity is - supported, i.e., x-planes can only be paired with x-planes. + freely pass through the surface. albedo : float, optional Albedo of the surfaces as a ratio of particle weight after interaction with the surface to the initial weight. Values must be positive. Only @@ -887,8 +885,7 @@ class YPlane(PlaneMixin, Surface): boundary_type : {'transmission', 'vacuum', 'reflective', 'periodic', 'white'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. Only axis-aligned periodicity is - supported, i.e., y-planes can only be paired with y-planes. + freely pass through the surface. albedo : float, optional Albedo of the surfaces as a ratio of particle weight after interaction with the surface to the initial weight. Values must be positive. Only @@ -952,8 +949,7 @@ class ZPlane(PlaneMixin, Surface): boundary_type : {'transmission', 'vacuum', 'reflective', 'periodic', 'white'}, optional Boundary condition that defines the behavior for particles hitting the surface. Defaults to transmissive boundary condition where particles - freely pass through the surface. Only axis-aligned periodicity is - supported, i.e., z-planes can only be paired with z-planes. + freely pass through the surface. albedo : float, optional Albedo of the surfaces as a ratio of particle weight after interaction with the surface to the initial weight. Values must be positive. Only diff --git a/openmc/tallies.py b/openmc/tallies.py index 075b1e9911..09365e5257 100644 --- a/openmc/tallies.py +++ b/openmc/tallies.py @@ -3,6 +3,7 @@ from collections.abc import Iterable, MutableSequence import copy from functools import partial, reduce, wraps from itertools import product +from math import sqrt, log from numbers import Integral, Real import operator from pathlib import Path @@ -12,6 +13,7 @@ import h5py import numpy as np import pandas as pd import scipy.sparse as sps +from scipy.stats import chi2, norm import openmc import openmc.checkvalue as cv @@ -91,10 +93,20 @@ class Tally(IDManagerMixin): sum_sq : numpy.ndarray An array containing the sum of each independent realization squared for each bin + sum_third : numpy.ndarray + An array containing the sum of each independent realization to the third power for + each bin + sum_fourth : numpy.ndarray + An array containing the sum of each independent realization to the fourth power for + each bin mean : numpy.ndarray An array containing the sample mean for each bin std_dev : numpy.ndarray An array containing the sample standard deviation for each bin + vov : numpy.ndarray + An array containing the variance of the variance for each tally bin + higher_moments : bool + Whether or not the tally accumulates the sums third and fourth to compute higher-order moments figure_of_merit : numpy.ndarray An array containing the figure of merit for each bin @@ -129,8 +141,12 @@ class Tally(IDManagerMixin): self._sum = None self._sum_sq = None + self._sum_third = None + self._sum_fourth = None self._mean = None self._std_dev = None + self._vov = None + self._higher_moments = False self._simulation_time = None self._with_batch_statistics = False self._derived = False @@ -221,6 +237,15 @@ class Tally(IDManagerMixin): cv.check_type('multiply density', value, bool) self._multiply_density = value + @property + def higher_moments(self) -> bool: + return self._higher_moments + + @higher_moments.setter + def higher_moments(self, value): + cv.check_type("higher_moments", value, bool) + self._higher_moments = value + @property def filters(self): return self._filters @@ -265,7 +290,7 @@ class Tally(IDManagerMixin): @property def num_nuclides(self): - return len(self._nuclides) + return max(len(self._nuclides), 1) @property def scores(self): @@ -368,9 +393,19 @@ class Tally(IDManagerMixin): group = f[f'tallies/tally {self.id}'] self._num_realizations = int(group['n_realizations'][()]) + for filt in self.filters: + if isinstance(filt, openmc.DistribcellFilter): + filter_group = f[f'tallies/filters/filter {filt.id}'] + filt._num_bins = int(filter_group['n_bins'][()]) + # Update nuclides nuclide_names = group['nuclides'][()] self._nuclides = [name.decode().strip() for name in nuclide_names] + # Check for higher_moments attribute + if "higher_moments" in group.attrs: + self._higher_moments = bool(group.attrs["higher_moments"][()]) + else: + self._higher_moments = False # Extract Tally data from the file data = group['results'] @@ -385,10 +420,25 @@ class Tally(IDManagerMixin): self._sum = sum_ self._sum_sq = sum_sq + if self._higher_moments: + # Extract additional Tally data when higher moments enabled + sum_third = data[:, :, 2] + sum_fourth = data[:, :, 3] + + # Reshape the results arrays + sum_third = np.reshape(sum_third, self.shape) + sum_fourth = np.reshape(sum_fourth, self.shape) + + # Set the additional data for this Tally + self._sum_third = sum_third + self._sum_fourth = sum_fourth + # Convert NumPy arrays to SciPy sparse LIL matrices if self.sparse: self._sum = sps.lil_matrix(self._sum.flatten(), self._sum.shape) self._sum_sq = sps.lil_matrix(self._sum_sq.flatten(), self._sum_sq.shape) + self._sum_third = sps.lil_matrix(self._sum_third.flatten(), self._sum_third.shape) + self._sum_fourth = sps.lil_matrix(self.sum_fourth.flatten(), self._sum_fourth.shape) # Read simulation time (needed for figure of merit) self._simulation_time = f["runtime"]["simulation"][()] @@ -428,6 +478,52 @@ class Tally(IDManagerMixin): cv.check_type('sum_sq', sum_sq, Iterable) self._sum_sq = sum_sq + @property + @ensure_results + def sum_third(self): + if not self._higher_moments: + raise ValueError( + "Higher moments have not been enabled for this tally. To make " + "higher moments available, set the higher_moments attribute to " + "True before running a simulation." + ) + + if not self._sp_filename or self.derived: + return None + + if self.sparse: + return np.reshape(self._sum_third.toarray(), self.shape) + else: + return self._sum_third + + @sum_third.setter + def sum_third(self, sum_third): + cv.check_type("sum_third", sum_third, Iterable) + self._sum_third = sum_third + + @property + @ensure_results + def sum_fourth(self): + if not self._higher_moments: + raise ValueError( + "Higher moments have not been enabled for this tally. To make " + "higher moments available, set the higher_moments attribute to " + "True before running a simulation." + ) + + if not self._sp_filename or self.derived: + return None + + if self.sparse: + return np.reshape(self._sum_fourth.toarray(), self.shape) + else: + return self._sum_fourth + + @sum_fourth.setter + def sum_fourth(self, sum_fourth): + cv.check_type("sum_fourth", sum_fourth, Iterable) + self._sum_fourth = sum_fourth + @property def mean(self): if self._mean is None: @@ -470,14 +566,357 @@ class Tally(IDManagerMixin): else: return self._std_dev + @property + def vov(self): + if self._vov is None: + n = self.num_realizations + sum1 = self.sum + sum2 = self.sum_sq + sum3 = self.sum_third + sum4 = self.sum_fourth + self._vov = np.zeros_like(sum1, dtype=float) + + # Calculate the variance of the variance (Eq. 2.232 in + # https://doi.org/10.2172/2372634) + numerator = (sum4 - (4.0*sum3*sum1)/n + + (6.0*sum2*(sum1**2))/(n**2) + - (3.0*(sum1)**4)/(n**3)) + denominator = (sum2 - (1.0/n)*(sum1**2))**2 + + mask = denominator > 0.0 + + self._vov[mask] = numerator[mask]/denominator[mask] - 1.0/n + + if self.sparse: + self._vov = sps.lil_matrix(self._vov.flatten(), self._vov.shape) + + if self.sparse: + return np.reshape(self._vov.toarray(), self.shape) + else: + return self._vov + + @property + def m2(self): + n = self.num_realizations + return self.sum_sq/n - self.mean**2 + + @property + def m3(self): + n = self.num_realizations + mean = self.mean + sum2 = self.sum_sq/n + sum3 = self.sum_third/n + + return sum3 - 3.0*mean*sum2 + 2.0*mean**3 + + @property + def m4(self): + n = self.num_realizations + mean = self.mean + sum2 = self.sum_sq/n + sum3 = self.sum_third/n + sum4 = self.sum_fourth/n + + return sum4 - 4.0*mean*sum3 + 6.0*(mean**2)*sum2 - 3.0*mean**4 + + def skew(self, bias=False) -> np.ndarray: + """Return the sample skewness of each tally bin. + + This method computes and returns the unadjusted or adjusted + Fisher-Pearson coefficient of skewness. + + Parameters + ---------- + bias : bool + If False, calculations are corrected for bias and the adjusted + Fisher-Pearson skewness (:math:`G_1`) is returned. If True, + calculations are not corrected for bias and the unadjusted skewness + (:math:`g_1`) is returned. + + Returns + ------- + float + The skewness of each tally bin + """ + n = self.num_realizations + m2 = self.m2 + m3 = self.m3 + + with np.errstate(divide="ignore", invalid="ignore"): + g1 = np.where(m2 > 0.0, m3/(m2**1.5), 0.0) + + if bias: + return g1 + else: + if n <= 2: + raise ValueError("Insufficient number of independent realizations" + f"for bias-corrected skewness: need n >= 3, got {n=}.") + else: + return sqrt(n*(n - 1))/(n - 2)*g1 + + def kurtosis(self, fisher=True, bias=False) -> np.ndarray: + r"""Return the sample kurtosis of each tally bin. + + This method computes and returns the sample kurtosis using either + Pearson's or Fisher's definition, with or without finite-sample bias + correction. The value returned depends on the `bias` and `fisher` + arguments as follows: + + - **bias=True, fisher=False**: Returns :math:`b_2` (Pearson's kurtosis) + This is the raw fourth standardized moment: :math:`m_4/m_2^2`. For a + normal distribution, :math:`b_2\approx 3`. + + - **bias=True, fisher=True**: Returns :math:`g_2` (excess kurtosis) This + is :math:`b_2 - 3`, centered at 0 for normal distributions. Positive + values indicate heavier tails, negative values lighter tails. + + - **bias=False, fisher=True** (default): Returns :math:`G_2` (adjusted + excess kurtosis). This applies finite-sample bias correction to + :math:`g_2`. This is the recommended estimator for statistical + inference. + + - **bias=False, fisher=False**: Returns bias-corrected Pearson's + kurtosis. This is :math:`G_2 + 3`. + + Parameters + ---------- + fisher : bool, optional + If True (default), Fisher's definition is used (excess kurtosis). If + False, Pearson's definition is used. + bias : bool, optional + If False (default), calculations are corrected for statistical bias + using finite-sample adjustments. If True, calculations use the + biased estimator (population formulas). + + Returns + ------- + numpy.ndarray + The kurtosis of each tally bin + + """ + n = self.num_realizations + m2 = self.m2 + m4 = self.m4 + + with np.errstate(divide="ignore", invalid="ignore"): + b2 = np.where(m2 > 0.0, m4/(m2**2), 0.0) + g2 = b2 - 3.0 + + if bias: + # Biased estimator (g2 or b2) + return g2 if fisher else b2 + else: + # Unbiased estimator with finite-sample correction + if n <= 3: + raise ValueError("Insufficient number of independent realizations" + f"for bias-corrected kurtosis: need n >= 4, got {n=}.") + else: + G2 = ((n - 1)/((n - 2)*(n - 3)))*((n + 1)*g2 + 6.0) + return G2 if fisher else G2 + 3.0 + + def skewtest(self, alternative: str = "two-sided"): + """Perform D'Agostino and Pearson's test for skewness. + + This method tests the null hypothesis that the skewness of the + population that the sample was drawn from is the same as that of a + corresponding normal distribution. + + Parameters + ---------- + alternative : {'two-sided', 'less', 'greater'}, optional + Defines the alternative hypothesis. The following options are + available: + + * 'two-sided': the skewness of the distribution is different from + that of the normal distribution (i.e., non-zero) + * 'less': the skewness of the distribution is less than that of the + normal distribution + * 'greater': the skewness of the distribution is greater than that + of the normal distribution + + Returns + ------- + statistic : np.ndarray + The computed z-score for the skewness test for each tally bin + pvalue : np.ndarray + The p-value for the hypothesis test for each tally bin + + Notes + ----- + This test is based on `D'Agostino and Pearson's test + `_. The test requires at least + 8 realizations to produce valid results. + + """ + n = self.num_realizations + if n < 8: + raise ValueError("Skewness test is not well-defined for n < 8.") + + g1 = self.skew(bias=True) + + # --- Z1 (skewness) --- + y = g1 * sqrt(((n + 1.0)*(n + 3.0))/(6.0*(n - 2.0))) + beta2 = (3.0*(n**2 + 27.0*n - 70.0)*(n + 1.0)*(n + 3.0) + )/((n - 2.0)*(n + 5.0)*(n + 7.0)*(n + 9.0)) + W2 = -1.0 + sqrt(2.0*(beta2 - 1.0)) + delta = 1.0 / sqrt(log(sqrt(W2))) + alpha = sqrt(2.0 / (W2 - 1.0)) + Zb1 = np.where( + y >= 0.0, + delta*np.log((y/alpha) + np.sqrt((y/alpha)**2 + 1.0)), + -delta*np.log((-y/alpha) + np.sqrt((y/alpha)**2 + 1.0)) + ) + + # p-value + if alternative == "two-sided": + p = 2.0 * (1.0 - norm.cdf(np.abs(Zb1))) + elif alternative == "greater": + p = 1.0 - norm.cdf(Zb1) + elif alternative == "less": + p = norm.cdf(Zb1) + else: + raise ValueError("alternative must be 'two-sided', 'greater', or 'less'") + + return Zb1, p + + def kurtosistest(self, alternative: str = "two-sided"): + """Perform D'Agostino and Pearson's test for kurtosis. + + This method tests the null hypothesis that the kurtosis of the + population that the sample was drawn from is the same as that of a + corresponding normal distribution. + + Parameters + ---------- + alternative : {'two-sided', 'less', 'greater'}, optional + Defines the alternative hypothesis. Default is 'two-sided'. The + following options are available: + + * 'two-sided': the kurtosis of the distribution is different from + that of the normal distribution + * 'less': the kurtosis of the distribution is less than that of the + normal distribution + * 'greater': the kurtosis of the distribution is greater than that + of the normal distribution + + Returns + ------- + statistic : np.ndarray + The computed z-score for the kurtosis test for each tally bin + pvalue : np.ndarray + The p-value for the hypothesis test for each tally bin + + Raises + ------ + ValueError + If the number of realizations is less than 20, or if an invalid + alternative hypothesis is specified. + + Notes + ----- + This test is based on `D'Agostino and Pearson's test + `_. The test is typically + recommended for at least 20 realizations to produce valid results. + + """ + n = self.num_realizations + if n < 20: + raise ValueError("Kurtosis test is typically recommended for n >= 20.") + + b2 = self.kurtosis(bias=True, fisher=False) + + # --- Z2 (kurtosis) --- + mean_b2 = 3.0 * (n - 1.0) / (n + 1.0) + var_b2 = (24.0*n*(n - 2.0)*(n - 3.0)/( + (n + 1.0)**2*(n + 3.0)*(n + 5.0))) + x = (b2 - mean_b2)/np.sqrt(var_b2) + moment = ((6.0*(n**2 - 5.0*n + 2.0))/((n + 7.0)*(n + 9.0)) + )*sqrt((6.0*(n + 3.0)*(n + 5.0))/(n*(n - 2.0)*(n - 3.0))) + A = 6.0 + (8.0/moment)*((2.0/moment) + sqrt(1.0 + 4.0/(moment**2))) + Zb2 = (1.0- 2.0/(9.0*A) - ((1.0 - 2.0/A) / (1.0 + (x + )*sqrt(2.0/(A - 4.0))))**(1.0/3.0)) / sqrt(2.0/(9.0*A)) + + # p-value + if alternative == "two-sided": + p = 2.0 * (1.0 - norm.cdf(np.abs(Zb2))) + elif alternative == "greater": + p = 1.0 - norm.cdf(Zb2) + elif alternative == "less": + p = norm.cdf(Zb2) + else: + raise ValueError("alternative must be 'two-sided', 'greater', or 'less'") + + return Zb2, p + + def normaltest(self, alternative: str = "two-sided"): + """Perform D'Agostino and Pearson's omnibus test for normality. + + This method tests the null hypothesis that a sample comes from a normal + distribution. It combines skewness and kurtosis to produce an omnibus + test of normality. + + Parameters + ---------- + alternative : {'two-sided', 'less', 'greater'}, optional + Defines the alternative hypothesis used for the component skewness + and kurtosis tests. Default is 'two-sided'. The following options + are available: + + * 'two-sided': the distribution is different from normal + * 'less': used for the component tests + * 'greater': used for the component tests + + Returns + ------- + statistic : np.ndarray + The computed z-score for the normality test for each tally bin + pvalue : np.ndarray + The p-value for the hypothesis test for each tally bin + + Raises + ------ + ValueError + If the number of realizations is less than 20, or if an invalid + alternative hypothesis is specified. + + Notes + ----- + This test combines a test for skewness and a test for kurtosis to + produce an `omnibus test `_. + The test statistic is: + + .. math:: + + K^2 = Z_1^2 + Z_2^2 + + where :math:`Z_1` is the z-score from the skewness test and :math:`Z_2` + is the z-score from the kurtosis test. This statistic follows a + chi-square distribution with 2 degrees of freedom. + + The test requires at least 20 realizations to produce valid results. + + """ + n = self.num_realizations + if n < 20: + raise ValueError("normaltest requires n >= 20 (per D'Agostino-Pearson).") + + # Use the component tests + Z1, _ = self.skewtest(alternative) + Z2, _ = self.kurtosistest(alternative) + + # Combine as chi-square with df=2 since we have skewness and kurtosis + K2 = Z1*Z1 + Z2*Z2 + p = chi2.sf(K2, df=2) + return K2, p + @property def figure_of_merit(self): mean = self.mean std_dev = self.std_dev fom = np.zeros_like(mean) nonzero = np.abs(mean) > 0 - fom[nonzero] = 1.0 / ( - (std_dev[nonzero] / mean[nonzero])**2 * self._simulation_time) + rel_err = std_dev[nonzero] / mean[nonzero] + fom[nonzero] = 1.0 / (rel_err**2 * self._simulation_time) return fom @property @@ -528,6 +967,12 @@ class Tally(IDManagerMixin): if self._sum_sq is not None: self._sum_sq = sps.lil_matrix(self._sum_sq.flatten(), self._sum_sq.shape) + if self._sum_third is not None: + self._sum_third = sps.lil_matrix(self._sum_third.flatten(), + self._sum_third.shape) + if self._sum_fourth is not None: + self._sum_fourth = sps.lil_matrix(self._sum_fourth.flatten(), + self._sum_fourth.shape) if self._mean is not None: self._mean = sps.lil_matrix(self._mean.flatten(), self._mean.shape) @@ -543,6 +988,10 @@ class Tally(IDManagerMixin): self._sum = np.reshape(self._sum.toarray(), self.shape) if self._sum_sq is not None: self._sum_sq = np.reshape(self._sum_sq.toarray(), self.shape) + if self._sum_third is not None: + self._sum_third = np.reshape(self._sum_third.toarray(), self.shape) + if self._sum_fourth is not None: + self._sum_fourth = np.reshape(self._sum_fourth.toarray(), self.shape) if self._mean is not None: self._mean = np.reshape(self._mean.toarray(), self.shape) if self._std_dev is not None: @@ -869,6 +1318,34 @@ class Tally(IDManagerMixin): merged_tally._sum_sq = np.reshape(merged_sum_sq, merged_tally.shape) + # Concatenate sum_third arrays if present in both tallies + if self._sum_third is not None and other._sum_third is not None: + self_sum_third = self.get_reshaped_data(value="sum_third") + other_sum_third = other_copy.get_reshaped_data(value="sum_third") + + if join_right: + merged_sum_third = np.concatenate((self_sum_third, other_sum_third), + axis=merge_axis) + else: + merged_sum_third = np.concatenate((other_sum_third, self_sum_third), + axis=merge_axis) + + merged_tally._sum_third = np.reshape(merged_sum_third, merged_tally.shape) + + # Concatenate sum_fourth arrays if present in both tallies + if self._sum_fourth is not None and other._sum_fourth is not None: + self_sum_fourth = self.get_reshaped_data(value="sum_fourth") + other_sum_fourth = other_copy.get_reshaped_data(value="sum_fourth") + + if join_right: + merged_sum_fourth = np.concatenate((self_sum_fourth, other_sum_fourth), + axis=merge_axis) + else: + merged_sum_fourth = np.concatenate((other_sum_fourth, self_sum_fourth), + axis=merge_axis) + + merged_tally._sum_fourth = np.reshape(merged_sum_fourth, merged_tally.shape) + # Concatenate mean arrays if present in both tallies if self.mean is not None and other.mean is not None: self_mean = self.get_reshaped_data(value='mean') @@ -958,6 +1435,11 @@ class Tally(IDManagerMixin): subelement = ET.SubElement(element, "derivative") subelement.text = str(self.derivative.id) + # Optional higher moments accumulation + if self.higher_moments: + subelement = ET.SubElement(element, "higher_moments") + subelement.text = str(self.higher_moments).lower() + return element def add_results(self, statepoint: cv.PathLike | openmc.StatePoint): @@ -984,8 +1466,12 @@ class Tally(IDManagerMixin): # point are based on the current statepoint file self._sum = None self._sum_sq = None + self._sum_third = None + self._sum_fourth = None self._mean = None self._std_dev = None + self._vov = None + self._higher_moments = False self._num_realizations = 0 self._results_read = False @@ -1355,7 +1841,9 @@ class Tally(IDManagerMixin): (value == 'std_dev' and self.std_dev is None) or \ (value == 'rel_err' and self.mean is None) or \ (value == 'sum' and self.sum is None) or \ - (value == 'sum_sq' and self.sum_sq is None): + (value == 'sum_sq' and self.sum_sq is None) or \ + (value == "sum_third" and self.sum_third is None) or \ + (value == "sum_fourth" and self.sum_fourth is None): msg = f'The Tally ID="{self.id}" has no data to return' raise ValueError(msg) @@ -1378,10 +1866,14 @@ class Tally(IDManagerMixin): data = self.sum[indices] elif value == 'sum_sq': data = self.sum_sq[indices] + elif value == "sum_third": + data = self.sum_third[indices] + elif value == "sum_fourth": + data = self.sum_fourth[indices] else: msg = f'Unable to return results from Tally ID="{value}" since ' \ f'the requested value "{self.id}" is not \'mean\', ' \ - '\'std_dev\', \'rel_err\', \'sum\', or \'sum_sq\'' + '\'std_dev\', \'rel_err\', \'sum\', \'sum_sq\', \'sum_third\' or \'sum_fourth\'' raise LookupError(msg) return data @@ -2711,6 +3203,16 @@ class Tally(IDManagerMixin): new_sum_sq = self.get_values(scores, filters, filter_bins, nuclides, 'sum_sq') new_tally.sum_sq = new_sum_sq + if not self.derived and self._sum_third is not None: + new_sum_third = self.get_values( + scores, filters, filter_bins, nuclides, "sum_third" + ) + new_tally._sum_third = new_sum_third + if not self.derived and self._sum_fourth is not None: + new_sum_fourth = self.get_values( + scores, filters, filter_bins, nuclides, "sum_fourth" + ) + new_tally._sum_fourth = new_sum_fourth if self.mean is not None: new_mean = self.get_values(scores, filters, filter_bins, nuclides, 'mean') @@ -3151,6 +3653,12 @@ class Tally(IDManagerMixin): if not self.derived and self.sum_sq is not None: new_tally._sum_sq = np.zeros(new_tally.shape, dtype=np.float64) new_tally._sum_sq[diag_indices, :, :] = self.sum_sq + if not self.derived and self._sum_third is not None: + new_tally._sum_third = np.zeros(new_tally.shape, dtype=np.float64) + new_tally._sum_third[diag_indices, :, :] = self.sum_third + if not self.derived and self._sum_fourth is not None: + new_tally._sum_fourth = np.zeros(new_tally.shape, dtype=np.float64) + new_tally._sum_fourth[diag_indices, :, :] = self.sum_fourth if self.mean is not None: new_tally._mean = np.zeros(new_tally.shape, dtype=np.float64) new_tally._mean[diag_indices, :, :] = self.mean @@ -3201,43 +3709,17 @@ class Tallies(cv.CheckedList): if possible. Defaults to False. """ - if not isinstance(tally, Tally): - msg = f'Unable to add a non-Tally "{tally}" to the Tallies instance' - raise TypeError(msg) - if merge: - merged = False - # Look for a tally to merge with this one for i, tally2 in enumerate(self): - # If a mergeable tally is found if tally2.can_merge(tally): # Replace tally2 with the merged tally merged_tally = tally2.merge(tally) self[i] = merged_tally - merged = True - break + return - # If no mergeable tally was found, simply add this tally - if not merged: - super().append(tally) - - else: - super().append(tally) - - def insert(self, index, item): - """Insert tally before index - - Parameters - ---------- - index : int - Index in list - item : openmc.Tally - Tally to insert - - """ - super().insert(index, item) + super().append(tally) def merge_tallies(self): """Merge any mergeable tallies together. Note that n-way merges are diff --git a/openmc/tracks.py b/openmc/tracks.py index 61e5a72442..81646e7d2e 100644 --- a/openmc/tracks.py +++ b/openmc/tracks.py @@ -296,16 +296,16 @@ class Tracks(list): for state in pt.states: points.InsertNextPoint(state['r']) - # Create VTK line and assign points to line. - n = pt.states.size - line = vtk.vtkPolyLine() - line.GetPointIds().SetNumberOfIds(n) - for i in range(n): - line.GetPointIds().SetId(i, point_offset + i) - point_offset += n + # Create VTK line and assign points to line. + n = pt.states.size + line = vtk.vtkPolyLine() + line.GetPointIds().SetNumberOfIds(n) + for i in range(n): + line.GetPointIds().SetId(i, point_offset + i) + point_offset += n - # Add line to cell array - cells.InsertNextCell(line) + # Add line to cell array + cells.InsertNextCell(line) data = vtk.vtkPolyData() data.SetPoints(points) diff --git a/openmc/utility_funcs.py b/openmc/utility_funcs.py index da9f73b165..935a589853 100644 --- a/openmc/utility_funcs.py +++ b/openmc/utility_funcs.py @@ -3,6 +3,8 @@ import os from pathlib import Path from tempfile import TemporaryDirectory +import h5py + import openmc from .checkvalue import PathLike @@ -57,3 +59,20 @@ def input_path(filename: PathLike) -> Path: return Path(filename).resolve() else: return Path(filename) + + +@contextmanager +def h5py_file_or_group(group_or_filename: PathLike | h5py.Group, *args, **kwargs): + """Context manager for opening an HDF5 file or using an existing group + + Parameters + ---------- + group_or_filename : path-like or h5py.Group + Path to HDF5 file, or group from an existing HDF5 file + + """ + if isinstance(group_or_filename, h5py.Group): + yield group_or_filename + else: + with h5py.File(group_or_filename, *args, **kwargs) as f: + yield f diff --git a/pyproject.toml b/pyproject.toml index 6e8ed798e7..2d67e83401 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -41,15 +41,22 @@ dependencies = [ [project.optional-dependencies] depletion-mpi = ["mpi4py"] docs = [ - "sphinx==5.0.2", + "sphinx", "sphinxcontrib-katex", "sphinx-numfig", "jupyter", "sphinxcontrib-svg2pdfconverter", - "sphinx-rtd-theme==1.0.0" + "sphinx-rtd-theme" ] -test = ["packaging", "pytest", "pytest-cov", "colorama", "openpyxl"] -ci = ["cpp-coveralls", "coveralls"] +test = [ + "packaging", + "pytest", + "pytest-cov>=4.0", + "pytest-rerunfailures", + "colorama", + "openpyxl", +] +ci = ["coverage>=7.4", "gcovr>=7.2"] vtk = ["vtk"] [project.urls] diff --git a/src/bank.cpp b/src/bank.cpp index 9955939f6e..33790379b8 100644 --- a/src/bank.cpp +++ b/src/bank.cpp @@ -20,6 +20,8 @@ vector source_bank; SharedArray surf_source_bank; +SharedArray collision_track_bank; + // The fission bank is allocated as a SharedArray, rather than a vector, as it // will be shared by all threads in the simulation. It will be allocated to a // fixed maximum capacity in the init_fission_bank() function. Then, Elements @@ -50,6 +52,7 @@ void free_memory_bank() { simulation::source_bank.clear(); simulation::surf_source_bank.clear(); + simulation::collision_track_bank.clear(); simulation::fission_bank.clear(); simulation::progeny_per_particle.clear(); simulation::ifp_source_delayed_group_bank.clear(); @@ -79,16 +82,9 @@ void sort_fission_bank() // Perform exclusive scan summation to determine starting indices in fission // bank for each parent particle id - int64_t tmp = simulation::progeny_per_particle[0]; - simulation::progeny_per_particle[0] = 0; - for (int64_t i = 1; i < simulation::progeny_per_particle.size(); i++) { - int64_t value = simulation::progeny_per_particle[i - 1] + tmp; - tmp = simulation::progeny_per_particle[i]; - simulation::progeny_per_particle[i] = value; - } - - // TODO: C++17 introduces the exclusive_scan() function which could be - // used to replace everything above this point in this function. + std::exclusive_scan(simulation::progeny_per_particle.begin(), + simulation::progeny_per_particle.end(), + simulation::progeny_per_particle.begin(), 0); // We need a scratch vector to make permutation of the fission bank into // sorted order easy. Under normal usage conditions, the fission bank is diff --git a/src/boundary_condition.cpp b/src/boundary_condition.cpp index 7216ac8964..2840b3c7d5 100644 --- a/src/boundary_condition.cpp +++ b/src/boundary_condition.cpp @@ -158,63 +158,44 @@ void TranslationalPeriodicBC::handle_particle( // RotationalPeriodicBC implementation //============================================================================== -RotationalPeriodicBC::RotationalPeriodicBC(int i_surf, int j_surf) +RotationalPeriodicBC::RotationalPeriodicBC( + int i_surf, int j_surf, PeriodicAxis axis) : PeriodicBC(i_surf, j_surf) { Surface& surf1 {*model::surfaces[i_surf_]}; Surface& surf2 {*model::surfaces[j_surf_]}; - // Check the type of the first surface - bool surf1_is_xyplane; - if (const auto* ptr = dynamic_cast(&surf1)) { - surf1_is_xyplane = true; - } else if (const auto* ptr = dynamic_cast(&surf1)) { - surf1_is_xyplane = true; - } else if (const auto* ptr = dynamic_cast(&surf1)) { - surf1_is_xyplane = false; - } else { - throw std::invalid_argument(fmt::format( - "Surface {} is an invalid type for " - "rotational periodic BCs. Only x-planes, y-planes, or general planes " - "(that are perpendicular to z) are supported for these BCs.", - surf1.id_)); - } - - // Check the type of the second surface - bool surf2_is_xyplane; - if (const auto* ptr = dynamic_cast(&surf2)) { - surf2_is_xyplane = true; - } else if (const auto* ptr = dynamic_cast(&surf2)) { - surf2_is_xyplane = true; - } else if (const auto* ptr = dynamic_cast(&surf2)) { - surf2_is_xyplane = false; - } else { - throw std::invalid_argument(fmt::format( - "Surface {} is an invalid type for " - "rotational periodic BCs. Only x-planes, y-planes, or general planes " - "(that are perpendicular to z) are supported for these BCs.", - surf2.id_)); + // below convention for right handed coordinate system + switch (axis) { + case x: + zero_axis_idx_ = 0; // x component of plane must be zero + axis_1_idx_ = 1; // y component independent + axis_2_idx_ = 2; // z component dependent + break; + case y: + // for a right handed coordinate system, z should be the independent axis + // but this would cause the y-rotation case to be different than the other + // two. using a left handed coordinate system and a negative rotation the + // compute angle and rotation matrix behavior mimics that of the x and z + // cases + zero_axis_idx_ = 1; // y component of plane must be zero + axis_1_idx_ = 0; // x component independent + axis_2_idx_ = 2; // z component dependent + break; + case z: + zero_axis_idx_ = 2; // z component of plane must be zero + axis_1_idx_ = 0; // x component independent + axis_2_idx_ = 1; // y component dependent + break; + default: + throw std::invalid_argument( + fmt::format("You've specified an axis that is not x, y, or z.")); } // Compute the surface normal vectors and make sure they are perpendicular - // to the z-axis + // to the correct axis Direction norm1 = surf1.normal({0, 0, 0}); Direction norm2 = surf2.normal({0, 0, 0}); - if (std::abs(norm1.z) > FP_PRECISION) { - throw std::invalid_argument(fmt::format( - "Rotational periodic BCs are only " - "supported for rotations about the z-axis, but surface {} is not " - "perpendicular to the z-axis.", - surf1.id_)); - } - if (std::abs(norm2.z) > FP_PRECISION) { - throw std::invalid_argument(fmt::format( - "Rotational periodic BCs are only " - "supported for rotations about the z-axis, but surface {} is not " - "perpendicular to the z-axis.", - surf2.id_)); - } - // Make sure both surfaces intersect the origin if (std::abs(surf1.evaluate({0, 0, 0})) > FP_COINCIDENT) { throw std::invalid_argument(fmt::format( @@ -231,15 +212,8 @@ RotationalPeriodicBC::RotationalPeriodicBC(int i_surf, int j_surf) surf2.id_)); } - // Compute the BC rotation angle. Here it is assumed that both surface - // normal vectors point inwards---towards the valid geometry region. - // Consequently, the rotation angle is not the difference between the two - // normals, but is instead the difference between one normal and one - // anti-normal. (An incident ray on one surface must be an outgoing ray on - // the other surface after rotation hence the anti-normal.) - double theta1 = std::atan2(norm1.y, norm1.x); - double theta2 = std::atan2(norm2.y, norm2.x) + PI; - angle_ = theta2 - theta1; + angle_ = compute_periodic_rotation(norm1[axis_2_idx_], norm1[axis_1_idx_], + norm2[axis_2_idx_], norm2[axis_1_idx_]); // Warn the user if the angle does not evenly divide a circle double rem = std::abs(std::remainder((2 * PI / angle_), 1.0)); @@ -251,6 +225,20 @@ RotationalPeriodicBC::RotationalPeriodicBC(int i_surf, int j_surf) } } +double RotationalPeriodicBC::compute_periodic_rotation( + double rise_1, double run_1, double rise_2, double run_2) const +{ + // Compute the BC rotation angle. Here it is assumed that both surface + // normal vectors point inwards---towards the valid geometry region. + // Consequently, the rotation angle is not the difference between the two + // normals, but is instead the difference between one normal and one + // anti-normal. (An incident ray on one surface must be an outgoing ray on + // the other surface after rotation hence the anti-normal.) + double theta1 = std::atan2(rise_1, run_1); + double theta2 = std::atan2(rise_2, run_2) + PI; + return theta2 - theta1; +} + void RotationalPeriodicBC::handle_particle( Particle& p, const Surface& surf) const { @@ -278,10 +266,16 @@ void RotationalPeriodicBC::handle_particle( Direction u = p.u(); double cos_theta = std::cos(theta); double sin_theta = std::sin(theta); - Position new_r = { - cos_theta * r.x - sin_theta * r.y, sin_theta * r.x + cos_theta * r.y, r.z}; - Direction new_u = { - cos_theta * u.x - sin_theta * u.y, sin_theta * u.x + cos_theta * u.y, u.z}; + + Position new_r; + new_r[zero_axis_idx_] = r[zero_axis_idx_]; + new_r[axis_1_idx_] = cos_theta * r[axis_1_idx_] - sin_theta * r[axis_2_idx_]; + new_r[axis_2_idx_] = sin_theta * r[axis_1_idx_] + cos_theta * r[axis_2_idx_]; + + Direction new_u; + new_u[zero_axis_idx_] = u[zero_axis_idx_]; + new_u[axis_1_idx_] = cos_theta * u[axis_1_idx_] - sin_theta * u[axis_2_idx_]; + new_u[axis_2_idx_] = sin_theta * u[axis_1_idx_] + cos_theta * u[axis_2_idx_]; // Handle the effects of the surface albedo on the particle's weight. BoundaryCondition::handle_albedo(p, surf); diff --git a/src/cell.cpp b/src/cell.cpp index f7d077fb51..030ffcbb41 100644 --- a/src/cell.cpp +++ b/src/cell.cpp @@ -142,6 +142,25 @@ double Cell::temperature(int32_t instance) const } } +double Cell::density_mult(int32_t instance) const +{ + if (instance >= 0) { + return density_mult_.size() == 1 ? density_mult_.at(0) + : density_mult_.at(instance); + } else { + return density_mult_[0]; + } +} + +double Cell::density(int32_t instance) const +{ + const int32_t mat_index = material(instance); + if (mat_index == MATERIAL_VOID) + return 0.0; + + return density_mult(instance) * model::materials[mat_index]->density_gpcc(); +} + void Cell::set_temperature(double T, int32_t instance, bool set_contained) { if (settings::temperature_method == TemperatureMethod::INTERPOLATION) { @@ -192,6 +211,47 @@ void Cell::set_temperature(double T, int32_t instance, bool set_contained) } } +void Cell::set_density(double density, int32_t instance, bool set_contained) +{ + if (type_ != Fill::MATERIAL && !set_contained) { + fatal_error( + fmt::format("Attempted to set the density multiplier of cell {} " + "which is not filled by a material.", + id_)); + } + + if (type_ == Fill::MATERIAL) { + const int32_t mat_index = material(instance); + if (mat_index == MATERIAL_VOID) + return; + + if (instance >= 0) { + // If density multiplier vector is not big enough, resize it first + if (density_mult_.size() != n_instances()) + density_mult_.resize(n_instances(), density_mult_[0]); + + // Set density multiplier for the corresponding instance + density_mult_.at(instance) = + density / model::materials[mat_index]->density_gpcc(); + } else { + // Set density multiplier for all instances + for (auto& x : density_mult_) { + x = density / model::materials[mat_index]->density_gpcc(); + } + } + } else { + auto contained_cells = this->get_contained_cells(instance); + for (const auto& entry : contained_cells) { + auto& cell = model::cells[entry.first]; + assert(cell->type_ == Fill::MATERIAL); + auto& instances = entry.second; + for (auto instance : instances) { + cell->set_density(density, instance); + } + } + } +} + void Cell::export_properties_hdf5(hid_t group) const { // Create a group for this cell. @@ -203,6 +263,15 @@ void Cell::export_properties_hdf5(hid_t group) const temps.push_back(sqrtkT_val * sqrtkT_val / K_BOLTZMANN); write_dataset(cell_group, "temperature", temps); + // Write density for one or more cell instances + if (type_ == Fill::MATERIAL && material_.size() > 0) { + vector density; + for (int32_t i = 0; i < density_mult_.size(); ++i) + density.push_back(this->density(i)); + + write_dataset(cell_group, "density", density); + } + close_group(cell_group); } @@ -217,7 +286,7 @@ void Cell::import_properties_hdf5(hid_t group) // Ensure number of temperatures makes sense auto n_temps = temps.size(); if (n_temps > 1 && n_temps != n_instances()) { - throw std::runtime_error(fmt::format( + fatal_error(fmt::format( "Number of temperatures for cell {} doesn't match number of instances", id_)); } @@ -229,6 +298,25 @@ void Cell::import_properties_hdf5(hid_t group) this->set_temperature(temps[i], i); } + // Read densities + if (object_exists(cell_group, "density")) { + vector density; + read_dataset(cell_group, "density", density); + + // Ensure number of densities makes sense + auto n_density = density.size(); + if (n_density > 1 && n_density != n_instances()) { + fatal_error(fmt::format("Number of densities for cell {} " + "doesn't match number of instances", + id_)); + } + + // Set densities. + for (int32_t i = 0; i < n_density; ++i) { + this->set_density(density[i], i); + } + } + close_group(cell_group); } @@ -268,6 +356,8 @@ void Cell::to_hdf5(hid_t cell_group) const temps.push_back(sqrtkT_val * sqrtkT_val / K_BOLTZMANN); write_dataset(group, "temperature", temps); + write_dataset(group, "density_mult", density_mult_); + } else if (type_ == Fill::UNIVERSE) { write_dataset(group, "fill_type", "universe"); write_dataset(group, "fill", model::universes[fill_]->id_); @@ -412,6 +502,44 @@ CSGCell::CSGCell(pugi::xml_node cell_node) } } + // Read the density element which can be distributed similar to temperature. + // These get assigned to the density multiplier, requiring a division by + // the material density. + // Note: calculating the actual density multiplier is deferred until materials + // are finalized. density_mult_ contains the true density in the meantime. + if (check_for_node(cell_node, "density")) { + density_mult_ = get_node_array(cell_node, "density"); + density_mult_.shrink_to_fit(); + + // Make sure this is a material-filled cell. + if (material_.size() == 0) { + fatal_error(fmt::format( + "Cell {} was specified with a density but no material. Density" + "specification is only valid for cells filled with a material.", + id_)); + } + + // Make sure this is a non-void material. + for (auto mat_id : material_) { + if (mat_id == MATERIAL_VOID) { + fatal_error(fmt::format( + "Cell {} was specified with a density, but contains a void " + "material. Density specification is only valid for cells " + "filled with a non-void material.", + id_)); + } + } + + // Make sure all densities are non-negative and greater than zero. + for (auto rho : density_mult_) { + if (rho <= 0) { + fatal_error(fmt::format( + "Cell {} was specified with a density less than or equal to zero", + id_)); + } + } + } + // Read the region specification. std::string region_spec; if (check_for_node(cell_node, "region")) { @@ -1315,6 +1443,24 @@ extern "C" int openmc_cell_set_temperature( return 0; } +extern "C" int openmc_cell_set_density( + int32_t index, double density, const int32_t* instance, bool set_contained) +{ + if (index < 0 || index >= model::cells.size()) { + strcpy(openmc_err_msg, "Index in cells array is out of bounds."); + return OPENMC_E_OUT_OF_BOUNDS; + } + + int32_t instance_index = instance ? *instance : -1; + try { + model::cells[index]->set_density(density, instance_index, set_contained); + } catch (const std::exception& e) { + set_errmsg(e.what()); + return OPENMC_E_UNASSIGNED; + } + return 0; +} + extern "C" int openmc_cell_get_temperature( int32_t index, const int32_t* instance, double* T) { @@ -1333,6 +1479,36 @@ extern "C" int openmc_cell_get_temperature( return 0; } +extern "C" int openmc_cell_get_density( + int32_t index, const int32_t* instance, double* density) +{ + if (index < 0 || index >= model::cells.size()) { + strcpy(openmc_err_msg, "Index in cells array is out of bounds."); + return OPENMC_E_OUT_OF_BOUNDS; + } + + int32_t instance_index = instance ? *instance : -1; + try { + if (model::cells[index]->type_ != Fill::MATERIAL) { + fatal_error( + fmt::format("Cell {}, instance {} is not filled with a material.", + model::cells[index]->id_, instance_index)); + } + + int32_t mat_index = model::cells[index]->material(instance_index); + if (mat_index == MATERIAL_VOID) { + *density = 0.0; + } else { + *density = model::cells[index]->density_mult(instance_index) * + model::materials[mat_index]->density_gpcc(); + } + } catch (const std::exception& e) { + set_errmsg(e.what()); + return OPENMC_E_UNASSIGNED; + } + return 0; +} + //! Get the bounding box of a cell extern "C" int openmc_cell_bounding_box( const int32_t index, double* llc, double* urc) diff --git a/src/collision_track.cpp b/src/collision_track.cpp new file mode 100644 index 0000000000..03cbc32b7b --- /dev/null +++ b/src/collision_track.cpp @@ -0,0 +1,238 @@ +#include "openmc/collision_track.h" + +#include +#include + +#include + +#include "openmc/bank.h" +#include "openmc/bank_io.h" +#include "openmc/cell.h" +#include "openmc/constants.h" +#include "openmc/error.h" +#include "openmc/file_utils.h" +#include "openmc/hdf5_interface.h" +#include "openmc/material.h" +#include "openmc/mcpl_interface.h" +#include "openmc/message_passing.h" +#include "openmc/nuclide.h" +#include "openmc/output.h" +#include "openmc/particle.h" +#include "openmc/settings.h" +#include "openmc/simulation.h" +#include "openmc/universe.h" + +#ifdef OPENMC_MPI +#include +#endif + +namespace openmc { + +namespace { + +hid_t h5_collision_track_banktype() +{ + hid_t postype = H5Tcreate(H5T_COMPOUND, sizeof(Position)); + H5Tinsert(postype, "x", HOFFSET(Position, x), H5T_NATIVE_DOUBLE); + H5Tinsert(postype, "y", HOFFSET(Position, y), H5T_NATIVE_DOUBLE); + H5Tinsert(postype, "z", HOFFSET(Position, z), H5T_NATIVE_DOUBLE); + + hid_t banktype = H5Tcreate(H5T_COMPOUND, sizeof(CollisionTrackSite)); + + H5Tinsert(banktype, "r", HOFFSET(CollisionTrackSite, r), postype); + H5Tinsert(banktype, "u", HOFFSET(CollisionTrackSite, u), postype); + H5Tinsert(banktype, "E", HOFFSET(CollisionTrackSite, E), H5T_NATIVE_DOUBLE); + H5Tinsert(banktype, "dE", HOFFSET(CollisionTrackSite, dE), H5T_NATIVE_DOUBLE); + H5Tinsert( + banktype, "time", HOFFSET(CollisionTrackSite, time), H5T_NATIVE_DOUBLE); + H5Tinsert( + banktype, "wgt", HOFFSET(CollisionTrackSite, wgt), H5T_NATIVE_DOUBLE); + H5Tinsert(banktype, "event_mt", HOFFSET(CollisionTrackSite, event_mt), + H5T_NATIVE_INT); + H5Tinsert(banktype, "delayed_group", + HOFFSET(CollisionTrackSite, delayed_group), H5T_NATIVE_INT); + H5Tinsert( + banktype, "cell_id", HOFFSET(CollisionTrackSite, cell_id), H5T_NATIVE_INT); + H5Tinsert(banktype, "nuclide_id", HOFFSET(CollisionTrackSite, nuclide_id), + H5T_NATIVE_INT); + H5Tinsert(banktype, "material_id", HOFFSET(CollisionTrackSite, material_id), + H5T_NATIVE_INT); + H5Tinsert(banktype, "universe_id", HOFFSET(CollisionTrackSite, universe_id), + H5T_NATIVE_INT); + H5Tinsert(banktype, "n_collision", HOFFSET(CollisionTrackSite, n_collision), + H5T_NATIVE_INT); + H5Tinsert(banktype, "particle", HOFFSET(CollisionTrackSite, particle), + H5T_NATIVE_INT); + H5Tinsert(banktype, "parent_id", HOFFSET(CollisionTrackSite, parent_id), + H5T_NATIVE_INT64); + H5Tinsert(banktype, "progeny_id", HOFFSET(CollisionTrackSite, progeny_id), + H5T_NATIVE_INT64); + H5Tclose(postype); + return banktype; +} + +void write_collision_track_bank(hid_t group_id, + openmc::span collision_track_bank, + const openmc::vector& bank_index) +{ + hid_t banktype = h5_collision_track_banktype(); +#ifdef OPENMC_MPI + write_bank_dataset("collision_track_bank", group_id, collision_track_bank, + bank_index, banktype, banktype, mpi::collision_track_site); +#else + write_bank_dataset("collision_track_bank", group_id, collision_track_bank, + bank_index, banktype, banktype); +#endif + + H5Tclose(banktype); +} + +void write_h5_collision_track(const char* filename, + openmc::span collision_track_bank, + const openmc::vector& bank_index) +{ +#ifdef PHDF5 + bool parallel = true; +#else + bool parallel = false; +#endif + + if (!filename) + fatal_error("write_h5_collision_track filename needs a nonempty name."); + + std::string filename_(filename); + const auto extension = get_file_extension(filename_); + if (extension.empty()) { + filename_.append(".h5"); + } else if (extension != "h5") { + warning("write_h5_collision_track was passed a file extension differing " + "from .h5, but an hdf5 file will be written."); + } + + hid_t file_id; + if (mpi::master || parallel) { + file_id = file_open(filename_.c_str(), 'w', true); + + // Write filetype and version info + write_attribute(file_id, "filetype", "collision_track"); + write_attribute(file_id, "version", VERSION_COLLISION_TRACK); + } + + write_collision_track_bank(file_id, collision_track_bank, bank_index); + + if (mpi::master || parallel) + file_close(file_id); +} + +} // namespace + +bool should_record_event(int id_cell, int mt_event, const std::string& nuclide, + int id_universe, int id_material, double energy_loss) +{ + auto matches_filter = [](const auto& filter_set, const auto& value) { + return filter_set.empty() || filter_set.count(value) > 0; + }; + + const auto& cfg = settings::collision_track_config; + return simulation::current_batch > settings::n_inactive && + !simulation::collision_track_bank.full() && + matches_filter(cfg.cell_ids, id_cell) && + matches_filter(cfg.mt_numbers, mt_event) && + matches_filter(cfg.universe_ids, id_universe) && + matches_filter(cfg.material_ids, id_material) && + matches_filter(cfg.nuclides, nuclide) && + (cfg.deposited_energy_threshold == 0 || + cfg.deposited_energy_threshold < energy_loss); +} + +void collision_track_reserve_bank() +{ + simulation::collision_track_bank.reserve( + settings::collision_track_config.max_collisions); +} + +void collision_track_flush_bank() +{ + const auto& cfg = settings::collision_track_config; + if (simulation::ct_current_file > cfg.max_files) + return; + + bool last_batch = (simulation::current_batch == settings::n_batches); + if (!simulation::collision_track_bank.full() && !last_batch) + return; + + auto size = simulation::collision_track_bank.size(); + if (size == 0 && !last_batch) + return; + + auto collision_track_work_index = mpi::calculate_parallel_index_vector(size); + openmc::span collisiontrackbankspan( + simulation::collision_track_bank.begin(), size); + + std::string ext = cfg.mcpl_write ? "mcpl" : "h5"; + auto filename = fmt::format("{}collision_track.{}.{}", settings::path_output, + simulation::ct_current_file, ext); + + if (cfg.max_files == 1 || (simulation::ct_current_file == 1 && last_batch)) { + filename = settings::path_output + "collision_track." + ext; + } + write_message("Creating {}...", filename, 4); + + if (cfg.mcpl_write) { + write_mcpl_collision_track( + filename.c_str(), collisiontrackbankspan, collision_track_work_index); + } else { + write_h5_collision_track( + filename.c_str(), collisiontrackbankspan, collision_track_work_index); + } + + simulation::collision_track_bank.clear(); + if (!last_batch && cfg.max_files >= 1) { + collision_track_reserve_bank(); + } + ++simulation::ct_current_file; +} + +void collision_track_record(Particle& particle) +{ + int cell_index = particle.lowest_coord().cell(); + if (cell_index == C_NONE) + return; + + int cell_id = model::cells[cell_index]->id_; + const auto* nuclide_ptr = data::nuclides[particle.event_nuclide()].get(); + std::string nuclide = nuclide_ptr->name_; + int universe_id = model::universes[particle.lowest_coord().universe()]->id_; + double delta_E = particle.E_last() - particle.E(); + int material_index = particle.material(); + if (material_index == C_NONE) + return; + + int material_id = model::materials[material_index]->id_; + + if (!should_record_event(cell_id, particle.event_mt(), nuclide, universe_id, + material_id, delta_E)) + return; + + CollisionTrackSite site; + site.r = particle.r(); + site.u = particle.u(); + site.E = particle.E_last(); + site.dE = delta_E; + site.time = particle.time(); + site.wgt = particle.wgt(); + site.event_mt = particle.event_mt(); + site.delayed_group = particle.delayed_group(); + site.cell_id = cell_id; + site.nuclide_id = + 10000 * nuclide_ptr->Z_ + 10 * nuclide_ptr->A_ + nuclide_ptr->metastable_; + site.material_id = material_id; + site.universe_id = universe_id; + site.n_collision = particle.n_collision(); + site.particle = particle.type(); + site.parent_id = particle.id(); + site.progeny_id = particle.n_progeny(); + simulation::collision_track_bank.thread_safe_append(site); +} + +} // namespace openmc diff --git a/src/distribution_multi.cpp b/src/distribution_multi.cpp index b7b3efe526..cdb33adc2a 100644 --- a/src/distribution_multi.cpp +++ b/src/distribution_multi.cpp @@ -58,6 +58,15 @@ PolarAzimuthal::PolarAzimuthal(Direction u, UPtrDist mu, UPtrDist phi) PolarAzimuthal::PolarAzimuthal(pugi::xml_node node) : UnitSphereDistribution {node} { + // Read reference directional unit vector + if (check_for_node(node, "reference_vwu")) { + auto v_ref = get_node_array(node, "reference_vwu"); + if (v_ref.size() != 3) + fatal_error("Angular distribution reference v direction must have " + "three parameters specified."); + v_ref_ = Direction(v_ref.data()); + } + w_ref_ = u_ref_.cross(v_ref_); if (check_for_node(node, "mu")) { pugi::xml_node node_dist = node.child("mu"); mu_ = distribution_from_xml(node_dist); @@ -79,11 +88,15 @@ Direction PolarAzimuthal::sample(uint64_t* seed) const double mu = mu_->sample(seed); if (mu == 1.0) return u_ref_; + if (mu == -1.0) + return -u_ref_; // Sample azimuthal angle double phi = phi_->sample(seed); - return rotate_angle(u_ref_, mu, &phi, seed); + double f = std::sqrt(1 - mu * mu); + + return mu * u_ref_ + f * std::cos(phi) * v_ref_ + f * std::sin(phi) * w_ref_; } //============================================================================== diff --git a/src/eigenvalue.cpp b/src/eigenvalue.cpp index 2685bbe98a..8412cbd3b4 100644 --- a/src/eigenvalue.cpp +++ b/src/eigenvalue.cpp @@ -127,30 +127,8 @@ void synchronize_bank() "No fission sites banked on MPI rank " + std::to_string(mpi::rank)); } - // Make sure all processors start at the same point for random sampling. Then - // skip ahead in the sequence using the starting index in the 'global' - // fission bank for each processor. - - int64_t id = simulation::total_gen + overall_generation(); - uint64_t seed = init_seed(id, STREAM_TRACKING); - advance_prn_seed(start, &seed); - - // Determine how many fission sites we need to sample from the source bank - // and the probability for selecting a site. - - int64_t sites_needed; - if (total < settings::n_particles) { - sites_needed = settings::n_particles % total; - } else { - sites_needed = settings::n_particles; - } - double p_sample = static_cast(sites_needed) / total; - simulation::time_bank_sample.start(); - // ========================================================================== - // SAMPLE N_PARTICLES FROM FISSION BANK AND PLACE IN TEMP_SITES - // Allocate temporary source bank -- we don't really know how many fission // sites were created, so overallocate by a factor of 3 int64_t index_temp = 0; @@ -165,33 +143,38 @@ void synchronize_bank() temp_delayed_groups, temp_lifetimes, 3 * simulation::work_per_rank); } - for (int64_t i = 0; i < simulation::fission_bank.size(); i++) { - const auto& site = simulation::fission_bank[i]; + // ========================================================================== + // SAMPLE N_PARTICLES FROM FISSION BANK AND PLACE IN TEMP_SITES - // If there are less than n_particles particles banked, automatically add - // int(n_particles/total) sites to temp_sites. For example, if you need - // 1000 and 300 were banked, this would add 3 source sites per banked site - // and the remaining 100 would be randomly sampled. - if (total < settings::n_particles) { - for (int64_t j = 1; j <= settings::n_particles / total; ++j) { - temp_sites[index_temp] = site; - if (settings::ifp_on) { - copy_ifp_data_from_fission_banks( - i, temp_delayed_groups[index_temp], temp_lifetimes[index_temp]); - } - ++index_temp; - } - } + // We use Uniform Combing method to exactly get the targeted particle size + // [https://doi.org/10.1080/00295639.2022.2091906] - // Randomly sample sites needed - if (prn(&seed) < p_sample) { - temp_sites[index_temp] = site; - if (settings::ifp_on) { - copy_ifp_data_from_fission_banks( - i, temp_delayed_groups[index_temp], temp_lifetimes[index_temp]); - } - ++index_temp; + // Make sure all processors use the same random number seed. + int64_t id = simulation::total_gen + overall_generation(); + uint64_t seed = init_seed(id, STREAM_TRACKING); + + // Comb specification + double teeth_distance = static_cast(total) / settings::n_particles; + double teeth_offset = prn(&seed) * teeth_distance; + + // First and last hitting tooth + int64_t end = start + simulation::fission_bank.size(); + int64_t tooth_start = std::ceil((start - teeth_offset) / teeth_distance); + int64_t tooth_end = std::floor((end - teeth_offset) / teeth_distance) + 1; + + // Locally comb particles in fission_bank + double tooth = tooth_start * teeth_distance + teeth_offset; + for (int64_t i = tooth_start; i < tooth_end; i++) { + int64_t idx = std::floor(tooth) - start; + temp_sites[index_temp] = simulation::fission_bank[idx]; + if (settings::ifp_on) { + copy_ifp_data_from_fission_banks( + idx, temp_delayed_groups[index_temp], temp_lifetimes[index_temp]); } + ++index_temp; + + // Next tooth + tooth += teeth_distance; } // At this point, the sampling of source sites is done and now we need to @@ -217,37 +200,6 @@ void synchronize_bank() finish = index_temp; #endif - // Now that the sampling is complete, we need to ensure that we have exactly - // n_particles source sites. The way this is done in a reproducible manner is - // to adjust only the source sites on the last processor. - - if (mpi::rank == mpi::n_procs - 1) { - if (finish > settings::n_particles) { - // If we have extra sites sampled, we will simply discard the extra - // ones on the last processor - index_temp = settings::n_particles - start; - - } else if (finish < settings::n_particles) { - // If we have too few sites, repeat sites from the very end of the - // fission bank - sites_needed = settings::n_particles - finish; - // TODO: sites_needed > simulation::fission_bank.size() or other test to - // make sure we don't need info from other proc - for (int i = 0; i < sites_needed; ++i) { - int i_bank = simulation::fission_bank.size() - sites_needed + i; - temp_sites[index_temp] = simulation::fission_bank[i_bank]; - if (settings::ifp_on) { - copy_ifp_data_from_fission_banks(i_bank, - temp_delayed_groups[index_temp], temp_lifetimes[index_temp]); - } - ++index_temp; - } - } - - // the last processor should not be sending sites to right - finish = simulation::work_index[mpi::rank + 1]; - } - simulation::time_bank_sample.stop(); simulation::time_bank_sendrecv.start(); @@ -451,6 +403,16 @@ void calculate_average_keff() t_value * std::sqrt( (simulation::k_sum[1] / n - std::pow(simulation::keff, 2)) / (n - 1)); + + // In some cases (such as an infinite medium problem), random ray + // may estimate k exactly and in an unvarying manner between iterations. + // In this case, the floating point roundoff between the division and the + // power operations may cause an extremely small negative value to occur + // inside the sqrt operation, leading to NaN. If this occurs, we check for + // it and set the std dev to zero. + if (!std::isfinite(simulation::keff_std)) { + simulation::keff_std = 0.0; + } } } } diff --git a/src/event.cpp b/src/event.cpp index aa3987504b..f33e132d0a 100644 --- a/src/event.cpp +++ b/src/event.cpp @@ -1,4 +1,5 @@ #include "openmc/event.h" + #include "openmc/material.h" #include "openmc/simulation.h" #include "openmc/timer.h" @@ -73,17 +74,17 @@ void process_calculate_xs_events(SharedArray& queue) { simulation::time_event_calculate_xs.start(); - // TODO: If using C++17, perform a parallel sort of the queue - // by particle type, material type, and then energy, in order to - // improve cache locality and reduce thread divergence on GPU. Prior - // to C++17, std::sort is a serial only operation, which in this case - // makes it too slow to be practical for most test problems. + // TODO: If using C++17, we could perform a parallel sort of the queue by + // particle type, material type, and then energy, in order to improve cache + // locality and reduce thread divergence on GPU. However, the parallel + // algorithms typically require linking against an additional library (Intel + // TBB). Prior to C++17, std::sort is a serial only operation, which in this + // case makes it too slow to be practical for most test problems. // // std::sort(std::execution::par_unseq, queue.data(), queue.data() + // queue.size()); int64_t offset = simulation::advance_particle_queue.size(); - ; #pragma omp parallel for schedule(runtime) for (int64_t i = 0; i < queue.size(); i++) { diff --git a/src/finalize.cpp b/src/finalize.cpp index e38b0b251c..344eaa1a0a 100644 --- a/src/finalize.cpp +++ b/src/finalize.cpp @@ -3,6 +3,7 @@ #include "openmc/bank.h" #include "openmc/capi.h" #include "openmc/cmfd_solver.h" +#include "openmc/collision_track.h" #include "openmc/constants.h" #include "openmc/cross_sections.h" #include "openmc/dagmc.h" @@ -76,6 +77,7 @@ int openmc_finalize() // Reset global variables settings::assume_separate = false; settings::check_overlaps = false; + settings::collision_track_config = CollisionTrackConfig {}; settings::confidence_intervals = false; settings::create_fission_neutrons = true; settings::create_delayed_neutrons = true; @@ -85,6 +87,7 @@ int openmc_finalize() settings::time_cutoff = {INFTY, INFTY, INFTY, INFTY}; settings::entropy_on = false; settings::event_based = false; + settings::free_gas_threshold = 400.0; settings::gen_per_batch = 1; settings::legendre_to_tabular = true; settings::legendre_to_tabular_points = -1; @@ -92,6 +95,7 @@ int openmc_finalize() settings::max_lost_particles = 10; settings::max_order = 0; settings::max_particles_in_flight = 100000; + settings::max_secondaries = 10000; settings::max_particle_events = 1'000'000; settings::max_history_splits = 10'000'000; settings::max_tracks = 1000; @@ -138,7 +142,7 @@ int openmc_finalize() settings::uniform_source_sampling = false; settings::ufs_on = false; settings::urr_ptables_on = true; - settings::verbosity = 7; + settings::verbosity = -1; settings::weight_cutoff = 0.25; settings::weight_survive = 1.0; settings::weight_windows_file.clear(); @@ -154,8 +158,8 @@ int openmc_finalize() simulation::entropy_mesh = nullptr; simulation::ufs_mesh = nullptr; - data::energy_max = {INFTY, INFTY}; - data::energy_min = {0.0, 0.0}; + data::energy_max = {INFTY, INFTY, INFTY, INFTY}; + data::energy_min = {0.0, 0.0, 0.0, 0.0}; data::temperature_min = 0.0; data::temperature_max = INFTY; model::root_universe = -1; @@ -175,6 +179,9 @@ int openmc_finalize() if (mpi::source_site != MPI_DATATYPE_NULL) { MPI_Type_free(&mpi::source_site); } + if (mpi::collision_track_site != MPI_DATATYPE_NULL) { + MPI_Type_free(&mpi::collision_track_site); + } #endif openmc_reset_random_ray(); diff --git a/src/geometry.cpp b/src/geometry.cpp index f32b63ed7a..e8c306ecf2 100644 --- a/src/geometry.cpp +++ b/src/geometry.cpp @@ -172,11 +172,13 @@ bool find_cell_inner( p.cell_instance() = cell_instance_at_level(p, p.n_coord() - 1); } - // Set the material and temperature. + // Set the material, temperature and density multiplier. p.material_last() = p.material(); p.material() = c.material(p.cell_instance()); p.sqrtkT_last() = p.sqrtkT(); p.sqrtkT() = c.sqrtkT(p.cell_instance()); + p.density_mult_last() = p.density_mult(); + p.density_mult() = c.density_mult(p.cell_instance()); return true; diff --git a/src/geometry_aux.cpp b/src/geometry_aux.cpp index 51732cf8b9..8a145fb1f1 100644 --- a/src/geometry_aux.cpp +++ b/src/geometry_aux.cpp @@ -195,6 +195,24 @@ void assign_temperatures() //============================================================================== +void finalize_cell_densities() +{ + for (auto& c : model::cells) { + // Convert to density multipliers. + if (!c->density_mult_.empty()) { + for (int32_t instance = 0; instance < c->density_mult_.size(); + ++instance) { + c->density_mult_[instance] /= + model::materials[c->material(instance)]->density_gpcc(); + } + } else { + c->density_mult_ = {1.0}; + } + } +} + +//============================================================================== + void get_temperatures( vector>& nuc_temps, vector>& thermal_temps) { @@ -362,6 +380,17 @@ void prepare_distribcell(const std::vector* user_distribcells) c.id_, c.sqrtkT_.size(), c.n_instances())); } } + + if (c.density_mult_.size() > 1) { + if (c.density_mult_.size() != c.n_instances()) { + fatal_error(fmt::format("Cell {} was specified with {} density " + "multipliers but has {} distributed " + "instances. The number of density multipliers " + "must equal one or the number " + "of instances.", + c.id_, c.density_mult_.size(), c.n_instances())); + } + } } // Search through universes for material cells and assign each one a diff --git a/src/hdf5_interface.cpp b/src/hdf5_interface.cpp index e90aa74901..c56d485e28 100644 --- a/src/hdf5_interface.cpp +++ b/src/hdf5_interface.cpp @@ -225,8 +225,7 @@ void get_name(hid_t obj_id, std::string& name) { size_t size = 1 + H5Iget_name(obj_id, nullptr, 0); name.resize(size); - // TODO: switch to name.data() when using C++17 - H5Iget_name(obj_id, &name[0], size); + H5Iget_name(obj_id, name.data(), size); } int get_num_datasets(hid_t group_id) @@ -537,14 +536,14 @@ void read_complex( H5Tclose(complex_id); } -void read_tally_results( - hid_t group_id, hsize_t n_filter, hsize_t n_score, double* results) +void read_tally_results(hid_t group_id, hsize_t n_filter, hsize_t n_score, + hsize_t n_results, double* results) { // Create dataspace for hyperslab in memory constexpr int ndim = 3; - hsize_t dims[ndim] {n_filter, n_score, 3}; + hsize_t dims[ndim] {n_filter, n_score, n_results}; hsize_t start[ndim] {0, 0, 1}; - hsize_t count[ndim] {n_filter, n_score, 2}; + hsize_t count[ndim] {n_filter, n_score, n_results - 1}; hid_t memspace = H5Screate_simple(ndim, dims, nullptr); H5Sselect_hyperslab(memspace, H5S_SELECT_SET, start, nullptr, count, nullptr); @@ -687,15 +686,15 @@ void write_string( group_id, 0, nullptr, buffer.length(), name, buffer.c_str(), indep); } -void write_tally_results( - hid_t group_id, hsize_t n_filter, hsize_t n_score, const double* results) +void write_tally_results(hid_t group_id, hsize_t n_filter, hsize_t n_score, + hsize_t n_results, const double* results) { // Set dimensions of sum/sum_sq hyperslab to store constexpr int ndim = 3; - hsize_t count[ndim] {n_filter, n_score, 2}; + hsize_t count[ndim] {n_filter, n_score, n_results - 1}; // Set dimensions of results array - hsize_t dims[ndim] {n_filter, n_score, 3}; + hsize_t dims[ndim] {n_filter, n_score, n_results}; hsize_t start[ndim] {0, 0, 1}; hid_t memspace = H5Screate_simple(ndim, dims, nullptr); H5Sselect_hyperslab(memspace, H5S_SELECT_SET, start, nullptr, count, nullptr); diff --git a/src/ifp.cpp b/src/ifp.cpp index 1f81f26f6e..cc4a76538b 100644 --- a/src/ifp.cpp +++ b/src/ifp.cpp @@ -28,13 +28,13 @@ bool is_generation_time_or_both() return false; } -void ifp(const Particle& p, const SourceSite& site, int64_t idx) +void ifp(const Particle& p, int64_t idx) { if (is_beta_effective_or_both()) { const auto& delayed_groups = simulation::ifp_source_delayed_group_bank[p.current_work() - 1]; simulation::ifp_fission_delayed_group_bank[idx] = - _ifp(site.delayed_group, delayed_groups); + _ifp(p.delayed_group(), delayed_groups); } if (is_generation_time_or_both()) { const auto& lifetimes = diff --git a/src/initialize.cpp b/src/initialize.cpp index 2da78137d1..a2269ed1ea 100644 --- a/src/initialize.cpp +++ b/src/initialize.cpp @@ -178,6 +178,37 @@ void initialize_mpi(MPI_Comm intracomm) MPI_DOUBLE, MPI_INT, MPI_INT, MPI_INT, MPI_INT, MPI_LONG, MPI_LONG}; MPI_Type_create_struct(11, blocks, disp, types, &mpi::source_site); MPI_Type_commit(&mpi::source_site); + + CollisionTrackSite bc; + MPI_Aint dispc[16]; + MPI_Get_address(&bc.r, &dispc[0]); // double + MPI_Get_address(&bc.u, &dispc[1]); // double + MPI_Get_address(&bc.E, &dispc[2]); // double + MPI_Get_address(&bc.dE, &dispc[3]); // double + MPI_Get_address(&bc.time, &dispc[4]); // double + MPI_Get_address(&bc.wgt, &dispc[5]); // double + MPI_Get_address(&bc.event_mt, &dispc[6]); // int + MPI_Get_address(&bc.delayed_group, &dispc[7]); // int + MPI_Get_address(&bc.cell_id, &dispc[8]); // int + MPI_Get_address(&bc.nuclide_id, &dispc[9]); // int + MPI_Get_address(&bc.material_id, &dispc[10]); // int + MPI_Get_address(&bc.universe_id, &dispc[11]); // int + MPI_Get_address(&bc.n_collision, &dispc[12]); // int + MPI_Get_address(&bc.particle, &dispc[13]); // int + MPI_Get_address(&bc.parent_id, &dispc[14]); // int64_t + MPI_Get_address(&bc.progeny_id, &dispc[15]); // int64_t + for (int i = 15; i >= 0; --i) { + dispc[i] -= dispc[0]; + } + + int blocksc[] = {3, 3, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; + MPI_Datatype typesc[] = {MPI_DOUBLE, MPI_DOUBLE, MPI_DOUBLE, MPI_DOUBLE, + MPI_DOUBLE, MPI_DOUBLE, MPI_INT, MPI_INT, MPI_INT, MPI_INT, MPI_INT, + MPI_INT, MPI_INT, MPI_INT, MPI_INT64_T, MPI_INT64_T}; + + MPI_Type_create_struct( + 16, blocksc, dispc, typesc, &mpi::collision_track_site); + MPI_Type_commit(&mpi::collision_track_site); } #endif // OPENMC_MPI @@ -195,6 +226,15 @@ int parse_command_line(int argc, char* argv[]) i += 1; settings::n_particles = std::stoll(argv[i]); + } else if (arg == "-q" || arg == "--verbosity") { + i += 1; + settings::verbosity = std::stoi(argv[i]); + if (settings::verbosity > 10 || settings::verbosity < 1) { + auto msg = fmt::format("Invalid verbosity: {}.", settings::verbosity); + strcpy(openmc_err_msg, msg.c_str()); + return OPENMC_E_INVALID_ARGUMENT; + } + } else if (arg == "-e" || arg == "--event") { settings::event_based = true; } else if (arg == "-r" || arg == "--restart") { @@ -345,8 +385,10 @@ bool read_model_xml() auto settings_root = root.child("settings"); // Verbosity - if (check_for_node(settings_root, "verbosity")) { + if (check_for_node(settings_root, "verbosity") && settings::verbosity == -1) { settings::verbosity = std::stoi(get_node_value(settings_root, "verbosity")); + } else if (settings::verbosity == -1) { + settings::verbosity = 7; } // To this point, we haven't displayed any output since we didn't know what @@ -401,6 +443,10 @@ bool read_model_xml() // Finalize cross sections having assigned temperatures finalize_cross_sections(); + // Compute cell density multipliers now that material densities + // have been finalized (from geometry_aux.h) + finalize_cell_densities(); + if (check_for_node(root, "tallies")) read_tallies_xml(root.child("tallies")); @@ -441,6 +487,11 @@ void read_separate_xml_files() // Finalize cross sections having assigned temperatures finalize_cross_sections(); + + // Compute cell density multipliers now that material densities + // have been finalized (from geometry_aux.h) + finalize_cell_densities(); + read_tallies_xml(); // Initialize distribcell_filters diff --git a/src/material.cpp b/src/material.cpp index 32384ddf12..54caa38409 100644 --- a/src/material.cpp +++ b/src/material.cpp @@ -890,7 +890,7 @@ void Material::calculate_neutron_xs(Particle& p) const // ADD TO MACROSCOPIC CROSS SECTION // Copy atom density of nuclide in material - double atom_density = atom_density_(i); + double atom_density = this->atom_density(i, p.density_mult()); // Add contributions to cross sections p.macro_xs().total += atom_density * micro.total; @@ -925,7 +925,7 @@ void Material::calculate_photon_xs(Particle& p) const // ADD TO MACROSCOPIC CROSS SECTION // Copy atom density of nuclide in material - double atom_density = atom_density_(i); + double atom_density = this->atom_density(i, p.density_mult()); // Add contributions to material macroscopic cross sections p.macro_xs().total += atom_density * micro.total; diff --git a/src/mcpl_interface.cpp b/src/mcpl_interface.cpp index b8e7807100..256f3343fc 100644 --- a/src/mcpl_interface.cpp +++ b/src/mcpl_interface.cpp @@ -18,6 +18,7 @@ #include #include #include +#include #include #include @@ -61,6 +62,8 @@ using mcpl_hdr_nparticles_fpt = uint64_t (*)(mcpl_file_t* file_handle); using mcpl_read_fpt = const mcpl_particle_repr_t* (*)(mcpl_file_t* file_handle); using mcpl_close_file_fpt = void (*)(mcpl_file_t* file_handle); +using mcpl_hdr_add_data_fpt = void (*)(mcpl_outfile_t* file_handle, + const char* key, uint32_t datalength, const char* data); using mcpl_create_outfile_fpt = mcpl_outfile_t* (*)(const char* filename); using mcpl_hdr_set_srcname_fpt = void (*)( mcpl_outfile_t* outfile_handle, const char* srcname); @@ -110,6 +113,7 @@ struct McplApi { mcpl_close_file_fpt close_file; mcpl_create_outfile_fpt create_outfile; mcpl_hdr_set_srcname_fpt hdr_set_srcname; + mcpl_hdr_add_data_fpt hdr_add_data; mcpl_add_particle_fpt add_particle; mcpl_close_outfile_fpt close_outfile; mcpl_hdr_add_stat_sum_fpt hdr_add_stat_sum; @@ -151,6 +155,15 @@ struct McplApi { close_outfile = reinterpret_cast( load_symbol_platform("mcpl_close_outfile")); + // Try to load mcpl_hdr_add_data (available in MCPL >= 2.1.0) + // Set to nullptr if not available for graceful fallback + try { + hdr_add_data = reinterpret_cast( + load_symbol_platform("mcpl_hdr_add_data")); + } catch (const std::runtime_error&) { + hdr_add_data = nullptr; + } + // Try to load mcpl_hdr_add_stat_sum (available in MCPL >= 2.1.0) // Set to nullptr if not available for graceful fallback try { @@ -545,4 +558,153 @@ void write_mcpl_source_point(const char* filename, span source_bank, } } +// Collision track feature with MCPL +void write_mcpl_collision_track_internal(mcpl_outfile_t* file_id, + span collision_track_bank, + const vector& bank_index_all_ranks) +{ + if (mpi::master) { + if (!file_id) { + fatal_error("MCPL: Internal error - master rank called " + "write_mcpl_source_bank_internal with null file_id."); + } + vector receive_buffer; + vector all_sites; + all_sites.reserve(static_cast(bank_index_all_ranks.back())); + vector all_blobs; + all_blobs.reserve(static_cast(bank_index_all_ranks.back())); + + for (int rank_idx = 0; rank_idx < mpi::n_procs; ++rank_idx) { + size_t num_sites_on_rank = static_cast( + bank_index_all_ranks[rank_idx + 1] - bank_index_all_ranks[rank_idx]); + if (num_sites_on_rank == 0) + continue; + + span sites_to_process; +#ifdef OPENMC_MPI + if (rank_idx == mpi::rank) { + sites_to_process = openmc::span( + collision_track_bank.data(), num_sites_on_rank); + } else { + receive_buffer.resize(num_sites_on_rank); + MPI_Recv(receive_buffer.data(), num_sites_on_rank, + mpi::collision_track_site, rank_idx, rank_idx, mpi::intracomm, + MPI_STATUS_IGNORE); + sites_to_process = openmc::span( + receive_buffer.data(), num_sites_on_rank); + } +#else + sites_to_process = openmc::span( + collision_track_bank.data(), num_sites_on_rank); +#endif + + for (const auto& site : sites_to_process) { + std::ostringstream custom_data_stream; + custom_data_stream << " dE : " << site.dE + << " ; event_mt : " << site.event_mt + << " ; delayed_group : " << site.delayed_group + << " ; cell_id : " << site.cell_id + << " ; nuclide_id : " << site.nuclide_id + << " ; material_id : " << site.material_id + << " ; universe_id : " << site.universe_id + << " ; n_collision : " << site.n_collision + << " ; parent_id : " << site.parent_id + << " ; progeny_id : " << site.progeny_id; + + all_blobs.push_back(custom_data_stream.str()); + all_sites.push_back(site); + } + } + + for (size_t idx = 0; idx < all_blobs.size(); ++idx) { + const auto& blob = all_blobs[idx]; + std::string key = "blob_" + std::to_string(idx); + g_mcpl_api->hdr_add_data(file_id, key.c_str(), blob.size(), blob.c_str()); + } + + for (const auto& site : all_sites) { + mcpl_particle_repr_t p_repr {}; + p_repr.position[0] = site.r.x; + p_repr.position[1] = site.r.y; + p_repr.position[2] = site.r.z; + p_repr.direction[0] = site.u.x; + p_repr.direction[1] = site.u.y; + p_repr.direction[2] = site.u.z; + p_repr.ekin = site.E * 1e-6; + p_repr.time = site.time * 1e3; + p_repr.weight = site.wgt; + switch (site.particle) { + case ParticleType::neutron: + p_repr.pdgcode = 2112; + break; + case ParticleType::photon: + p_repr.pdgcode = 22; + break; + case ParticleType::electron: + p_repr.pdgcode = 11; + break; + case ParticleType::positron: + p_repr.pdgcode = -11; + break; + default: + continue; + } + g_mcpl_api->add_particle(file_id, &p_repr); + } + } else { +#ifdef OPENMC_MPI + if (!collision_track_bank.empty()) { + MPI_Send(collision_track_bank.data(), collision_track_bank.size(), + mpi::collision_track_site, 0, mpi::rank, mpi::intracomm); + } +#endif + } +} + +void write_mcpl_collision_track(const char* filename, + span collision_track_bank, + const vector& bank_index) +{ + ensure_mcpl_ready_or_fatal(); + + std::string filename_(filename); + const auto extension = get_file_extension(filename_); + if (extension.empty()) { + filename_.append(".mcpl"); + } else if (extension != "mcpl") { + warning(fmt::format("Specified filename '{}' has an extension '.{}', but " + "an MCPL file (.mcpl) will be written using this name.", + filename, extension)); + } + + mcpl_outfile_t* file_id = nullptr; + + if (mpi::master) { + file_id = g_mcpl_api->create_outfile(filename_.c_str()); + if (!file_id) { + fatal_error(fmt::format( + "MCPL: Failed to create output file '{}'. Check permissions and path.", + filename_)); + } + std::string src_line; + if (VERSION_DEV) { + src_line = fmt::format("OpenMC {}.{}.{}-dev{}", VERSION_MAJOR, + VERSION_MINOR, VERSION_RELEASE, VERSION_COMMIT_COUNT); + } else { + src_line = fmt::format( + "OpenMC {}.{}.{}", VERSION_MAJOR, VERSION_MINOR, VERSION_RELEASE); + } + + g_mcpl_api->hdr_set_srcname(file_id, src_line.c_str()); + } + write_mcpl_collision_track_internal( + file_id, collision_track_bank, bank_index); + + if (mpi::master) { + if (file_id) { + g_mcpl_api->close_outfile(file_id); + } + } +} + } // namespace openmc diff --git a/src/mesh.cpp b/src/mesh.cpp index 3e4ff1a3ec..c3a2d45818 100644 --- a/src/mesh.cpp +++ b/src/mesh.cpp @@ -51,6 +51,7 @@ #include "libmesh/mesh_modification.h" #include "libmesh/mesh_tools.h" #include "libmesh/numeric_vector.h" +#include "libmesh/replicated_mesh.h" #endif #ifdef OPENMC_DAGMC_ENABLED @@ -230,6 +231,42 @@ void MaterialVolumes::add_volume_unsafe( // Mesh implementation //============================================================================== +template +const std::unique_ptr& Mesh::create( + T dataset, const std::string& mesh_type, const std::string& mesh_library) +{ + // Determine mesh type. Add to model vector and map + if (mesh_type == RegularMesh::mesh_type) { + model::meshes.push_back(make_unique(dataset)); + } else if (mesh_type == RectilinearMesh::mesh_type) { + model::meshes.push_back(make_unique(dataset)); + } else if (mesh_type == CylindricalMesh::mesh_type) { + model::meshes.push_back(make_unique(dataset)); + } else if (mesh_type == SphericalMesh::mesh_type) { + model::meshes.push_back(make_unique(dataset)); +#ifdef OPENMC_DAGMC_ENABLED + } else if (mesh_type == UnstructuredMesh::mesh_type && + mesh_library == MOABMesh::mesh_lib_type) { + model::meshes.push_back(make_unique(dataset)); +#endif +#ifdef OPENMC_LIBMESH_ENABLED + } else if (mesh_type == UnstructuredMesh::mesh_type && + mesh_library == LibMesh::mesh_lib_type) { + model::meshes.push_back(make_unique(dataset)); +#endif + } else if (mesh_type == UnstructuredMesh::mesh_type) { + fatal_error("Unstructured mesh support is not enabled or the mesh " + "library is invalid."); + } else { + fatal_error(fmt::format("Invalid mesh type: {}", mesh_type)); + } + + // Map ID to position in vector + model::mesh_map[model::meshes.back()->id_] = model::meshes.size() - 1; + + return model::meshes.back(); +} + Mesh::Mesh(pugi::xml_node node) { // Read mesh id @@ -238,6 +275,17 @@ Mesh::Mesh(pugi::xml_node node) name_ = get_node_value(node, "name"); } +Mesh::Mesh(hid_t group) +{ + // Read mesh ID + read_attribute(group, "id", id_); + + // Read mesh name + if (object_exists(group, "name")) { + read_dataset(group, "name", name_); + } +} + void Mesh::set_id(int32_t id) { assert(id >= 0 || id == C_NONE); @@ -265,7 +313,13 @@ void Mesh::set_id(int32_t id) // Update ID and entry in the mesh map id_ = id; - model::mesh_map[id] = model::meshes.size() - 1; + + // find the index of this mesh in the model::meshes vector + // (search in reverse because this mesh was likely just added to the vector) + auto it = std::find_if(model::meshes.rbegin(), model::meshes.rend(), + [this](const std::unique_ptr& mesh) { return mesh.get() == this; }); + + model::mesh_map[id] = std::distance(model::meshes.begin(), it.base()) - 1; } vector Mesh::volumes() const @@ -590,6 +644,8 @@ Position StructuredMesh::sample_element( UnstructuredMesh::UnstructuredMesh(pugi::xml_node node) : Mesh(node) { + n_dimension_ = 3; + // check the mesh type if (check_for_node(node, "type")) { auto temp = get_node_value(node, "type", true, true); @@ -625,6 +681,46 @@ UnstructuredMesh::UnstructuredMesh(pugi::xml_node node) : Mesh(node) } } +UnstructuredMesh::UnstructuredMesh(hid_t group) : Mesh(group) +{ + n_dimension_ = 3; + + // check the mesh type + if (object_exists(group, "type")) { + std::string temp; + read_dataset(group, "type", temp); + if (temp != mesh_type) { + fatal_error(fmt::format("Invalid mesh type: {}", temp)); + } + } + + // check if a length unit multiplier was specified + if (object_exists(group, "length_multiplier")) { + read_dataset(group, "length_multiplier", length_multiplier_); + } + + // get the filename of the unstructured mesh to load + if (object_exists(group, "filename")) { + read_dataset(group, "filename", filename_); + if (!file_exists(filename_)) { + fatal_error("Mesh file '" + filename_ + "' does not exist!"); + } + } else { + fatal_error(fmt::format( + "No filename supplied for unstructured mesh with ID: {}", id_)); + } + + if (attribute_exists(group, "options")) { + read_attribute(group, "options", options_); + } + + // check if mesh tally data should be written with + // statepoint files + if (attribute_exists(group, "output")) { + read_attribute(group, "output", output_); + } +} + void UnstructuredMesh::determine_bounds() { double xmin = INFTY; @@ -1084,6 +1180,72 @@ void StructuredMesh::surface_bins_crossed( // RegularMesh implementation //============================================================================== +int RegularMesh::set_grid() +{ + auto shape = xt::adapt(shape_, {n_dimension_}); + + // Check that dimensions are all greater than zero + if (xt::any(shape <= 0)) { + set_errmsg("All entries for a regular mesh dimensions " + "must be positive."); + return OPENMC_E_INVALID_ARGUMENT; + } + + // Make sure lower_left and dimension match + if (lower_left_.size() != n_dimension_) { + set_errmsg("Number of entries in lower_left must be the same " + "as the regular mesh dimensions."); + return OPENMC_E_INVALID_ARGUMENT; + } + if (width_.size() > 0) { + + // Check to ensure width has same dimensions + if (width_.size() != n_dimension_) { + set_errmsg("Number of entries on width must be the same as " + "the regular mesh dimensions."); + return OPENMC_E_INVALID_ARGUMENT; + } + + // Check for negative widths + if (xt::any(width_ < 0.0)) { + set_errmsg("Cannot have a negative width on a regular mesh."); + return OPENMC_E_INVALID_ARGUMENT; + } + + // Set width and upper right coordinate + upper_right_ = xt::eval(lower_left_ + shape * width_); + + } else if (upper_right_.size() > 0) { + + // Check to ensure upper_right_ has same dimensions + if (upper_right_.size() != n_dimension_) { + set_errmsg("Number of entries on upper_right must be the " + "same as the regular mesh dimensions."); + return OPENMC_E_INVALID_ARGUMENT; + } + + // Check that upper-right is above lower-left + if (xt::any(upper_right_ < lower_left_)) { + set_errmsg( + "The upper_right coordinates of a regular mesh must be greater than " + "the lower_left coordinates."); + return OPENMC_E_INVALID_ARGUMENT; + } + + // Set width + width_ = xt::eval((upper_right_ - lower_left_) / shape); + } + + // Set material volumes + volume_frac_ = 1.0 / xt::prod(shape)(); + + element_volume_ = 1.0; + for (int i = 0; i < n_dimension_; i++) { + element_volume_ *= width_[i]; + } + return 0; +} + RegularMesh::RegularMesh(pugi::xml_node node) : StructuredMesh {node} { // Determine number of dimensions for mesh @@ -1098,12 +1260,6 @@ RegularMesh::RegularMesh(pugi::xml_node node) : StructuredMesh {node} } std::copy(shape.begin(), shape.end(), shape_.begin()); - // Check that dimensions are all greater than zero - if (xt::any(shape <= 0)) { - fatal_error("All entries on the element for a tally " - "mesh must be positive."); - } - // Check for lower-left coordinates if (check_for_node(node, "lower_left")) { // Read mesh lower-left corner location @@ -1112,12 +1268,6 @@ RegularMesh::RegularMesh(pugi::xml_node node) : StructuredMesh {node} fatal_error("Must specify on a mesh."); } - // Make sure lower_left and dimension match - if (shape.size() != lower_left_.size()) { - fatal_error("Number of entries on must be the same " - "as the number of entries on ."); - } - if (check_for_node(node, "width")) { // Make sure one of upper-right or width were specified if (check_for_node(node, "upper_right")) { @@ -1126,49 +1276,52 @@ RegularMesh::RegularMesh(pugi::xml_node node) : StructuredMesh {node} width_ = get_node_xarray(node, "width"); - // Check to ensure width has same dimensions - auto n = width_.size(); - if (n != lower_left_.size()) { - fatal_error("Number of entries on must be the same as " - "the number of entries on ."); - } - - // Check for negative widths - if (xt::any(width_ < 0.0)) { - fatal_error("Cannot have a negative on a tally mesh."); - } - - // Set width and upper right coordinate - upper_right_ = xt::eval(lower_left_ + shape * width_); - } else if (check_for_node(node, "upper_right")) { + upper_right_ = get_node_xarray(node, "upper_right"); - // Check to ensure width has same dimensions - auto n = upper_right_.size(); - if (n != lower_left_.size()) { - fatal_error("Number of entries on must be the " - "same as the number of entries on ."); - } - - // Check that upper-right is above lower-left - if (xt::any(upper_right_ < lower_left_)) { - fatal_error("The coordinates must be greater than " - "the coordinates on a tally mesh."); - } - - // Set width - width_ = xt::eval((upper_right_ - lower_left_) / shape); } else { fatal_error("Must specify either or on a mesh."); } - // Set material volumes - volume_frac_ = 1.0 / xt::prod(shape)(); + if (int err = set_grid()) { + fatal_error(openmc_err_msg); + } +} - element_volume_ = 1.0; - for (int i = 0; i < n_dimension_; i++) { - element_volume_ *= width_[i]; +RegularMesh::RegularMesh(hid_t group) : StructuredMesh {group} +{ + // Determine number of dimensions for mesh + if (!object_exists(group, "dimension")) { + fatal_error("Must specify on a regular mesh."); + } + + xt::xtensor shape; + read_dataset(group, "dimension", shape); + int n = n_dimension_ = shape.size(); + if (n != 1 && n != 2 && n != 3) { + fatal_error("Mesh must be one, two, or three dimensions."); + } + std::copy(shape.begin(), shape.end(), shape_.begin()); + + // Check for lower-left coordinates + if (object_exists(group, "lower_left")) { + // Read mesh lower-left corner location + read_dataset(group, "lower_left", lower_left_); + } else { + fatal_error("Must specify lower_left dataset on a mesh."); + } + + if (object_exists(group, "upper_right")) { + + read_dataset(group, "upper_right", upper_right_); + + } else { + fatal_error("Must specify either upper_right dataset on a mesh."); + } + + if (int err = set_grid()) { + fatal_error(openmc_err_msg); } } @@ -1341,6 +1494,19 @@ RectilinearMesh::RectilinearMesh(pugi::xml_node node) : StructuredMesh {node} } } +RectilinearMesh::RectilinearMesh(hid_t group) : StructuredMesh {group} +{ + n_dimension_ = 3; + + read_dataset(group, "x_grid", grid_[0]); + read_dataset(group, "y_grid", grid_[1]); + read_dataset(group, "z_grid", grid_[2]); + + if (int err = set_grid()) { + fatal_error(openmc_err_msg); + } +} + const std::string RectilinearMesh::mesh_type = "rectilinear"; std::string RectilinearMesh::get_mesh_type() const @@ -1476,6 +1642,19 @@ CylindricalMesh::CylindricalMesh(pugi::xml_node node) } } +CylindricalMesh::CylindricalMesh(hid_t group) : PeriodicStructuredMesh {group} +{ + n_dimension_ = 3; + read_dataset(group, "r_grid", grid_[0]); + read_dataset(group, "phi_grid", grid_[1]); + read_dataset(group, "z_grid", grid_[2]); + read_dataset(group, "origin", origin_); + + if (int err = set_grid()) { + fatal_error(openmc_err_msg); + } +} + const std::string CylindricalMesh::mesh_type = "cylindrical"; std::string CylindricalMesh::get_mesh_type() const @@ -1754,6 +1933,20 @@ SphericalMesh::SphericalMesh(pugi::xml_node node) } } +SphericalMesh::SphericalMesh(hid_t group) : PeriodicStructuredMesh {group} +{ + n_dimension_ = 3; + + read_dataset(group, "r_grid", grid_[0]); + read_dataset(group, "theta_grid", grid_[1]); + read_dataset(group, "phi_grid", grid_[2]); + read_dataset(group, "origin", origin_); + + if (int err = set_grid()) { + fatal_error(openmc_err_msg); + } +} + const std::string SphericalMesh::mesh_type = "spherical"; std::string SphericalMesh::get_mesh_type() const @@ -2518,8 +2711,15 @@ MOABMesh::MOABMesh(pugi::xml_node node) : UnstructuredMesh(node) initialize(); } -MOABMesh::MOABMesh(const std::string& filename, double length_multiplier) +MOABMesh::MOABMesh(hid_t group) : UnstructuredMesh(group) { + initialize(); +} + +MOABMesh::MOABMesh(const std::string& filename, double length_multiplier) + : UnstructuredMesh() +{ + n_dimension_ = 3; filename_ = filename; set_length_multiplier(length_multiplier); initialize(); @@ -3215,7 +3415,16 @@ void MOABMesh::write(const std::string& base_filename) const const std::string LibMesh::mesh_lib_type = "libmesh"; -LibMesh::LibMesh(pugi::xml_node node) : UnstructuredMesh(node), adaptive_(false) +LibMesh::LibMesh(pugi::xml_node node) : UnstructuredMesh(node) +{ + // filename_ and length_multiplier_ will already be set by the + // UnstructuredMesh constructor + set_mesh_pointer_from_filename(filename_); + set_length_multiplier(length_multiplier_); + initialize(); +} + +LibMesh::LibMesh(hid_t group) : UnstructuredMesh(group) { // filename_ and length_multiplier_ will already be set by the // UnstructuredMesh constructor @@ -3226,9 +3435,8 @@ LibMesh::LibMesh(pugi::xml_node node) : UnstructuredMesh(node), adaptive_(false) // create the mesh from a pointer to a libMesh Mesh LibMesh::LibMesh(libMesh::MeshBase& input_mesh, double length_multiplier) - : adaptive_(input_mesh.n_active_elem() != input_mesh.n_elem()) { - if (!dynamic_cast(&input_mesh)) { + if (!input_mesh.is_replicated()) { fatal_error("At present LibMesh tallies require a replicated mesh. Please " "ensure 'input_mesh' is a libMesh::ReplicatedMesh."); } @@ -3240,8 +3448,8 @@ LibMesh::LibMesh(libMesh::MeshBase& input_mesh, double length_multiplier) // create the mesh from an input file LibMesh::LibMesh(const std::string& filename, double length_multiplier) - : adaptive_(false) { + n_dimension_ = 3; set_mesh_pointer_from_filename(filename); set_length_multiplier(length_multiplier); initialize(); @@ -3302,21 +3510,6 @@ void LibMesh::initialize() auto first_elem = *m_->elements_begin(); first_element_id_ = first_elem->id(); - // if the mesh is adaptive elements aren't guaranteed by libMesh to be - // contiguous in ID space, so we need to map from bin indices (defined over - // active elements) to global dof ids - if (adaptive_) { - bin_to_elem_map_.reserve(m_->n_active_elem()); - elem_to_bin_map_.resize(m_->n_elem(), -1); - for (auto it = m_->active_elements_begin(); it != m_->active_elements_end(); - it++) { - auto elem = *it; - - bin_to_elem_map_.push_back(elem->id()); - elem_to_bin_map_[elem->id()] = bin_to_elem_map_.size() - 1; - } - } - // bounding box for the mesh for quick rejection checks bbox_ = libMesh::MeshTools::create_bounding_box(*m_); libMesh::Point ll = bbox_.min(); @@ -3374,7 +3567,7 @@ std::string LibMesh::library() const int LibMesh::n_bins() const { - return m_->n_active_elem(); + return m_->n_elem(); } int LibMesh::n_surface_bins() const @@ -3397,14 +3590,6 @@ int LibMesh::n_surface_bins() const void LibMesh::add_score(const std::string& var_name) { - if (adaptive_) { - warning(fmt::format( - "Exodus output cannot be provided as unstructured mesh {} is adaptive.", - this->id_)); - - return; - } - if (!equation_systems_) { build_eqn_sys(); } @@ -3440,14 +3625,6 @@ void LibMesh::remove_scores() void LibMesh::set_score_data(const std::string& var_name, const vector& values, const vector& std_dev) { - if (adaptive_) { - warning(fmt::format( - "Exodus output cannot be provided as unstructured mesh {} is adaptive.", - this->id_)); - - return; - } - if (!equation_systems_) { build_eqn_sys(); } @@ -3491,14 +3668,6 @@ void LibMesh::set_score_data(const std::string& var_name, void LibMesh::write(const std::string& filename) const { - if (adaptive_) { - warning(fmt::format( - "Exodus output cannot be provided as unstructured mesh {} is adaptive.", - this->id_)); - - return; - } - write_message(fmt::format( "Writing file: {}.e for unstructured mesh {}", filename, this->id_)); libMesh::ExodusII_IO exo(*m_); @@ -3532,8 +3701,7 @@ int LibMesh::get_bin(Position r) const int LibMesh::get_bin_from_element(const libMesh::Elem* elem) const { - int bin = - adaptive_ ? elem_to_bin_map_[elem->id()] : elem->id() - first_element_id_; + int bin = elem->id() - first_element_id_; if (bin >= n_bins() || bin < 0) { fatal_error(fmt::format("Invalid bin: {}", bin)); } @@ -3548,7 +3716,7 @@ std::pair, vector> LibMesh::plot( const libMesh::Elem& LibMesh::get_element_from_bin(int bin) const { - return adaptive_ ? m_->elem_ref(bin_to_elem_map_.at(bin)) : m_->elem_ref(bin); + return m_->elem_ref(bin); } double LibMesh::volume(int bin) const @@ -3556,6 +3724,65 @@ double LibMesh::volume(int bin) const return this->get_element_from_bin(bin).volume(); } +AdaptiveLibMesh::AdaptiveLibMesh( + libMesh::MeshBase& input_mesh, double length_multiplier) + : LibMesh(input_mesh, length_multiplier), num_active_(m_->n_active_elem()) +{ + // if the mesh is adaptive elements aren't guaranteed by libMesh to be + // contiguous in ID space, so we need to map from bin indices (defined over + // active elements) to global dof ids + bin_to_elem_map_.reserve(num_active_); + elem_to_bin_map_.resize(m_->n_elem(), -1); + for (auto it = m_->active_elements_begin(); it != m_->active_elements_end(); + it++) { + auto elem = *it; + + bin_to_elem_map_.push_back(elem->id()); + elem_to_bin_map_[elem->id()] = bin_to_elem_map_.size() - 1; + } +} + +int AdaptiveLibMesh::n_bins() const +{ + return num_active_; +} + +void AdaptiveLibMesh::add_score(const std::string& var_name) +{ + warning(fmt::format( + "Exodus output cannot be provided as unstructured mesh {} is adaptive.", + this->id_)); +} + +void AdaptiveLibMesh::set_score_data(const std::string& var_name, + const vector& values, const vector& std_dev) +{ + warning(fmt::format( + "Exodus output cannot be provided as unstructured mesh {} is adaptive.", + this->id_)); +} + +void AdaptiveLibMesh::write(const std::string& filename) const +{ + warning(fmt::format( + "Exodus output cannot be provided as unstructured mesh {} is adaptive.", + this->id_)); +} + +int AdaptiveLibMesh::get_bin_from_element(const libMesh::Elem* elem) const +{ + int bin = elem_to_bin_map_[elem->id()]; + if (bin >= n_bins() || bin < 0) { + fatal_error(fmt::format("Invalid bin: {}", bin)); + } + return bin; +} + +const libMesh::Elem& AdaptiveLibMesh::get_element_from_bin(int bin) const +{ + return m_->elem_ref(bin_to_elem_map_.at(bin)); +} + #endif // OPENMC_LIBMESH_ENABLED //============================================================================== @@ -3596,34 +3823,51 @@ void read_meshes(pugi::xml_node root) mesh_lib = get_node_value(node, "library", true, true); } - // Read mesh and add to vector - if (mesh_type == RegularMesh::mesh_type) { - model::meshes.push_back(make_unique(node)); - } else if (mesh_type == RectilinearMesh::mesh_type) { - model::meshes.push_back(make_unique(node)); - } else if (mesh_type == CylindricalMesh::mesh_type) { - model::meshes.push_back(make_unique(node)); - } else if (mesh_type == SphericalMesh::mesh_type) { - model::meshes.push_back(make_unique(node)); -#ifdef OPENMC_DAGMC_ENABLED - } else if (mesh_type == UnstructuredMesh::mesh_type && - mesh_lib == MOABMesh::mesh_lib_type) { - model::meshes.push_back(make_unique(node)); -#endif -#ifdef OPENMC_LIBMESH_ENABLED - } else if (mesh_type == UnstructuredMesh::mesh_type && - mesh_lib == LibMesh::mesh_lib_type) { - model::meshes.push_back(make_unique(node)); -#endif - } else if (mesh_type == UnstructuredMesh::mesh_type) { - fatal_error("Unstructured mesh support is not enabled or the mesh " - "library is invalid."); - } else { - fatal_error("Invalid mesh type: " + mesh_type); + Mesh::create(node, mesh_type, mesh_lib); + } +} + +void read_meshes(hid_t group) +{ + std::unordered_set mesh_ids; + + std::vector ids; + read_attribute(group, "ids", ids); + + for (auto id : ids) { + + // Check to make sure multiple meshes in the same file don't share IDs + if (contains(mesh_ids, id)) { + fatal_error(fmt::format("Two or more meshes use the same unique ID " + "'{}' in the same HDF5 input file", + id)); + } + mesh_ids.insert(id); + + // If we've already read a mesh with the same ID in a *different* file, + // assume it is the same here + if (model::mesh_map.find(id) != model::mesh_map.end()) { + warning(fmt::format("Mesh with ID={} appears in multiple files.", id)); + continue; } - // Map ID to position in vector - model::mesh_map[model::meshes.back()->id_] = model::meshes.size() - 1; + std::string name = fmt::format("mesh {}", id); + hid_t mesh_group = open_group(group, name.c_str()); + + std::string mesh_type; + if (object_exists(mesh_group, "type")) { + read_dataset(mesh_group, "type", mesh_type); + } else { + mesh_type = "regular"; + } + + // determine the mesh library to use + std::string mesh_lib; + if (object_exists(mesh_group, "library")) { + read_dataset(mesh_group, "library", mesh_lib); + } + + Mesh::create(mesh_group, mesh_type, mesh_lib); } } diff --git a/src/message_passing.cpp b/src/message_passing.cpp index 374c1aa725..a160f6d73c 100644 --- a/src/message_passing.cpp +++ b/src/message_passing.cpp @@ -10,6 +10,7 @@ bool master {true}; #ifdef OPENMC_MPI MPI_Comm intracomm {MPI_COMM_NULL}; MPI_Datatype source_site {MPI_DATATYPE_NULL}; +MPI_Datatype collision_track_site {MPI_DATATYPE_NULL}; #endif extern "C" bool openmc_master() diff --git a/src/mgxs.cpp b/src/mgxs.cpp index a88d2c196b..a2c479f215 100644 --- a/src/mgxs.cpp +++ b/src/mgxs.cpp @@ -617,10 +617,12 @@ void Mgxs::calculate_xs(Particle& p) } int temperature = p.mg_xs_cache().t; int angle = p.mg_xs_cache().a; - p.macro_xs().total = xs[temperature].total(angle, p.g()); - p.macro_xs().absorption = xs[temperature].absorption(angle, p.g()); + p.macro_xs().total = xs[temperature].total(angle, p.g()) * p.density_mult(); + p.macro_xs().absorption = + xs[temperature].absorption(angle, p.g()) * p.density_mult(); p.macro_xs().nu_fission = - fissionable ? xs[temperature].nu_fission(angle, p.g()) : 0.; + fissionable ? xs[temperature].nu_fission(angle, p.g()) * p.density_mult() + : 0.; } //============================================================================== diff --git a/src/nuclide.cpp b/src/nuclide.cpp index 7cb84640d6..5ae6e30ee2 100644 --- a/src/nuclide.cpp +++ b/src/nuclide.cpp @@ -31,8 +31,8 @@ namespace openmc { //============================================================================== namespace data { -array energy_min {0.0, 0.0}; -array energy_max {INFTY, INFTY}; +array energy_min {0.0, 0.0, 0.0, 0.0}; +array energy_max {INFTY, INFTY, INFTY, INFTY}; double temperature_min {INFTY}; double temperature_max {0.0}; std::unordered_map nuclide_map; diff --git a/src/output.cpp b/src/output.cpp index 0a14e8843d..80e2b10ab8 100644 --- a/src/output.cpp +++ b/src/output.cpp @@ -281,6 +281,7 @@ void print_usage() " -t, --track Write tracks for all particles (up to " "max_tracks)\n" " -e, --event Run using event-based parallelism\n" + " -q, --verbosity Output verbosity\n" " -v, --version Show version information\n" " -h, --help Show this message\n"); } diff --git a/src/particle.cpp b/src/particle.cpp index 67cb144935..c3e947db73 100644 --- a/src/particle.cpp +++ b/src/particle.cpp @@ -8,6 +8,7 @@ #include "openmc/bank.h" #include "openmc/capi.h" #include "openmc/cell.h" +#include "openmc/collision_track.h" #include "openmc/constants.h" #include "openmc/dagmc.h" #include "openmc/error.h" @@ -121,6 +122,9 @@ void Particle::from_source(const SourceSite* src) fission() = false; zero_flux_derivs(); lifetime() = 0.0; +#ifdef OPENMC_DAGMC_ENABLED + history().reset(); +#endif // Copy attributes from source bank site type() = src->particle; @@ -144,6 +148,7 @@ void Particle::from_source(const SourceSite* src) time() = src->time; time_last() = src->time; parent_nuclide() = src->parent_nuclide; + delayed_group() = src->delayed_group; // Convert signed surface ID to signed index if (src->surf_id != SURFACE_NONE) { @@ -200,7 +205,8 @@ void Particle::event_calculate_xs() // Calculate microscopic and macroscopic cross sections if (material() != MATERIAL_VOID) { if (settings::run_CE) { - if (material() != material_last() || sqrtkT() != sqrtkT_last()) { + if (material() != material_last() || sqrtkT() != sqrtkT_last() || + density_mult() != density_mult_last()) { // If the material is the same as the last material and the // temperature hasn't changed, we don't need to lookup cross // sections again. @@ -227,7 +233,7 @@ void Particle::event_advance() { // Sample a distance to collision if (type() == ParticleType::electron || type() == ParticleType::positron) { - collision_distance() = 0.0; + collision_distance() = material() == MATERIAL_VOID ? INFINITY : 0.0; } else if (macro_xs().total == 0.0) { collision_distance() = INFINITY; } else { @@ -252,6 +258,11 @@ void Particle::event_advance() this->time() += dt; this->lifetime() += dt; + // Score timed track-length tallies + if (!model::active_timed_tracklength_tallies.empty()) { + score_timed_tracklength_tally(*this, distance); + } + // Score track-length tallies if (!model::active_tracklength_tallies.empty()) { score_tracklength_tally(*this, distance); @@ -341,6 +352,11 @@ void Particle::event_collide() collision_mg(*this); } + // Collision track feature to recording particle interaction + if (settings::collision_track) { + collision_track_record(*this); + } + // Score collision estimator tallies -- this is done after a collision // has occurred rather than before because we need information on the // outgoing energy for any tallies with an outgoing energy filter @@ -544,7 +560,8 @@ void Particle::cross_surface(const Surface& surf) #endif // Handle any applicable boundary conditions. - if (surf.bc_ && settings::run_mode != RunMode::PLOTTING) { + if (surf.bc_ && settings::run_mode != RunMode::PLOTTING && + settings::run_mode != RunMode::VOLUME) { surf.bc_->handle_particle(*this, surf); return; } @@ -558,9 +575,10 @@ void Particle::cross_surface(const Surface& surf) int32_t i_cell = next_cell(surface_index(), cell_last(n_coord() - 1), lowest_coord().universe()) - 1; - // save material and temp + // save material, temperature, and density multiplier material_last() = material(); sqrtkT_last() = sqrtkT(); + density_mult_last() = density_mult(); // set new cell value lowest_coord().cell() = i_cell; auto& cell = model::cells[i_cell]; @@ -571,6 +589,7 @@ void Particle::cross_surface(const Surface& surf) material() = cell->material(cell_instance()); sqrtkT() = cell->sqrtkT(cell_instance()); + density_mult() = cell->density_mult(cell_instance()); return; } #endif @@ -851,10 +870,12 @@ void Particle::update_neutron_xs( // If the cache doesn't match, recalculate micro xs if (this->E() != micro.last_E || this->sqrtkT() != micro.last_sqrtkT || - i_sab != micro.index_sab || sab_frac != micro.sab_frac) { + i_sab != micro.index_sab || sab_frac != micro.sab_frac || + ncrystal_xs != micro.ncrystal_xs) { data::nuclides[i_nuclide]->calculate_xs(i_sab, i_grid, sab_frac, *this); // If NCrystal is being used, update micro cross section cache + micro.ncrystal_xs = ncrystal_xs; if (ncrystal_xs >= 0.0) { data::nuclides[i_nuclide]->calculate_elastic_xs(*this); ncrystal_update_micro(ncrystal_xs, micro); diff --git a/src/physics.cpp b/src/physics.cpp index 3c06e543de..41509af97b 100644 --- a/src/physics.cpp +++ b/src/physics.cpp @@ -115,13 +115,14 @@ void sample_neutron_reaction(Particle& p) // Make sure particle population doesn't grow out of control for // subcritical multiplication problems. - if (p.secondary_bank().size() >= 10000) { + if (p.secondary_bank().size() >= settings::max_secondaries) { fatal_error( "The secondary particle bank appears to be growing without " "bound. You are likely running a subcritical multiplication problem " "with k-effective close to or greater than one."); } } + p.event_mt() = rx.mt_; } // Create secondary photons @@ -210,13 +211,23 @@ void create_fission_sites(Particle& p, int i_nuclide, const Reaction& rx) site.particle = ParticleType::neutron; site.time = p.time(); site.wgt = 1. / weight; - site.parent_id = p.id(); - site.progeny_id = p.n_progeny()++; site.surf_id = 0; // Sample delayed group and angle/energy for fission reaction sample_fission_neutron(i_nuclide, rx, &site, p); + // Reject site if it exceeds time cutoff + if (site.delayed_group > 0) { + double t_cutoff = settings::time_cutoff[static_cast(site.particle)]; + if (site.time > t_cutoff) { + continue; + } + } + + // Set parent and progeny IDs + site.parent_id = p.id(); + site.progeny_id = p.n_progeny()++; + // Store fission site in bank if (use_fission_bank) { int64_t idx = simulation::fission_bank.thread_safe_append(site); @@ -236,18 +247,15 @@ void create_fission_sites(Particle& p, int i_nuclide, const Reaction& rx) } // Iterated Fission Probability (IFP) method if (settings::ifp_on) { - ifp(p, site, idx); + ifp(p, idx); } } else { p.secondary_bank().push_back(site); } - // Set the delayed group on the particle as well - p.delayed_group() = site.delayed_group; - // Increment the number of neutrons born delayed - if (p.delayed_group() > 0) { - nu_d[p.delayed_group() - 1]++; + if (site.delayed_group > 0) { + nu_d[site.delayed_group - 1]++; } // Write fission particles to nuBank @@ -496,7 +504,7 @@ int sample_nuclide(Particle& p) for (int i = 0; i < n; ++i) { // Get atom density int i_nuclide = mat->nuclide_[i]; - double atom_density = mat->atom_density_[i]; + double atom_density = mat->atom_density(i, p.density_mult()); // Increment probability to compare to cutoff prob += atom_density * p.neutron_xs(i_nuclide).total; @@ -521,7 +529,7 @@ int sample_element(Particle& p) for (int i = 0; i < mat->element_.size(); ++i) { // Find atom density int i_element = mat->element_[i]; - double atom_density = mat->atom_density_[i]; + double atom_density = mat->atom_density(i, p.density_mult()); // Determine microscopic cross section double sigma = atom_density * p.photon_xs(i_element).total; @@ -656,7 +664,9 @@ void absorption(Particle& p, int i_nuclide) p.wgt() = 0.0; p.event() = TallyEvent::ABSORB; - p.event_mt() = N_DISAPPEAR; + if (!p.fission()) { + p.event_mt() = N_DISAPPEAR; + } } } } @@ -844,7 +854,7 @@ Direction sample_target_velocity(const Nuclide& nuc, double E, Direction u, // otherwise, use free gas model } else { - if (E >= FREE_GAS_THRESHOLD * kT && nuc.awr_ > 1.0) { + if (E >= settings::free_gas_threshold * kT && nuc.awr_ > 1.0) { return {}; } else { sampling_method = ResScatMethod::cxs; @@ -1069,6 +1079,10 @@ void sample_fission_neutron( // set the delayed group for the particle born from fission site->delayed_group = group; + // Sample time of emission based on decay constant of precursor + double decay_rate = rx.products_[site->delayed_group].decay_rate_; + site->time -= std::log(prn(p.current_seed())) / decay_rate; + } else { // ==================================================================== // PROMPT NEUTRON SAMPLED diff --git a/src/physics_mg.cpp b/src/physics_mg.cpp index 5ebef9c141..4c28cb1795 100644 --- a/src/physics_mg.cpp +++ b/src/physics_mg.cpp @@ -139,8 +139,6 @@ void create_fission_sites(Particle& p) site.particle = ParticleType::neutron; site.time = p.time(); site.wgt = 1. / weight; - site.parent_id = p.id(); - site.progeny_id = p.n_progeny()++; // Sample the cosine of the angle, assuming fission neutrons are emitted // isotropically @@ -165,6 +163,24 @@ void create_fission_sites(Particle& p) // of the code, 0 is prompt. site.delayed_group = dg + 1; + // If delayed product production, sample time of emission + if (dg != -1) { + auto& macro_xs = data::mg.macro_xs_[p.material()]; + double decay_rate = + macro_xs.get_xs(MgxsType::DECAY_RATE, 0, nullptr, nullptr, &dg, 0, 0); + site.time -= std::log(prn(p.current_seed())) / decay_rate; + + // Reject site if it exceeds time cutoff + double t_cutoff = settings::time_cutoff[static_cast(site.particle)]; + if (site.time > t_cutoff) { + continue; + } + } + + // Set parent and progeny ID + site.parent_id = p.id(); + site.progeny_id = p.n_progeny()++; + // Store fission site in bank if (use_fission_bank) { int64_t idx = simulation::fission_bank.thread_safe_append(site); diff --git a/src/random_ray/flat_source_domain.cpp b/src/random_ray/flat_source_domain.cpp index 4092388308..ec14795dd2 100644 --- a/src/random_ray/flat_source_domain.cpp +++ b/src/random_ray/flat_source_domain.cpp @@ -53,24 +53,6 @@ FlatSourceDomain::FlatSourceDomain() : negroups_(data::mg.num_energy_groups_) // Initialize source regions. bool is_linear = RandomRay::source_shape_ != RandomRaySourceShape::FLAT; source_regions_ = SourceRegionContainer(negroups_, is_linear); - source_regions_.assign( - base_source_regions, SourceRegion(negroups_, is_linear)); - - // Initialize materials - int64_t source_region_id = 0; - for (int i = 0; i < model::cells.size(); i++) { - Cell& cell = *model::cells[i]; - if (cell.type_ == Fill::MATERIAL) { - for (int j = 0; j < cell.n_instances(); j++) { - source_regions_.material(source_region_id++) = cell.material(j); - } - } - } - - // Sanity check - if (source_region_id != base_source_regions) { - fatal_error("Unexpected number of source regions"); - } // Initialize tally volumes if (volume_normalized_flux_tallies_) { @@ -118,54 +100,58 @@ void FlatSourceDomain::accumulate_iteration_flux() } } -// Compute new estimate of scattering + fission sources in each source region -// based on the flux estimate from the previous iteration. -void FlatSourceDomain::update_neutron_source(double k_eff) +void FlatSourceDomain::update_single_neutron_source(SourceRegionHandle& srh) { - simulation::time_update_src.start(); - - double inverse_k_eff = 1.0 / k_eff; - -// Reset all source regions to zero (important for void regions) -#pragma omp parallel for - for (int64_t se = 0; se < n_source_elements(); se++) { - source_regions_.source(se) = 0.0; + // Reset all source regions to zero (important for void regions) + for (int g = 0; g < negroups_; g++) { + srh.source(g) = 0.0; } // Add scattering + fission source -#pragma omp parallel for - for (int64_t sr = 0; sr < n_source_regions(); sr++) { - int material = source_regions_.material(sr); - if (material == MATERIAL_VOID) { - continue; - } + int material = srh.material(); + if (material != MATERIAL_VOID) { + double inverse_k_eff = 1.0 / k_eff_; for (int g_out = 0; g_out < negroups_; g_out++) { double sigma_t = sigma_t_[material * negroups_ + g_out]; double scatter_source = 0.0; double fission_source = 0.0; for (int g_in = 0; g_in < negroups_; g_in++) { - double scalar_flux = source_regions_.scalar_flux_old(sr, g_in); + double scalar_flux = srh.scalar_flux_old(g_in); double sigma_s = sigma_s_[material * negroups_ * negroups_ + g_out * negroups_ + g_in]; double nu_sigma_f = nu_sigma_f_[material * negroups_ + g_in]; double chi = chi_[material * negroups_ + g_out]; scatter_source += sigma_s * scalar_flux; - fission_source += nu_sigma_f * scalar_flux * chi; + if (settings::create_fission_neutrons) { + fission_source += nu_sigma_f * scalar_flux * chi; + } } - source_regions_.source(sr, g_out) = + srh.source(g_out) = (scatter_source + fission_source * inverse_k_eff) / sigma_t; } } // Add external source if in fixed source mode if (settings::run_mode == RunMode::FIXED_SOURCE) { -#pragma omp parallel for - for (int64_t se = 0; se < n_source_elements(); se++) { - source_regions_.source(se) += source_regions_.external_source(se); + for (int g = 0; g < negroups_; g++) { + srh.source(g) += srh.external_source(g); } } +} + +// Compute new estimate of scattering + fission sources in each source region +// based on the flux estimate from the previous iteration. +void FlatSourceDomain::update_all_neutron_sources() +{ + simulation::time_update_src.start(); + +#pragma omp parallel for + for (int64_t sr = 0; sr < n_source_regions(); sr++) { + SourceRegionHandle srh = source_regions_.get_source_region_handle(sr); + update_single_neutron_source(srh); + } simulation::time_update_src.stop(); } @@ -320,7 +306,7 @@ int64_t FlatSourceDomain::add_source_to_scalar_flux() // Generates new estimate of k_eff based on the differences between this // iteration's estimate of the scalar flux and the last iteration's estimate. -double FlatSourceDomain::compute_k_eff(double k_eff_old) const +void FlatSourceDomain::compute_k_eff() { double fission_rate_old = 0; double fission_rate_new = 0; @@ -365,7 +351,7 @@ double FlatSourceDomain::compute_k_eff(double k_eff_old) const p[sr] = sr_fission_source_new; } - double k_eff_new = k_eff_old * (fission_rate_new / fission_rate_old); + double k_eff_new = k_eff_ * (fission_rate_new / fission_rate_old); double H = 0.0; // defining an inverse sum for better performance @@ -385,7 +371,8 @@ double FlatSourceDomain::compute_k_eff(double k_eff_old) const // Adds entropy value to shared entropy vector in openmc namespace. simulation::entropy.push_back(H); - return k_eff_new; + fission_rate_ = fission_rate_new; + k_eff_ = k_eff_new; } // This function is responsible for generating a mapping between random @@ -535,12 +522,33 @@ void FlatSourceDomain::reset_tally_volumes() // simulation double FlatSourceDomain::compute_fixed_source_normalization_factor() const { - // If we are not in fixed source mode, then there are no external sources - // so no normalization is needed. - if (settings::run_mode != RunMode::FIXED_SOURCE || adjoint_) { + // Eigenvalue mode normalization + if (settings::run_mode == RunMode::EIGENVALUE) { + // Normalize fluxes by total number of fission neutrons produced. This + // ensures consistent scaling of the eigenvector such that its magnitude is + // comparable to the eigenvector produced by the Monte Carlo solver. + // Multiplying by the eigenvalue is unintuitive, but it is necessary. + // If the eigenvalue is 1.2, per starting source neutron, you will + // generate 1.2 neutrons. Thus if we normalize to generating only ONE + // neutron in total for the whole domain, then we don't actually have enough + // flux to generate the required 1.2 neutrons. We only know the flux + // required to generate 1 neutron (which would have required less than one + // starting neutron). Thus, you have to scale the flux up by the eigenvalue + // such that 1.2 neutrons are generated, so as to be consistent with the + // bookkeeping in MC which is all done per starting source neutron (not per + // neutron produced). + return k_eff_ / (fission_rate_ * simulation_volume_); + } + + // If we are in adjoint mode of a fixed source problem, the external + // source is already normalized, such that all resulting fluxes are + // also normalized. + if (adjoint_) { return 1.0; } + // Fixed source mode normalization + // Step 1 is to sum over all source regions and energy groups to get the // total external source strength in the simulation. double simulation_external_source_strength = 0.0; @@ -652,7 +660,6 @@ void FlatSourceDomain::random_ray_tally() "random ray mode."); break; } - // Apply score to the appropriate tally bin Tally& tally {*model::tallies[task.tally_idx]}; #pragma omp atomic @@ -726,21 +733,21 @@ void FlatSourceDomain::output_to_vtk() const print_plot(); // Outer loop over plots - for (int p = 0; p < model::plots.size(); p++) { + for (int plt = 0; plt < model::plots.size(); plt++) { // Get handle to OpenMC plot object and extract params - Plot* openmc_plot = dynamic_cast(model::plots[p].get()); + Plot* openmc_plot = dynamic_cast(model::plots[plt].get()); // Random ray plots only support voxel plots if (!openmc_plot) { warning(fmt::format("Plot {} is invalid plot type -- only voxel plotting " "is allowed in random ray mode.", - p)); + plt)); continue; } else if (openmc_plot->type_ != Plot::PlotType::voxel) { warning(fmt::format("Plot {} is invalid plot type -- only voxel plotting " "is allowed in random ray mode.", - p)); + plt)); continue; } @@ -794,23 +801,11 @@ void FlatSourceDomain::output_to_vtk() const continue; } - int i_cell = p.lowest_coord().cell(); - int64_t sr = source_region_offsets_[i_cell] + p.cell_instance(); - if (RandomRay::mesh_subdivision_enabled_) { - int mesh_idx = base_source_regions_.mesh(sr); - int mesh_bin; - if (mesh_idx == C_NONE) { - mesh_bin = 0; - } else { - mesh_bin = model::meshes[mesh_idx]->get_bin(p.r()); - } - SourceRegionKey sr_key {sr, mesh_bin}; - auto it = source_region_map_.find(sr_key); - if (it != source_region_map_.end()) { - sr = it->second; - } else { - sr = -1; - } + SourceRegionKey sr_key = lookup_source_region_key(p); + int64_t sr = -1; + auto it = source_region_map_.find(sr_key); + if (it != source_region_map_.end()) { + sr = it->second; } voxel_indices[z * Ny * Nx + y * Nx + x] = sr; @@ -967,13 +962,17 @@ void FlatSourceDomain::output_to_vtk() const } void FlatSourceDomain::apply_external_source_to_source_region( - Discrete* discrete, double strength_factor, SourceRegionHandle& srh) + int src_idx, SourceRegionHandle& srh) { - srh.external_source_present() = 1; - + auto s = model::external_sources[src_idx].get(); + auto is = dynamic_cast(s); + auto discrete = dynamic_cast(is->energy()); + double strength_factor = is->strength(); const auto& discrete_energies = discrete->x(); const auto& discrete_probs = discrete->prob(); + srh.external_source_present() = 1; + for (int i = 0; i < discrete_energies.size(); i++) { int g = data::mg.get_group_index(discrete_energies[i]); srh.external_source(g) += discrete_probs[i] * strength_factor; @@ -981,8 +980,7 @@ void FlatSourceDomain::apply_external_source_to_source_region( } void FlatSourceDomain::apply_external_source_to_cell_instances(int32_t i_cell, - Discrete* discrete, double strength_factor, int target_material_id, - const vector& instances) + int src_idx, int target_material_id, const vector& instances) { Cell& cell = *model::cells[i_cell]; @@ -1000,16 +998,13 @@ void FlatSourceDomain::apply_external_source_to_cell_instances(int32_t i_cell, if (target_material_id == C_NONE || cell_material_id == target_material_id) { int64_t source_region = source_region_offsets_[i_cell] + j; - SourceRegionHandle srh = - source_regions_.get_source_region_handle(source_region); - apply_external_source_to_source_region(discrete, strength_factor, srh); + external_volumetric_source_map_[source_region].push_back(src_idx); } } } void FlatSourceDomain::apply_external_source_to_cell_and_children( - int32_t i_cell, Discrete* discrete, double strength_factor, - int32_t target_material_id) + int32_t i_cell, int src_idx, int32_t target_material_id) { Cell& cell = *model::cells[i_cell]; @@ -1017,14 +1012,14 @@ void FlatSourceDomain::apply_external_source_to_cell_and_children( vector instances(cell.n_instances()); std::iota(instances.begin(), instances.end(), 0); apply_external_source_to_cell_instances( - i_cell, discrete, strength_factor, target_material_id, instances); + i_cell, src_idx, target_material_id, instances); } else if (target_material_id == C_NONE) { std::unordered_map> cell_instance_list = cell.get_contained_cells(0, nullptr); for (const auto& pair : cell_instance_list) { int32_t i_child_cell = pair.first; - apply_external_source_to_cell_instances(i_child_cell, discrete, - strength_factor, target_material_id, pair.second); + apply_external_source_to_cell_instances( + i_child_cell, src_idx, target_material_id, pair.second); } } } @@ -1070,36 +1065,17 @@ void FlatSourceDomain::convert_external_sources() "point source at {}", sp->r())); } - int i_cell = gs.lowest_coord().cell(); - int64_t sr = source_region_offsets_[i_cell] + gs.cell_instance(); + SourceRegionKey key = lookup_source_region_key(gs); - if (RandomRay::mesh_subdivision_enabled_) { - // If mesh subdivision is enabled, we need to determine which subdivided - // mesh bin the point source coordinate is in as well - int mesh_idx = source_regions_.mesh(sr); - int mesh_bin; - if (mesh_idx == C_NONE) { - mesh_bin = 0; - } else { - mesh_bin = model::meshes[mesh_idx]->get_bin(gs.r()); - } - // With the source region and mesh bin known, we can use the - // accompanying SourceRegionKey as a key into a map that stores the - // corresponding external source index for the point source. Notably, we - // do not actually apply the external source to any source regions here, - // as if mesh subdivision is enabled, they haven't actually been - // discovered & initilized yet. When discovered, they will read from the - // point_source_map to determine if there are any point source terms - // that should be applied. - SourceRegionKey key {sr, mesh_bin}; - point_source_map_[key] = es; - } else { - // If we are not using mesh subdivision, we can apply the external - // source directly to the source region as we do for volumetric domain - // constraint sources. - SourceRegionHandle srh = source_regions_.get_source_region_handle(sr); - apply_external_source_to_source_region(energy, strength_factor, srh); - } + // With the source region and mesh bin known, we can use the + // accompanying SourceRegionKey as a key into a map that stores the + // corresponding external source index for the point source. Notably, we + // do not actually apply the external source to any source regions here, + // as if mesh subdivision is enabled, they haven't actually been + // discovered & initilized yet. When discovered, they will read from the + // external_source_map to determine if there are any external source + // terms that should be applied. + external_point_source_map_[key].push_back(es); } else { // If not a point source, then use the volumetric domain constraints to @@ -1107,42 +1083,25 @@ void FlatSourceDomain::convert_external_sources() if (is->domain_type() == Source::DomainType::MATERIAL) { for (int32_t material_id : domain_ids) { for (int i_cell = 0; i_cell < model::cells.size(); i_cell++) { - apply_external_source_to_cell_and_children( - i_cell, energy, strength_factor, material_id); + apply_external_source_to_cell_and_children(i_cell, es, material_id); } } } else if (is->domain_type() == Source::DomainType::CELL) { for (int32_t cell_id : domain_ids) { int32_t i_cell = model::cell_map[cell_id]; - apply_external_source_to_cell_and_children( - i_cell, energy, strength_factor, C_NONE); + apply_external_source_to_cell_and_children(i_cell, es, C_NONE); } } else if (is->domain_type() == Source::DomainType::UNIVERSE) { for (int32_t universe_id : domain_ids) { int32_t i_universe = model::universe_map[universe_id]; Universe& universe = *model::universes[i_universe]; for (int32_t i_cell : universe.cells_) { - apply_external_source_to_cell_and_children( - i_cell, energy, strength_factor, C_NONE); + apply_external_source_to_cell_and_children(i_cell, es, C_NONE); } } } } } // End loop over external sources - -// Divide the fixed source term by sigma t (to save time when applying each -// iteration) -#pragma omp parallel for - for (int64_t sr = 0; sr < n_source_regions(); sr++) { - int material = source_regions_.material(sr); - if (material == MATERIAL_VOID) { - continue; - } - for (int g = 0; g < negroups_; g++) { - double sigma_t = sigma_t_[material * negroups_ + g]; - source_regions_.external_source(sr, g) /= sigma_t; - } - } } void FlatSourceDomain::flux_swap() @@ -1159,13 +1118,23 @@ void FlatSourceDomain::flatten_xs() const int a = 0; n_materials_ = data::mg.macro_xs_.size(); - for (auto& m : data::mg.macro_xs_) { + for (int i = 0; i < n_materials_; i++) { + auto& m = data::mg.macro_xs_[i]; for (int g_out = 0; g_out < negroups_; g_out++) { if (m.exists_in_model) { double sigma_t = m.get_xs(MgxsType::TOTAL, g_out, NULL, NULL, NULL, t, a); sigma_t_.push_back(sigma_t); + if (sigma_t < MINIMUM_MACRO_XS) { + Material* mat = model::materials[i].get(); + warning(fmt::format( + "Material \"{}\" (id: {}) has a group {} total cross section " + "({:.3e}) below the minimum threshold " + "({:.3e}). Material will be treated as pure void.", + mat->name(), mat->id(), g_out, sigma_t, MINIMUM_MACRO_XS)); + } + double nu_sigma_f = m.get_xs(MgxsType::NU_FISSION, g_out, NULL, NULL, NULL, t, a); nu_sigma_f_.push_back(nu_sigma_f); @@ -1206,7 +1175,7 @@ void FlatSourceDomain::flatten_xs() } } -void FlatSourceDomain::set_adjoint_sources(const vector& forward_flux) +void FlatSourceDomain::set_adjoint_sources() { // Set the adjoint external source to 1/forward_flux. If the forward flux is // negative, zero, or extremely close to zero, set the adjoint source to zero, @@ -1220,7 +1189,7 @@ void FlatSourceDomain::set_adjoint_sources(const vector& forward_flux) double max_flux = 0.0; #pragma omp parallel for reduction(max : max_flux) for (int64_t se = 0; se < n_source_elements(); se++) { - double flux = forward_flux[se]; + double flux = source_regions_.scalar_flux_final(se); if (flux > max_flux) { max_flux = flux; } @@ -1230,7 +1199,7 @@ void FlatSourceDomain::set_adjoint_sources(const vector& forward_flux) #pragma omp parallel for for (int64_t sr = 0; sr < n_source_regions(); sr++) { for (int g = 0; g < negroups_; g++) { - double flux = forward_flux[sr * negroups_ + g]; + double flux = source_regions_.scalar_flux_final(sr, g); if (flux <= ZERO_FLUX_CUTOFF * max_flux) { source_regions_.external_source(sr, g) = 0.0; } else { @@ -1239,6 +1208,7 @@ void FlatSourceDomain::set_adjoint_sources(const vector& forward_flux) if (flux > 0.0) { source_regions_.external_source_present(sr) = 1; } + source_regions_.scalar_flux_final(sr, g) = 0.0; } } @@ -1265,7 +1235,6 @@ void FlatSourceDomain::set_adjoint_sources(const vector& forward_flux) source_regions_.external_source_present(sr) = 0; } } - // Divide the fixed source term by sigma t (to save time when applying each // iteration) #pragma omp parallel for @@ -1326,13 +1295,14 @@ void FlatSourceDomain::apply_mesh_to_cell_instances(int32_t i_cell, if ((target_material_id == C_NONE && !is_target_void) || cell_material_id == target_material_id) { int64_t sr = source_region_offsets_[i_cell] + j; - if (source_regions_.mesh(sr) != C_NONE) { - // print out the source region that is broken: + // Check if the key is already present in the mesh_map_ + if (mesh_map_.find(sr) != mesh_map_.end()) { fatal_error(fmt::format("Source region {} already has mesh idx {} " "applied, but trying to apply mesh idx {}", - sr, source_regions_.mesh(sr), mesh_idx)); + sr, mesh_map_[sr], mesh_idx)); } - source_regions_.mesh(sr) = mesh_idx; + // If the SR has not already been assigned, then we can write to it + mesh_map_[sr] = mesh_idx; } } } @@ -1402,18 +1372,9 @@ void FlatSourceDomain::apply_meshes() } } -void FlatSourceDomain::prepare_base_source_regions() -{ - std::swap(source_regions_, base_source_regions_); - source_regions_.negroups() = base_source_regions_.negroups(); - source_regions_.is_linear() = base_source_regions_.is_linear(); -} - SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( - int64_t sr, int mesh_bin, Position r, double dist, Direction u) + SourceRegionKey sr_key, Position r, Direction u) { - SourceRegionKey sr_key {sr, mesh_bin}; - // Case 1: Check if the source region key is already present in the permanent // map. This is the most common condition, as any source region visited in a // previous power iteration will already be present in the permanent map. If @@ -1475,9 +1436,8 @@ SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( gs.r() = r + TINY_BIT * u; gs.u() = {1.0, 0.0, 0.0}; exhaustive_find_cell(gs); - int gs_i_cell = gs.lowest_coord().cell(); - int64_t sr_found = source_region_offsets_[gs_i_cell] + gs.cell_instance(); - if (sr_found != sr) { + int64_t sr_found = lookup_base_source_region_idx(gs); + if (sr_found != sr_key.base_source_region_id) { discovered_source_regions_.unlock(sr_key); SourceRegionHandle handle; handle.is_numerical_fp_artifact_ = true; @@ -1485,9 +1445,9 @@ SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( } // Sanity check on mesh bin - int mesh_idx = base_source_regions_.mesh(sr); + int mesh_idx = lookup_mesh_idx(sr_key.base_source_region_id); if (mesh_idx == C_NONE) { - if (mesh_bin != 0) { + if (sr_key.mesh_bin != 0) { discovered_source_regions_.unlock(sr_key); SourceRegionHandle handle; handle.is_numerical_fp_artifact_ = true; @@ -1496,7 +1456,7 @@ SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( } else { Mesh* mesh = model::meshes[mesh_idx].get(); int bin_found = mesh->get_bin(r + TINY_BIT * u); - if (bin_found != mesh_bin) { + if (bin_found != sr_key.mesh_bin) { discovered_source_regions_.unlock(sr_key); SourceRegionHandle handle; handle.is_numerical_fp_artifact_ = true; @@ -1508,26 +1468,60 @@ SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( // condition only occurs the first time the source region is discovered // (typically in the first power iteration). In this case, we need to handle // creation of the new source region and its storage into the parallel map. - // The new source region is created by copying the base source region, so as - // to inherit material, external source, and some flux properties etc. We - // also pass the base source region id to allow the new source region to - // know which base source region it is derived from. - SourceRegion* sr_ptr = discovered_source_regions_.emplace( - sr_key, {base_source_regions_.get_source_region_handle(sr), sr}); - discovered_source_regions_.unlock(sr_key); + // Additionally, we need to determine the source region's material, initialize + // the starting scalar flux guess, and apply any known external sources. + + // Call the basic constructor for the source region and store in the parallel + // map. + bool is_linear = RandomRay::source_shape_ != RandomRaySourceShape::FLAT; + SourceRegion* sr_ptr = + discovered_source_regions_.emplace(sr_key, {negroups_, is_linear}); SourceRegionHandle handle {*sr_ptr}; - // Check if the new source region contains a point source and apply it if so - auto it2 = point_source_map_.find(sr_key); - if (it2 != point_source_map_.end()) { - int es = it2->second; - auto s = model::external_sources[es].get(); - auto is = dynamic_cast(s); - auto energy = dynamic_cast(is->energy()); - double strength_factor = is->strength(); - apply_external_source_to_source_region(energy, strength_factor, handle); - int material = handle.material(); - if (material != MATERIAL_VOID) { + // Determine the material + int gs_i_cell = gs.lowest_coord().cell(); + Cell& cell = *model::cells[gs_i_cell]; + int material = cell.material(gs.cell_instance()); + + // If material total XS is extremely low, just set it to void to avoid + // problems with 1/Sigma_t + for (int g = 0; g < negroups_; g++) { + double sigma_t = sigma_t_[material * negroups_ + g]; + if (sigma_t < MINIMUM_MACRO_XS) { + material = MATERIAL_VOID; + break; + } + } + + handle.material() = material; + + // Store the mesh index (if any) assigned to this source region + handle.mesh() = mesh_idx; + + if (settings::run_mode == RunMode::FIXED_SOURCE) { + // Determine if there are any volumetric sources, and apply them. + // Volumetric sources are specifc only to the base SR idx. + auto it_vol = + external_volumetric_source_map_.find(sr_key.base_source_region_id); + if (it_vol != external_volumetric_source_map_.end()) { + const vector& vol_sources = it_vol->second; + for (int src_idx : vol_sources) { + apply_external_source_to_source_region(src_idx, handle); + } + } + + // Determine if there are any point sources, and apply them. + // Point sources are specific to the source region key. + auto it_point = external_point_source_map_.find(sr_key); + if (it_point != external_point_source_map_.end()) { + const vector& point_sources = it_point->second; + for (int src_idx : point_sources) { + apply_external_source_to_source_region(src_idx, handle); + } + } + + // Divide external source term by sigma_t + if (material != C_NONE) { for (int g = 0; g < negroups_; g++) { double sigma_t = sigma_t_[material * negroups_ + g]; handle.external_source(g) /= sigma_t; @@ -1535,6 +1529,21 @@ SourceRegionHandle FlatSourceDomain::get_subdivided_source_region_handle( } } + // Compute the combined source term + update_single_neutron_source(handle); + + // Unlock the parallel map. Note: we may be tempted to release + // this lock earlier, and then just use the source region's lock to protect + // the flux/source initialization stages above. However, the rest of the code + // only protects updates to the new flux and volume fields, and assumes that + // the source is constant for the duration of transport. Thus, using just the + // source region's lock by itself would result in other threads potentially + // reading from the source before it is computed, as they won't use the lock + // when only reading from the SR's source. It would be expensive to protect + // those operations, whereas generating the SR is only done once, so we just + // hold the map's bucket lock until the source region is fully initialized. + discovered_source_regions_.unlock(sr_key); + return handle; } @@ -1620,4 +1629,52 @@ void FlatSourceDomain::apply_transport_stabilization() } } +// Determines the base source region index (i.e., a material filled cell +// instance) that corresponds to a particular location in the geometry. Requires +// that the "gs" object passed in has already been initialized and has called +// find_cell etc. +int64_t FlatSourceDomain::lookup_base_source_region_idx( + const GeometryState& gs) const +{ + int i_cell = gs.lowest_coord().cell(); + int64_t sr = source_region_offsets_[i_cell] + gs.cell_instance(); + return sr; +} + +// Determines the index of the mesh (if any) that has been applied +// to a particular base source region index. +int FlatSourceDomain::lookup_mesh_idx(int64_t sr) const +{ + int mesh_idx = C_NONE; + auto mesh_it = mesh_map_.find(sr); + if (mesh_it != mesh_map_.end()) { + mesh_idx = mesh_it->second; + } + return mesh_idx; +} + +// Determines the source region key that corresponds to a particular location in +// the geometry. This takes into account both the base source region index as +// well as the mesh bin if a mesh is applied to this source region for +// subdivision. +SourceRegionKey FlatSourceDomain::lookup_source_region_key( + const GeometryState& gs) const +{ + int64_t sr = lookup_base_source_region_idx(gs); + int64_t mesh_bin = lookup_mesh_bin(sr, gs.r()); + return SourceRegionKey {sr, mesh_bin}; +} + +// Determines the mesh bin that corresponds to a particular base source region +// index and position. +int64_t FlatSourceDomain::lookup_mesh_bin(int64_t sr, Position r) const +{ + int mesh_idx = lookup_mesh_idx(sr); + int mesh_bin = 0; + if (mesh_idx != C_NONE) { + mesh_bin = model::meshes[mesh_idx]->get_bin(r); + } + return mesh_bin; +} + } // namespace openmc diff --git a/src/random_ray/linear_source_domain.cpp b/src/random_ray/linear_source_domain.cpp index 81412164ec..47ffbb727b 100644 --- a/src/random_ray/linear_source_domain.cpp +++ b/src/random_ray/linear_source_domain.cpp @@ -34,25 +34,18 @@ void LinearSourceDomain::batch_reset() } } -void LinearSourceDomain::update_neutron_source(double k_eff) +void LinearSourceDomain::update_single_neutron_source(SourceRegionHandle& srh) { - simulation::time_update_src.start(); - - double inverse_k_eff = 1.0 / k_eff; - -// Reset all source regions to zero (important for void regions) -#pragma omp parallel for - for (int64_t se = 0; se < n_source_elements(); se++) { - source_regions_.source(se) = 0.0; + // Reset all source regions to zero (important for void regions) + for (int g = 0; g < negroups_; g++) { + srh.source(g) = 0.0; } -#pragma omp parallel for - for (int64_t sr = 0; sr < n_source_regions(); sr++) { - int material = source_regions_.material(sr); - if (material == MATERIAL_VOID) { - continue; - } - MomentMatrix invM = source_regions_.mom_matrix(sr).inverse(); + // Add scattering + fission source + int material = srh.material(); + if (material != MATERIAL_VOID) { + double inverse_k_eff = 1.0 / k_eff_; + MomentMatrix invM = srh.mom_matrix().inverse(); for (int g_out = 0; g_out < negroups_; g_out++) { double sigma_t = sigma_t_[material * negroups_ + g_out]; @@ -64,8 +57,8 @@ void LinearSourceDomain::update_neutron_source(double k_eff) for (int g_in = 0; g_in < negroups_; g_in++) { // Handles for the flat and linear components of the flux - double flux_flat = source_regions_.scalar_flux_old(sr, g_in); - MomentArray flux_linear = source_regions_.flux_moments_old(sr, g_in); + double flux_flat = srh.scalar_flux_old(g_in); + MomentArray flux_linear = srh.flux_moments_old(g_in); // Handles for cross sections double sigma_s = @@ -75,13 +68,15 @@ void LinearSourceDomain::update_neutron_source(double k_eff) // Compute source terms for flat and linear components of the flux scatter_flat += sigma_s * flux_flat; - fission_flat += nu_sigma_f * flux_flat * chi; scatter_linear += sigma_s * flux_linear; - fission_linear += nu_sigma_f * flux_linear * chi; + if (settings::create_fission_neutrons) { + fission_flat += nu_sigma_f * flux_flat * chi; + fission_linear += nu_sigma_f * flux_linear * chi; + } } // Compute the flat source term - source_regions_.source(sr, g_out) = + srh.source(g_out) = (scatter_flat + fission_flat * inverse_k_eff) / sigma_t; // Compute the linear source terms. In the first 10 iterations when the @@ -91,25 +86,21 @@ void LinearSourceDomain::update_neutron_source(double k_eff) // very small/noisy or have poorly developed spatial moments, so we zero // the source gradients (effectively making this a flat source region // temporarily), so as to improve stability. - if (simulation::current_batch > 10 && - source_regions_.source(sr, g_out) >= 0.0) { - source_regions_.source_gradients(sr, g_out) = + if (simulation::current_batch > 10 && srh.source(g_out) >= 0.0) { + srh.source_gradients(g_out) = invM * ((scatter_linear + fission_linear * inverse_k_eff) / sigma_t); } else { - source_regions_.source_gradients(sr, g_out) = {0.0, 0.0, 0.0}; + srh.source_gradients(g_out) = {0.0, 0.0, 0.0}; } } } + // Add external source if in fixed source mode if (settings::run_mode == RunMode::FIXED_SOURCE) { -// Add external source to flat source term if in fixed source mode -#pragma omp parallel for - for (int64_t se = 0; se < n_source_elements(); se++) { - source_regions_.source(se) += source_regions_.external_source(se); + for (int g = 0; g < negroups_; g++) { + srh.source(g) += srh.external_source(g); } } - - simulation::time_update_src.stop(); } void LinearSourceDomain::normalize_scalar_flux_and_volumes( diff --git a/src/random_ray/random_ray.cpp b/src/random_ray/random_ray.cpp index 27f674c427..c19d136a4a 100644 --- a/src/random_ray/random_ray.cpp +++ b/src/random_ray/random_ray.cpp @@ -237,7 +237,6 @@ double RandomRay::distance_inactive_; double RandomRay::distance_active_; unique_ptr RandomRay::ray_source_; RandomRaySourceShape RandomRay::source_shape_ {RandomRaySourceShape::FLAT}; -bool RandomRay::mesh_subdivision_enabled_ {false}; RandomRaySampleMethod RandomRay::sample_method_ {RandomRaySampleMethod::PRNG}; RandomRay::RandomRay() @@ -279,6 +278,10 @@ uint64_t RandomRay::transport_history_based_single_ray() // Transports ray across a single source region void RandomRay::event_advance_ray() { + // If geometry debug mode is on, check for cell overlaps + if (settings::check_overlaps) + check_cell_overlap(*this); + // Find the distance to the nearest boundary boundary() = distance_to_boundary(*this); double distance = boundary().distance(); @@ -336,71 +339,60 @@ void RandomRay::event_advance_ray() void RandomRay::attenuate_flux(double distance, bool is_active, double offset) { - // Determine source region index etc. - int i_cell = lowest_coord().cell(); - - // The base source region is the spatial region index - int64_t sr = domain_->source_region_offsets_[i_cell] + cell_instance(); + // Lookup base source region index + int64_t sr = domain_->lookup_base_source_region_idx(*this); // Perform ray tracing across mesh - if (mesh_subdivision_enabled_) { - // Determine the mesh index for the base source region, if any - int mesh_idx = domain_->base_source_regions_.mesh(sr); + // Determine the mesh index for the base source region, if any + int mesh_idx = domain_->lookup_mesh_idx(sr); - if (mesh_idx == C_NONE) { - // If there's no mesh being applied to this cell, then - // we just attenuate the flux as normal, and set - // the mesh bin to 0 - attenuate_flux_inner(distance, is_active, sr, 0, r()); - } else { - // If there is a mesh being applied to this cell, then - // we loop over all the bin crossings and attenuate - // separately. - Mesh* mesh = model::meshes[mesh_idx].get(); - - // We adjust the start and end positions of the ray slightly - // to accomodate for floating point precision issues that tend - // to occur at mesh boundaries that overlap with geometry lattice - // boundaries. - Position start = r() + (offset + TINY_BIT) * u(); - Position end = start + (distance - 2.0 * TINY_BIT) * u(); - double reduced_distance = (end - start).norm(); - - // Ray trace through the mesh and record bins and lengths - mesh_bins_.resize(0); - mesh_fractional_lengths_.resize(0); - mesh->bins_crossed(start, end, u(), mesh_bins_, mesh_fractional_lengths_); - - // Loop over all mesh bins and attenuate flux - for (int b = 0; b < mesh_bins_.size(); b++) { - double physical_length = reduced_distance * mesh_fractional_lengths_[b]; - attenuate_flux_inner( - physical_length, is_active, sr, mesh_bins_[b], start); - start += physical_length * u(); - } - } + if (mesh_idx == C_NONE) { + // If there's no mesh being applied to this cell, then + // we just attenuate the flux as normal, and set + // the mesh bin to 0 + attenuate_flux_inner(distance, is_active, sr, 0, r()); } else { - attenuate_flux_inner(distance, is_active, sr, C_NONE, r()); + // If there is a mesh being applied to this cell, then + // we loop over all the bin crossings and attenuate + // separately. + Mesh* mesh = model::meshes[mesh_idx].get(); + + // We adjust the start and end positions of the ray slightly + // to accomodate for floating point precision issues that tend + // to occur at mesh boundaries that overlap with geometry lattice + // boundaries. + Position start = r() + (offset + TINY_BIT) * u(); + Position end = start + (distance - 2.0 * TINY_BIT) * u(); + double reduced_distance = (end - start).norm(); + + // Ray trace through the mesh and record bins and lengths + mesh_bins_.resize(0); + mesh_fractional_lengths_.resize(0); + mesh->bins_crossed(start, end, u(), mesh_bins_, mesh_fractional_lengths_); + + // Loop over all mesh bins and attenuate flux + for (int b = 0; b < mesh_bins_.size(); b++) { + double physical_length = reduced_distance * mesh_fractional_lengths_[b]; + attenuate_flux_inner( + physical_length, is_active, sr, mesh_bins_[b], start); + start += physical_length * u(); + } } } void RandomRay::attenuate_flux_inner( double distance, bool is_active, int64_t sr, int mesh_bin, Position r) { + SourceRegionKey sr_key {sr, mesh_bin}; SourceRegionHandle srh; - if (mesh_subdivision_enabled_) { - srh = domain_->get_subdivided_source_region_handle( - sr, mesh_bin, r, distance, u()); - if (srh.is_numerical_fp_artifact_) { - return; - } - } else { - srh = domain_->source_regions_.get_source_region_handle(sr); + srh = domain_->get_subdivided_source_region_handle(sr_key, r, u()); + if (srh.is_numerical_fp_artifact_) { + return; } switch (source_shape_) { case RandomRaySourceShape::FLAT: - if (this->material() == MATERIAL_VOID) { + if (srh.material() == MATERIAL_VOID) { attenuate_flux_flat_source_void(srh, distance, is_active, r); } else { attenuate_flux_flat_source(srh, distance, is_active, r); @@ -408,7 +400,7 @@ void RandomRay::attenuate_flux_inner( break; case RandomRaySourceShape::LINEAR: case RandomRaySourceShape::LINEAR_XY: - if (this->material() == MATERIAL_VOID) { + if (srh.material() == MATERIAL_VOID) { attenuate_flux_linear_source_void(srh, distance, is_active, r); } else { attenuate_flux_linear_source(srh, distance, is_active, r); @@ -439,7 +431,7 @@ void RandomRay::attenuate_flux_flat_source( n_event()++; // Get material - int material = this->material(); + int material = srh.material(); // MOC incoming flux attenuation + source contribution/attenuation equation for (int g = 0; g < negroups_; g++) { @@ -490,7 +482,7 @@ void RandomRay::attenuate_flux_flat_source_void( // The number of geometric intersections is counted for reporting purposes n_event()++; - int material = this->material(); + int material = srh.material(); // If ray is in the active phase (not in dead zone), make contributions to // source region bookkeeping @@ -537,7 +529,7 @@ void RandomRay::attenuate_flux_linear_source( // The number of geometric intersections is counted for reporting purposes n_event()++; - int material = this->material(); + int material = srh.material(); Position& centroid = srh.centroid(); Position midpoint = r + u() * (distance / 2.0); @@ -810,27 +802,12 @@ void RandomRay::initialize_ray(uint64_t ray_id, FlatSourceDomain* domain) cell_born() = lowest_coord().cell(); } + SourceRegionKey sr_key = domain_->lookup_source_region_key(*this); + SourceRegionHandle srh = + domain_->get_subdivided_source_region_handle(sr_key, r(), u()); + // Initialize ray's starting angular flux to starting location's isotropic // source - int i_cell = lowest_coord().cell(); - int64_t sr = domain_->source_region_offsets_[i_cell] + cell_instance(); - - SourceRegionHandle srh; - if (mesh_subdivision_enabled_) { - int mesh_idx = domain_->base_source_regions_.mesh(sr); - int mesh_bin; - if (mesh_idx == C_NONE) { - mesh_bin = 0; - } else { - Mesh* mesh = model::meshes[mesh_idx].get(); - mesh_bin = mesh->get_bin(r()); - } - srh = - domain_->get_subdivided_source_region_handle(sr, mesh_bin, r(), 0.0, u()); - } else { - srh = domain_->source_regions_.get_source_region_handle(sr); - } - if (!srh.is_numerical_fp_artifact_) { for (int g = 0; g < negroups_; g++) { angular_flux_[g] = srh.source(g); diff --git a/src/random_ray/random_ray_simulation.cpp b/src/random_ray/random_ray_simulation.cpp index 388a778b84..d475b2593e 100644 --- a/src/random_ray/random_ray_simulation.cpp +++ b/src/random_ray/random_ray_simulation.cpp @@ -47,97 +47,82 @@ void openmc_run_random_ray() if (mpi::master) validate_random_ray_inputs(); - // Declare forward flux so that it can be saved for later adjoint simulation - vector forward_flux; - SourceRegionContainer forward_source_regions; - SourceRegionContainer forward_base_source_regions; - std::unordered_map - forward_source_region_map; + // Initialize Random Ray Simulation Object + RandomRaySimulation sim; - { - // Initialize Random Ray Simulation Object - RandomRaySimulation sim; + // Initialize fixed sources, if present + sim.apply_fixed_sources_and_mesh_domains(); - // Initialize fixed sources, if present - sim.apply_fixed_sources_and_mesh_domains(); + // Begin main simulation timer + simulation::time_total.start(); - // Begin main simulation timer - simulation::time_total.start(); + // Execute random ray simulation + sim.simulate(); - // Execute random ray simulation - sim.simulate(); + // End main simulation timer + simulation::time_total.stop(); - // End main simulation timer - simulation::time_total.stop(); - - // Normalize and save the final forward flux - sim.domain()->serialize_final_fluxes(forward_flux); - - double source_normalization_factor = - sim.domain()->compute_fixed_source_normalization_factor() / - (settings::n_batches - settings::n_inactive); + // Normalize and save the final forward flux + double source_normalization_factor = + sim.domain()->compute_fixed_source_normalization_factor() / + (settings::n_batches - settings::n_inactive); #pragma omp parallel for - for (uint64_t i = 0; i < forward_flux.size(); i++) { - forward_flux[i] *= source_normalization_factor; - } - - forward_source_regions = sim.domain()->source_regions_; - forward_source_region_map = sim.domain()->source_region_map_; - forward_base_source_regions = sim.domain()->base_source_regions_; - - // Finalize OpenMC - openmc_simulation_finalize(); - - // Output all simulation results - sim.output_simulation_results(); + for (uint64_t se = 0; se < sim.domain()->n_source_elements(); se++) { + sim.domain()->source_regions_.scalar_flux_final(se) *= + source_normalization_factor; } + // Finalize OpenMC + openmc_simulation_finalize(); + + // Output all simulation results + sim.output_simulation_results(); + ////////////////////////////////////////////////////////// // Run adjoint simulation (if enabled) ////////////////////////////////////////////////////////// - if (adjoint_needed) { - reset_timers(); - - // Configure the domain for adjoint simulation - FlatSourceDomain::adjoint_ = true; - - if (mpi::master) - header("ADJOINT FLUX SOLVE", 3); - - // Initialize OpenMC general data structures - openmc_simulation_init(); - - // Initialize Random Ray Simulation Object - RandomRaySimulation adjoint_sim; - - // Initialize adjoint fixed sources, if present - adjoint_sim.prepare_fixed_sources_adjoint(forward_flux, - forward_source_regions, forward_base_source_regions, - forward_source_region_map); - - // Transpose scattering matrix - adjoint_sim.domain()->transpose_scattering_matrix(); - - // Swap nu_sigma_f and chi - adjoint_sim.domain()->nu_sigma_f_.swap(adjoint_sim.domain()->chi_); - - // Begin main simulation timer - simulation::time_total.start(); - - // Execute random ray simulation - adjoint_sim.simulate(); - - // End main simulation timer - simulation::time_total.stop(); - - // Finalize OpenMC - openmc_simulation_finalize(); - - // Output all simulation results - adjoint_sim.output_simulation_results(); + if (!adjoint_needed) { + return; } + + reset_timers(); + + // Configure the domain for adjoint simulation + FlatSourceDomain::adjoint_ = true; + + if (mpi::master) + header("ADJOINT FLUX SOLVE", 3); + + // Initialize OpenMC general data structures + openmc_simulation_init(); + + sim.domain()->k_eff_ = 1.0; + + // Initialize adjoint fixed sources, if present + sim.prepare_fixed_sources_adjoint(); + + // Transpose scattering matrix + sim.domain()->transpose_scattering_matrix(); + + // Swap nu_sigma_f and chi + sim.domain()->nu_sigma_f_.swap(sim.domain()->chi_); + + // Begin main simulation timer + simulation::time_total.start(); + + // Execute random ray simulation + sim.simulate(); + + // End main simulation timer + simulation::time_total.stop(); + + // Finalize OpenMC + openmc_simulation_finalize(); + + // Output all simulation results + sim.output_simulation_results(); } // Enforces restrictions on inputs in random ray mode. While there are @@ -348,7 +333,6 @@ void validate_random_ray_inputs() // when generating weight windows with FW-CADIS and an overlaid mesh. /////////////////////////////////////////////////////////////////// if (RandomRay::source_shape_ == RandomRaySourceShape::LINEAR && - RandomRay::mesh_subdivision_enabled_ && variance_reduction::weight_windows.size() > 0) { warning( "Linear sources may result in negative fluxes in small source regions " @@ -366,7 +350,6 @@ void openmc_reset_random_ray() FlatSourceDomain::mesh_domain_map_.clear(); RandomRay::ray_source_.reset(); RandomRay::source_shape_ = RandomRaySourceShape::FLAT; - RandomRay::mesh_subdivision_enabled_ = false; RandomRay::sample_method_ = RandomRaySampleMethod::PRNG; } @@ -412,20 +395,11 @@ void RandomRaySimulation::apply_fixed_sources_and_mesh_domains() } } -void RandomRaySimulation::prepare_fixed_sources_adjoint( - vector& forward_flux, SourceRegionContainer& forward_source_regions, - SourceRegionContainer& forward_base_source_regions, - std::unordered_map& - forward_source_region_map) +void RandomRaySimulation::prepare_fixed_sources_adjoint() { + domain_->source_regions_.adjoint_reset(); if (settings::run_mode == RunMode::FIXED_SOURCE) { - if (RandomRay::mesh_subdivision_enabled_) { - domain_->source_regions_ = forward_source_regions; - domain_->source_region_map_ = forward_source_region_map; - domain_->base_source_regions_ = forward_base_source_regions; - domain_->source_regions_.adjoint_reset(); - } - domain_->set_adjoint_sources(forward_flux); + domain_->set_adjoint_sources(); } } @@ -445,22 +419,18 @@ void RandomRaySimulation::simulate() simulation::total_weight = 1.0; // Update source term (scattering + fission) - domain_->update_neutron_source(k_eff_); + domain_->update_all_neutron_sources(); - // Reset scalar fluxes, iteration volume tallies, and region hit flags to - // zero + // Reset scalar fluxes, iteration volume tallies, and region hit flags + // to zero domain_->batch_reset(); - // At the beginning of the simulation, if mesh subvivision is in use, we + // At the beginning of the simulation, if mesh subdivision is in use, we // need to swap the main source region container into the base container, // as the main source region container will be used to hold the true // subdivided source regions. The base container will therefore only // contain the external source region information, the mesh indices, // material properties, and initial guess values for the flux/source. - if (RandomRay::mesh_subdivision_enabled_ && - simulation::current_batch == 1 && !FlatSourceDomain::adjoint_) { - domain_->prepare_base_source_regions(); - } // Start timer for transport simulation::time_transport.start(); @@ -476,11 +446,9 @@ void RandomRaySimulation::simulate() simulation::time_transport.stop(); - // If using mesh subdivision, add any newly discovered source regions - // to the main source region container. - if (RandomRay::mesh_subdivision_enabled_) { - domain_->finalize_discovered_source_regions(); - } + // Add any newly discovered source regions to the main source region + // container. + domain_->finalize_discovered_source_regions(); // Normalize scalar flux and update volumes domain_->normalize_scalar_flux_and_volumes( @@ -494,10 +462,10 @@ void RandomRaySimulation::simulate() if (settings::run_mode == RunMode::EIGENVALUE) { // Compute random ray k-eff - k_eff_ = domain_->compute_k_eff(k_eff_); + domain_->compute_k_eff(); // Store random ray k-eff into OpenMC's native k-eff variable - global_tally_tracklength = k_eff_; + global_tally_tracklength = domain_->k_eff_; } // Execute all tallying tasks, if this is an active batch @@ -507,12 +475,6 @@ void RandomRaySimulation::simulate() // estimate domain_->accumulate_iteration_flux(); - // Generate mapping between source regions and tallies - if (!domain_->mapped_all_tallies_ && - !RandomRay::mesh_subdivision_enabled_) { - domain_->convert_source_regions_to_tallies(0); - } - // Use above mapping to contribute FSR flux data to appropriate // tallies domain_->random_ray_tally(); @@ -522,7 +484,7 @@ void RandomRaySimulation::simulate() domain_->flux_swap(); // Check for any obvious insabilities/nans/infs - instability_check(n_hits, k_eff_, avg_miss_rate_); + instability_check(n_hits, domain_->k_eff_, avg_miss_rate_); } // End MPI master work // Finalize the current batch @@ -571,7 +533,7 @@ void RandomRaySimulation::instability_check( } if (k_eff > 10.0 || k_eff < 0.01 || !(std::isfinite(k_eff))) { - fatal_error("Instability detected"); + fatal_error(fmt::format("Instability detected: k-eff = {:.5f}", k_eff)); } } } diff --git a/src/random_ray/source_region.cpp b/src/random_ray/source_region.cpp index 1205b995a6..3b06f0ed09 100644 --- a/src/random_ray/source_region.cpp +++ b/src/random_ray/source_region.cpp @@ -48,7 +48,7 @@ SourceRegion::SourceRegion(int negroups, bool is_linear) } scalar_flux_new_.assign(negroups, 0.0); - source_.resize(negroups); + source_.assign(negroups, 0.0); scalar_flux_final_.assign(negroups, 0.0); tally_task_.resize(negroups); @@ -60,25 +60,6 @@ SourceRegion::SourceRegion(int negroups, bool is_linear) } } -SourceRegion::SourceRegion(const SourceRegionHandle& handle, int64_t parent_sr) - : SourceRegion(handle.negroups_, handle.is_linear_) -{ - material_ = handle.material(); - mesh_ = handle.mesh(); - parent_sr_ = parent_sr; - for (int g = 0; g < scalar_flux_new_.size(); g++) { - scalar_flux_old_[g] = handle.scalar_flux_old(g); - source_[g] = handle.source(g); - } - - if (settings::run_mode == RunMode::FIXED_SOURCE) { - external_source_present_ = handle.external_source_present(); - for (int g = 0; g < scalar_flux_new_.size(); g++) { - external_source_[g] = handle.external_source(g); - } - } -} - //============================================================================== // SourceRegionContainer implementation //============================================================================== @@ -259,9 +240,12 @@ void SourceRegionContainer::adjoint_reset() MomentMatrix {0.0, 0.0, 0.0, 0.0, 0.0, 0.0}); std::fill(mom_matrix_t_.begin(), mom_matrix_t_.end(), MomentMatrix {0.0, 0.0, 0.0, 0.0, 0.0, 0.0}); - std::fill(scalar_flux_old_.begin(), scalar_flux_old_.end(), 0.0); + if (settings::run_mode == RunMode::FIXED_SOURCE) { + std::fill(scalar_flux_old_.begin(), scalar_flux_old_.end(), 0.0); + } else { + std::fill(scalar_flux_old_.begin(), scalar_flux_old_.end(), 1.0); + } std::fill(scalar_flux_new_.begin(), scalar_flux_new_.end(), 0.0); - std::fill(scalar_flux_final_.begin(), scalar_flux_final_.end(), 0.0); std::fill(source_.begin(), source_.end(), 0.0f); std::fill(external_source_.begin(), external_source_.end(), 0.0f); std::fill(source_gradients_.begin(), source_gradients_.end(), diff --git a/src/settings.cpp b/src/settings.cpp index afa42a3c5e..5b472468fc 100644 --- a/src/settings.cpp +++ b/src/settings.cpp @@ -11,6 +11,7 @@ #endif #include "openmc/capi.h" +#include "openmc/collision_track.h" #include "openmc/constants.h" #include "openmc/container_util.h" #include "openmc/distribution.h" @@ -26,6 +27,7 @@ #include "openmc/plot.h" #include "openmc/random_lcg.h" #include "openmc/random_ray/random_ray.h" +#include "openmc/reaction.h" #include "openmc/simulation.h" #include "openmc/source.h" #include "openmc/string_utils.h" @@ -45,6 +47,7 @@ namespace settings { // Default values for boolean flags bool assume_separate {false}; bool check_overlaps {false}; +bool collision_track {false}; bool cmfd_run {false}; bool confidence_intervals {false}; bool create_delayed_neutrons {true}; @@ -114,6 +117,7 @@ int max_order {0}; int n_log_bins {8000}; int n_batches; int n_max_batches; +int max_secondaries {10000}; int max_history_splits {10'000'000}; int max_tracks {1000}; ResScatMethod res_scat_method {ResScatMethod::rvs}; @@ -125,7 +129,9 @@ SolverType solver_type {SolverType::MONTE_CARLO}; std::unordered_set sourcepoint_batch; std::unordered_set statepoint_batch; double source_rejection_fraction {0.05}; +double free_gas_threshold {400.0}; std::unordered_set source_write_surf_id; +CollisionTrackConfig collision_track_config {}; int64_t ssw_max_particles; int64_t ssw_max_files; int64_t ssw_cell_id {C_NONE}; @@ -139,7 +145,7 @@ int trace_gen; int64_t trace_particle; vector> track_identifiers; int trigger_batch_interval {1}; -int verbosity {7}; +int verbosity {-1}; double weight_cutoff {0.25}; double weight_survive {1.0}; @@ -345,7 +351,6 @@ void get_run_parameters(pugi::xml_node node_base) } FlatSourceDomain::mesh_domain_map_[mesh_id].emplace_back( type, domain_id); - RandomRay::mesh_subdivision_enabled_ = true; } } } @@ -391,8 +396,10 @@ void read_settings_xml() xml_node root = doc.document_element(); // Verbosity - if (check_for_node(root, "verbosity")) { + if (check_for_node(root, "verbosity") && verbosity == -1) { verbosity = std::stoi(get_node_value(root, "verbosity")); + } else if (verbosity == -1) { + verbosity = 7; } // To this point, we haven't displayed any output since we didn't know what @@ -540,6 +547,20 @@ void read_settings_xml(pugi::xml_node root) } else if (rel_max_lost_particles <= 0.0 || rel_max_lost_particles >= 1.0) { fatal_error("Relative max lost particles must be between zero and one."); } + + // Check for user value for the number of generation of the Iterated Fission + // Probability (IFP) method + if (check_for_node(root, "ifp_n_generation")) { + ifp_n_generation = std::stoi(get_node_value(root, "ifp_n_generation")); + if (ifp_n_generation <= 0) { + fatal_error("'ifp_n_generation' must be greater than 0."); + } + // Avoid tallying 0 if IFP logs are not complete when active cycles start + if (ifp_n_generation > n_inactive) { + fatal_error("'ifp_n_generation' must be lower than or equal to the " + "number of inactive cycles."); + } + } } // Copy plotting random number seed if specified @@ -651,6 +672,10 @@ void read_settings_xml(pugi::xml_node root) std::stod(get_node_value(root, "source_rejection_fraction")); } + if (check_for_node(root, "free_gas_threshold")) { + free_gas_threshold = std::stod(get_node_value(root, "free_gas_threshold")); + } + // Survival biasing if (check_for_node(root, "survival_biasing")) { survival_biasing = get_node_value_bool(root, "survival_biasing"); @@ -920,8 +945,72 @@ void read_settings_xml(pugi::xml_node root) } } - // If source is not separate and is to be written out in the statepoint file, - // make sure that the sourcepoint batch numbers are contained in the + // Check if the user has specified to write specific collisions + if (check_for_node(root, "collision_track")) { + settings::collision_track = true; + // Get collision track node + xml_node node_ct = root.child("collision_track"); + collision_track_config = CollisionTrackConfig {}; + + // Determine cell ids at which crossing particles are to be banked + if (check_for_node(node_ct, "cell_ids")) { + auto temp = get_node_array(node_ct, "cell_ids"); + for (const auto& b : temp) { + collision_track_config.cell_ids.insert(b); + } + } + if (check_for_node(node_ct, "reactions")) { + auto temp = get_node_array(node_ct, "reactions"); + for (const auto& b : temp) { + int reaction_int = reaction_type(b); + if (reaction_int > 0) { + collision_track_config.mt_numbers.insert(reaction_int); + } + } + } + if (check_for_node(node_ct, "universe_ids")) { + auto temp = get_node_array(node_ct, "universe_ids"); + for (const auto& b : temp) { + collision_track_config.universe_ids.insert(b); + } + } + if (check_for_node(node_ct, "material_ids")) { + auto temp = get_node_array(node_ct, "material_ids"); + for (const auto& b : temp) { + collision_track_config.material_ids.insert(b); + } + } + if (check_for_node(node_ct, "nuclides")) { + auto temp = get_node_array(node_ct, "nuclides"); + for (const auto& b : temp) { + collision_track_config.nuclides.insert(b); + } + } + if (check_for_node(node_ct, "deposited_E_threshold")) { + collision_track_config.deposited_energy_threshold = + std::stod(get_node_value(node_ct, "deposited_E_threshold")); + } + // Get maximum number of particles to be banked per collision + if (check_for_node(node_ct, "max_collisions")) { + collision_track_config.max_collisions = + std::stoll(get_node_value(node_ct, "max_collisions")); + } else { + warning("A maximum number of collisions needs to be specified. " + "By default the code sets 'max_collisions' parameter equals to " + "1000."); + } + // Get maximum number of collision_track files to be created + if (check_for_node(node_ct, "max_collision_track_files")) { + collision_track_config.max_files = + std::stoll(get_node_value(node_ct, "max_collision_track_files")); + } + if (check_for_node(node_ct, "mcpl")) { + collision_track_config.mcpl_write = get_node_value_bool(node_ct, "mcpl"); + } + } + + // If source is not separate and is to be written out in the statepoint + // file, make sure that the sourcepoint batch numbers are contained in the // statepoint list if (!source_separate) { for (const auto& b : sourcepoint_batch) { @@ -1057,20 +1146,6 @@ void read_settings_xml(pugi::xml_node root) temperature_range[1] = range.at(1); } - // Check for user value for the number of generation of the Iterated Fission - // Probability (IFP) method - if (check_for_node(root, "ifp_n_generation")) { - ifp_n_generation = std::stoi(get_node_value(root, "ifp_n_generation")); - if (ifp_n_generation <= 0) { - fatal_error("'ifp_n_generation' must be greater than 0."); - } - // Avoid tallying 0 if IFP logs are not complete when active cycles start - if (ifp_n_generation > n_inactive) { - fatal_error("'ifp_n_generation' must be lower than or equal to the " - "number of inactive cycles."); - } - } - // Check for tabular_legendre options if (check_for_node(root, "tabular_legendre")) { // Get pointer to tabular_legendre node @@ -1144,6 +1219,11 @@ void read_settings_xml(pugi::xml_node root) weight_windows_on = get_node_value_bool(root, "weight_windows_on"); } + if (check_for_node(root, "max_secondaries")) { + settings::max_secondaries = + std::stoi(get_node_value(root, "max_secondaries")); + } + if (check_for_node(root, "max_history_splits")) { settings::max_history_splits = std::stoi(get_node_value(root, "max_history_splits")); @@ -1161,8 +1241,8 @@ void read_settings_xml(pugi::xml_node root) variance_reduction::weight_windows_generators.emplace_back( std::make_unique(node_wwg)); } - // if any of the weight windows are intended to be generated otf, make sure - // they're applied + // if any of the weight windows are intended to be generated otf, make + // sure they're applied for (const auto& wwg : variance_reduction::weight_windows_generators) { if (wwg->on_the_fly_) { settings::weight_windows_on = true; @@ -1210,11 +1290,6 @@ extern "C" int openmc_set_n_batches( return OPENMC_E_INVALID_ARGUMENT; } - if (simulation::current_batch >= n_batches) { - set_errmsg("Number of batches must be greater than current batch."); - return OPENMC_E_INVALID_ARGUMENT; - } - if (!settings::trigger_on) { // Set n_batches and n_max_batches to same value settings::n_batches = n_batches; diff --git a/src/simulation.cpp b/src/simulation.cpp index b9986f4737..b536ae5881 100644 --- a/src/simulation.cpp +++ b/src/simulation.cpp @@ -2,6 +2,7 @@ #include "openmc/bank.h" #include "openmc/capi.h" +#include "openmc/collision_track.h" #include "openmc/container_util.h" #include "openmc/eigenvalue.h" #include "openmc/error.h" @@ -9,7 +10,6 @@ #include "openmc/geometry_aux.h" #include "openmc/ifp.h" #include "openmc/material.h" -#include "openmc/mcpl_interface.h" #include "openmc/message_passing.h" #include "openmc/nuclide.h" #include "openmc/output.h" @@ -118,6 +118,7 @@ int openmc_simulation_init() // Reset global variables -- this is done before loading state point (as that // will potentially populate k_generation and entropy) simulation::current_batch = 0; + simulation::ct_current_file = 1; simulation::ssw_current_file = 1; simulation::k_generation.clear(); simulation::entropy.clear(); @@ -297,6 +298,7 @@ namespace openmc { namespace simulation { +int ct_current_file; int current_batch; int current_gen; bool initialized {false}; @@ -347,6 +349,11 @@ void allocate_banks() // Allocate surface source bank simulation::surf_source_bank.reserve(settings::ssw_max_particles); } + + if (settings::collision_track) { + // Allocate collision track bank + collision_track_reserve_bank(); + } } void initialize_batch() @@ -400,11 +407,8 @@ void finalize_batch() simulation::time_tallies.stop(); // update weight windows if needed - if (settings::solver_type != SolverType::RANDOM_RAY || - simulation::current_batch == settings::n_batches) { - for (const auto& wwg : variance_reduction::weight_windows_generators) { - wwg->update(); - } + for (const auto& wwg : variance_reduction::weight_windows_generators) { + wwg->update(); } // Reset global tally results @@ -493,6 +497,10 @@ void finalize_batch() ++simulation::ssw_current_file; } } + // Write collision track file if requested + if (settings::collision_track) { + collision_track_flush_bank(); + } } void initialize_generation() @@ -674,8 +682,9 @@ void calculate_work() void initialize_data() { // Determine minimum/maximum energy for incident neutron/photon data - data::energy_max = {INFTY, INFTY}; - data::energy_min = {0.0, 0.0}; + data::energy_max = {INFTY, INFTY, INFTY, INFTY}; + data::energy_min = {0.0, 0.0, 0.0, 0.0}; + for (const auto& nuc : data::nuclides) { if (nuc->grid_.size() >= 1) { int neutron = static_cast(ParticleType::neutron); @@ -703,11 +712,21 @@ void initialize_data() // than the current minimum/maximum if (data::ttb_e_grid.size() >= 1) { int photon = static_cast(ParticleType::photon); + int electron = static_cast(ParticleType::electron); + int positron = static_cast(ParticleType::positron); int n_e = data::ttb_e_grid.size(); + + const std::vector charged = {electron, positron}; + for (auto t : charged) { + data::energy_min[t] = std::exp(data::ttb_e_grid(1)); + data::energy_max[t] = std::exp(data::ttb_e_grid(n_e - 1)); + } + data::energy_min[photon] = - std::max(data::energy_min[photon], std::exp(data::ttb_e_grid(1))); - data::energy_max[photon] = std::min( - data::energy_max[photon], std::exp(data::ttb_e_grid(n_e - 1))); + std::max(data::energy_min[photon], data::energy_min[electron]); + + data::energy_max[photon] = + std::min(data::energy_max[photon], data::energy_max[electron]); } } } diff --git a/src/source.cpp b/src/source.cpp index 12323f7bd7..f6aa665ebd 100644 --- a/src/source.cpp +++ b/src/source.cpp @@ -290,6 +290,12 @@ IndependentSource::IndependentSource(pugi::xml_node node) : Source(node) } else if (temp_str == "photon") { particle_ = ParticleType::photon; settings::photon_transport = true; + } else if (temp_str == "electron") { + particle_ = ParticleType::electron; + settings::photon_transport = true; + } else if (temp_str == "positron") { + particle_ = ParticleType::positron; + settings::photon_transport = true; } else { fatal_error(std::string("Unknown source particle type: ") + temp_str); } diff --git a/src/state_point.cpp b/src/state_point.cpp index 8195c48650..8ccebeb05a 100644 --- a/src/state_point.cpp +++ b/src/state_point.cpp @@ -9,6 +9,7 @@ #include #include "openmc/bank.h" +#include "openmc/bank_io.h" #include "openmc/capi.h" #include "openmc/constants.h" #include "openmc/eigenvalue.h" @@ -201,6 +202,12 @@ extern "C" int openmc_statepoint_write(const char* filename, bool* write_source) write_attribute(tally_group, "multiply_density", 0); } + if (tally->higher_moments()) { + write_attribute(tally_group, "higher_moments", 1); + } else { + write_attribute(tally_group, "higher_moments", 0); + } + if (tally->estimator_ == TallyEstimator::ANALOG) { write_dataset(tally_group, "estimator", "analog"); } else if (tally->estimator_ == TallyEstimator::TRACKLENGTH) { @@ -264,12 +271,13 @@ extern "C" int openmc_statepoint_write(const char* filename, bool* write_source) for (const auto& tally : model::tallies) { if (!tally->writable_) continue; - // Write sum and sum_sq for each bin + + // Write results for each bin std::string name = "tally " + std::to_string(tally->id_); hid_t tally_group = open_group(tallies_group, name.c_str()); auto& results = tally->results_; write_tally_results(tally_group, results.shape()[0], - results.shape()[1], results.data()); + results.shape()[1], results.shape()[2], results.data()); close_group(tally_group); } } else { @@ -509,7 +517,8 @@ extern "C" int openmc_statepoint_load(const char* filename) } else { auto& results = tally->results_; read_tally_results(tally_group, results.shape()[0], - results.shape()[1], results.data()); + results.shape()[1], results.shape()[2], results.data()); + read_dataset(tally_group, "n_realizations", tally->n_realizations_); close_group(tally_group); } @@ -545,7 +554,7 @@ extern "C" int openmc_statepoint_load(const char* filename) return 0; } -hid_t h5banktype() +hid_t h5banktype(bool memory) { // Create compound type for position hid_t postype = H5Tcreate(H5T_COMPOUND, sizeof(struct Position)); @@ -560,7 +569,10 @@ hid_t h5banktype() // - openmc/statepoint.py // - docs/source/io_formats/statepoint.rst // - docs/source/io_formats/source.rst - hid_t banktype = H5Tcreate(H5T_COMPOUND, sizeof(struct SourceSite)); + auto n = sizeof(SourceSite); + if (!memory) + n = 2 * sizeof(struct Position) + 3 * sizeof(double) + 3 * sizeof(int); + hid_t banktype = H5Tcreate(H5T_COMPOUND, n); H5Tinsert(banktype, "r", HOFFSET(SourceSite, r), postype); H5Tinsert(banktype, "u", HOFFSET(SourceSite, u), postype); H5Tinsert(banktype, "E", HOFFSET(SourceSite, E), H5T_NATIVE_DOUBLE); @@ -632,96 +644,19 @@ void write_h5_source_point(const char* filename, span source_bank, void write_source_bank(hid_t group_id, span source_bank, const vector& bank_index) { - hid_t banktype = h5banktype(); - - // Set total and individual process dataspace sizes for source bank - int64_t dims_size = bank_index.back(); - int64_t count_size = bank_index[mpi::rank + 1] - bank_index[mpi::rank]; - -#ifdef PHDF5 - // Set size of total dataspace for all procs and rank - hsize_t dims[] {static_cast(dims_size)}; - hid_t dspace = H5Screate_simple(1, dims, nullptr); - hid_t dset = H5Dcreate(group_id, "source_bank", banktype, dspace, H5P_DEFAULT, - H5P_DEFAULT, H5P_DEFAULT); - - // Create another data space but for each proc individually - hsize_t count[] {static_cast(count_size)}; - hid_t memspace = H5Screate_simple(1, count, nullptr); - - // Select hyperslab for this dataspace - hsize_t start[] {static_cast(bank_index[mpi::rank])}; - H5Sselect_hyperslab(dspace, H5S_SELECT_SET, start, nullptr, count, nullptr); - - // Set up the property list for parallel writing - hid_t plist = H5Pcreate(H5P_DATASET_XFER); - H5Pset_dxpl_mpio(plist, H5FD_MPIO_COLLECTIVE); - - // Write data to file in parallel - H5Dwrite(dset, banktype, memspace, dspace, plist, source_bank.data()); - - // Free resources - H5Sclose(dspace); - H5Sclose(memspace); - H5Dclose(dset); - H5Pclose(plist); + hid_t membanktype = h5banktype(true); + hid_t filebanktype = h5banktype(false); +#ifdef OPENMC_MPI + write_bank_dataset("source_bank", group_id, source_bank, bank_index, + membanktype, filebanktype, mpi::source_site); #else - - if (mpi::master) { - // Create dataset big enough to hold all source sites - hsize_t dims[] {static_cast(dims_size)}; - hid_t dspace = H5Screate_simple(1, dims, nullptr); - hid_t dset = H5Dcreate(group_id, "source_bank", banktype, dspace, - H5P_DEFAULT, H5P_DEFAULT, H5P_DEFAULT); - - // Save source bank sites since the array is overwritten below -#ifdef OPENMC_MPI - vector temp_source {source_bank.begin(), source_bank.end()}; + write_bank_dataset("source_bank", group_id, source_bank, bank_index, + membanktype, filebanktype); #endif - for (int i = 0; i < mpi::n_procs; ++i) { - // Create memory space - hsize_t count[] {static_cast(bank_index[i + 1] - bank_index[i])}; - hid_t memspace = H5Screate_simple(1, count, nullptr); - -#ifdef OPENMC_MPI - // Receive source sites from other processes - if (i > 0) - MPI_Recv(source_bank.data(), count[0], mpi::source_site, i, i, - mpi::intracomm, MPI_STATUS_IGNORE); -#endif - - // Select hyperslab for this dataspace - dspace = H5Dget_space(dset); - hsize_t start[] {static_cast(bank_index[i])}; - H5Sselect_hyperslab( - dspace, H5S_SELECT_SET, start, nullptr, count, nullptr); - - // Write data to hyperslab - H5Dwrite( - dset, banktype, memspace, dspace, H5P_DEFAULT, source_bank.data()); - - H5Sclose(memspace); - H5Sclose(dspace); - } - - // Close all ids - H5Dclose(dset); - -#ifdef OPENMC_MPI - // Restore state of source bank - std::copy(temp_source.begin(), temp_source.end(), source_bank.begin()); -#endif - } else { -#ifdef OPENMC_MPI - MPI_Send(source_bank.data(), count_size, mpi::source_site, 0, mpi::rank, - mpi::intracomm); -#endif - } -#endif - - H5Tclose(banktype); + H5Tclose(membanktype); + H5Tclose(filebanktype); } // Determine member names of a compound HDF5 datatype @@ -742,7 +677,7 @@ std::string dtype_member_names(hid_t dtype_id) void read_source_bank( hid_t group_id, vector& sites, bool distribute) { - hid_t banktype = h5banktype(); + hid_t banktype = h5banktype(true); // Open the dataset hid_t dset = H5Dopen(group_id, "source_bank", H5P_DEFAULT); @@ -1001,7 +936,8 @@ void write_tally_results_nr(hid_t file_id) // Write reduced tally results to file auto shape = results_copy.shape(); - write_tally_results(tally_group, shape[0], shape[1], results_copy.data()); + write_tally_results( + tally_group, shape[0], shape[1], shape[2], results_copy.data()); close_group(tally_group); } else { diff --git a/src/surface.cpp b/src/surface.cpp index 419859efae..8337943041 100644 --- a/src/surface.cpp +++ b/src/surface.cpp @@ -1464,8 +1464,44 @@ void read_surfaces(pugi::xml_node node) surf1.bc_ = make_unique(i_surf, j_surf); surf2.bc_ = make_unique(i_surf, j_surf); } else { - surf1.bc_ = make_unique(i_surf, j_surf); - surf2.bc_ = make_unique(i_surf, j_surf); + // check that both normals have at least one 0 component + if (std::abs(norm1.x) > FP_PRECISION && + std::abs(norm1.y) > FP_PRECISION && + std::abs(norm1.z) > FP_PRECISION) { + fatal_error(fmt::format( + "The normal ({}) of the periodic surface ({}) does not contain any " + "component with a zero value. A RotationalPeriodicBC requires one " + "component which is zero for both plane normals.", + norm1, i_surf)); + } + if (std::abs(norm2.x) > FP_PRECISION && + std::abs(norm2.y) > FP_PRECISION && + std::abs(norm2.z) > FP_PRECISION) { + fatal_error(fmt::format( + "The normal ({}) of the periodic surface ({}) does not contain any " + "component with a zero value. A RotationalPeriodicBC requires one " + "component which is zero for both plane normals.", + norm2, j_surf)); + } + // find common zero component, which indicates the periodic axis + RotationalPeriodicBC::PeriodicAxis axis; + if (std::abs(norm1.x) <= FP_PRECISION && + std::abs(norm2.x) <= FP_PRECISION) { + axis = RotationalPeriodicBC::PeriodicAxis::x; + } else if (std::abs(norm1.y) <= FP_PRECISION && + std::abs(norm2.y) <= FP_PRECISION) { + axis = RotationalPeriodicBC::PeriodicAxis::y; + } else if (std::abs(norm1.z) <= FP_PRECISION && + std::abs(norm2.z) <= FP_PRECISION) { + axis = RotationalPeriodicBC::PeriodicAxis::z; + } else { + fatal_error(fmt::format( + "There is no component which is 0.0 in both normal vectors. This " + "indicates that the two planes are not periodic about the X, Y, or Z " + "axis, which is not supported.")); + } + surf1.bc_ = make_unique(i_surf, j_surf, axis); + surf2.bc_ = make_unique(i_surf, j_surf, axis); } // If albedo data is present in albedo map, set the boundary albedo. diff --git a/src/tallies/tally.cpp b/src/tallies/tally.cpp index ba18386026..6eef1da9cf 100644 --- a/src/tallies/tally.cpp +++ b/src/tallies/tally.cpp @@ -27,10 +27,12 @@ #include "openmc/tallies/filter_legendre.h" #include "openmc/tallies/filter_mesh.h" #include "openmc/tallies/filter_meshborn.h" +#include "openmc/tallies/filter_meshmaterial.h" #include "openmc/tallies/filter_meshsurface.h" #include "openmc/tallies/filter_particle.h" #include "openmc/tallies/filter_sph_harm.h" #include "openmc/tallies/filter_surface.h" +#include "openmc/tallies/filter_time.h" #include "openmc/xml_interface.h" #include "xtensor/xadapt.hpp" @@ -38,9 +40,10 @@ #include "xtensor/xview.hpp" #include -#include // for max +#include // for max, set_union #include -#include // for size_t +#include // for size_t +#include // for back_inserter #include namespace openmc { @@ -56,11 +59,13 @@ vector> tallies; vector active_tallies; vector active_analog_tallies; vector active_tracklength_tallies; +vector active_timed_tracklength_tallies; vector active_collision_tallies; vector active_meshsurf_tallies; vector active_surface_tallies; vector active_pulse_height_tallies; vector pulse_height_cells; +vector time_grid; } // namespace model namespace simulation { @@ -102,6 +107,9 @@ Tally::Tally(pugi::xml_node node) multiply_density_ = get_node_value_bool(node, "multiply_density"); } + if (check_for_node(node, "higher_moments")) { + higher_moments_ = get_node_value_bool(node, "higher_moments"); + } // ======================================================================= // READ DATA FOR FILTERS @@ -207,7 +215,7 @@ Tally::Tally(pugi::xml_node node) "number of inactive cycles."); } settings::ifp_on = true; - } else { + } else if (settings::run_mode == RunMode::FIXED_SOURCE) { fatal_error( "Iterated Fission Probability can only be used in an eigenvalue " "calculation."); @@ -243,8 +251,8 @@ Tally::Tally(pugi::xml_node node) for (int score : scores_) { switch (score) { case SCORE_PULSE_HEIGHT: - fatal_error( - "For pulse-height tallies, photon transport needs to be activated."); + fatal_error("For pulse-height tallies, photon transport needs to be " + "activated."); break; } } @@ -318,7 +326,8 @@ Tally::Tally(pugi::xml_node node) if (has_energyout && i_nuc == -1) { fatal_error(fmt::format( "Error on tally {}: Cannot use a " - "'nuclide_density' or 'temperature' derivative on a tally with an " + "'nuclide_density' or 'temperature' derivative on a tally with " + "an " "outgoing energy filter and 'total' nuclide rate. Instead, tally " "each nuclide in the material individually.", id_)); @@ -493,9 +502,9 @@ void Tally::add_filter(Filter* filter) void Tally::set_strides() { - // Set the strides. Filters are traversed in reverse so that the last filter - // has the shortest stride in memory and the first filter has the longest - // stride. + // Set the strides. Filters are traversed in reverse so that the last + // filter has the shortest stride in memory and the first filter has the + // longest stride. auto n = filters_.size(); strides_.resize(n, 0); int stride = 1; @@ -551,9 +560,11 @@ void Tally::set_scores(const vector& scores) // Iterate over the given scores. for (auto score_str : scores) { - // Make sure a delayed group filter wasn't used with an incompatible score. + // Make sure a delayed group filter wasn't used with an incompatible + // score. if (delayedgroup_filter_ != C_NONE) { - if (score_str != "delayed-nu-fission" && score_str != "decay-rate") + if (score_str != "delayed-nu-fission" && score_str != "decay-rate" && + score_str != "ifp-beta-numerator") fatal_error("Cannot tally " + score_str + "with a delayedgroup filter"); } @@ -792,7 +803,11 @@ void Tally::init_triggers(pugi::xml_node node) void Tally::init_results() { int n_scores = scores_.size() * nuclides_.size(); - results_ = xt::empty({n_filter_bins_, n_scores, 3}); + if (higher_moments_) { + results_ = xt::empty({n_filter_bins_, n_scores, 5}); + } else { + results_ = xt::empty({n_filter_bins_, n_scores, 3}); + } } void Tally::reset() @@ -817,22 +832,46 @@ void Tally::accumulate() total_source = 1.0; } + // Determine number of particles contributing to tally + double contributing_particles = settings::reduce_tallies + ? settings::n_particles + : simulation::work_per_rank; + // Account for number of source particles in normalization double norm = - total_source / (settings::n_particles * settings::gen_per_batch); + total_source / (contributing_particles * settings::gen_per_batch); if (settings::solver_type == SolverType::RANDOM_RAY) { norm = 1.0; } -// Accumulate each result + // Accumulate each result + if (higher_moments_) { #pragma omp parallel for - for (int i = 0; i < results_.shape()[0]; ++i) { - for (int j = 0; j < results_.shape()[1]; ++j) { - double val = results_(i, j, TallyResult::VALUE) * norm; - results_(i, j, TallyResult::VALUE) = 0.0; - results_(i, j, TallyResult::SUM) += val; - results_(i, j, TallyResult::SUM_SQ) += val * val; + // filter bins (specific cell, energy bins) + for (int i = 0; i < results_.shape()[0]; ++i) { + // score bins (flux, total reaction rate, fission reaction rate, etc.) + for (int j = 0; j < results_.shape()[1]; ++j) { + double val = results_(i, j, TallyResult::VALUE) * norm; + double val2 = val * val; + results_(i, j, TallyResult::VALUE) = 0.0; + results_(i, j, TallyResult::SUM) += val; + results_(i, j, TallyResult::SUM_SQ) += val2; + results_(i, j, TallyResult::SUM_THIRD) += val2 * val; + results_(i, j, TallyResult::SUM_FOURTH) += val2 * val2; + } + } + } else { +#pragma omp parallel for + // filter bins (specific cell, energy bins) + for (int i = 0; i < results_.shape()[0]; ++i) { + // score bins (flux, total reaction rate, fission reaction rate, etc.) + for (int j = 0; j < results_.shape()[1]; ++j) { + double val = results_(i, j, TallyResult::VALUE) * norm; + results_(i, j, TallyResult::VALUE) = 0.0; + results_(i, j, TallyResult::SUM) += val; + results_(i, j, TallyResult::SUM_SQ) += val * val; + } } } } @@ -984,8 +1023,8 @@ void reduce_tally_results() } } - // Note that global tallies are *always* reduced even when no_reduce option is - // on. + // Note that global tallies are *always* reduced even when no_reduce option + // is on. // Get view of global tally values auto& gt = simulation::global_tallies; @@ -1064,21 +1103,59 @@ void accumulate_tallies() } } +double distance_to_time_boundary(double time, double speed) +{ + if (model::time_grid.empty()) { + return INFTY; + } else if (time >= model::time_grid.back()) { + return INFTY; + } else { + double next_time = + *std::upper_bound(model::time_grid.begin(), model::time_grid.end(), time); + return (next_time - time) * speed; + } +} + +//! Add new points to the global time grid +// +//! \param grid Vector of new time points to add +void add_to_time_grid(vector grid) +{ + if (grid.empty()) + return; + + // Create new vector with enough space to hold old and new grid points + vector merged; + merged.reserve(model::time_grid.size() + grid.size()); + + // Merge and remove duplicates + std::set_union(model::time_grid.begin(), model::time_grid.end(), grid.begin(), + grid.end(), std::back_inserter(merged)); + + // Swap in the new grid + model::time_grid.swap(merged); +} + void setup_active_tallies() { model::active_tallies.clear(); model::active_analog_tallies.clear(); model::active_tracklength_tallies.clear(); + model::active_timed_tracklength_tallies.clear(); model::active_collision_tallies.clear(); model::active_meshsurf_tallies.clear(); model::active_surface_tallies.clear(); model::active_pulse_height_tallies.clear(); + model::time_grid.clear(); for (auto i = 0; i < model::tallies.size(); ++i) { const auto& tally {*model::tallies[i]}; if (tally.active_) { model::active_tallies.push_back(i); + bool mesh_present = (tally.get_filter() || + tally.get_filter()); + auto time_filter = tally.get_filter(); switch (tally.type_) { case TallyType::VOLUME: @@ -1087,7 +1164,12 @@ void setup_active_tallies() model::active_analog_tallies.push_back(i); break; case TallyEstimator::TRACKLENGTH: - model::active_tracklength_tallies.push_back(i); + if (time_filter && mesh_present) { + model::active_timed_tracklength_tallies.push_back(i); + add_to_time_grid(time_filter->bins()); + } else { + model::active_tracklength_tallies.push_back(i); + } break; case TallyEstimator::COLLISION: model::active_collision_tallies.push_back(i); @@ -1123,10 +1205,12 @@ void free_memory_tally() model::active_tallies.clear(); model::active_analog_tallies.clear(); model::active_tracklength_tallies.clear(); + model::active_timed_tracklength_tallies.clear(); model::active_collision_tallies.clear(); model::active_meshsurf_tallies.clear(); model::active_surface_tallies.clear(); model::active_pulse_height_tallies.clear(); + model::time_grid.clear(); model::tally_map.clear(); } @@ -1465,8 +1549,8 @@ extern "C" int openmc_tally_get_n_realizations(int32_t index, int32_t* n) return 0; } -//! \brief Returns a pointer to a tally results array along with its shape. This -//! allows a user to obtain in-memory tally results from Python directly. +//! \brief Returns a pointer to a tally results array along with its shape. +//! This allows a user to obtain in-memory tally results from Python directly. extern "C" int openmc_tally_results( int32_t index, double** results, size_t* shape) { diff --git a/src/tallies/tally_scoring.cpp b/src/tallies/tally_scoring.cpp index e73fb90f31..67e851644a 100644 --- a/src/tallies/tally_scoring.cpp +++ b/src/tallies/tally_scoring.cpp @@ -233,7 +233,7 @@ double score_fission_q(const Particle& p, int score_bin, const Tally& tally, double score {0.0}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); const Nuclide& nuc {*data::nuclides[j_nuclide]}; score += get_nuc_fission_q(nuc, p, score_bin) * atom_density * p.neutron_xs(j_nuclide).fission; @@ -696,7 +696,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); score += p.neutron_xs(j_nuclide).fission * data::nuclides[j_nuclide]->nu( E, ReactionProduct::EmissionMode::prompt) * @@ -743,7 +743,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); // Tally each delayed group bin individually for (auto d_bin = 0; d_bin < filt.n_bins(); ++d_bin) { auto d = filt.groups()[d_bin]; @@ -763,7 +763,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); score += p.neutron_xs(j_nuclide).fission * data::nuclides[j_nuclide]->nu( E, ReactionProduct::EmissionMode::delayed) * @@ -824,7 +824,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); const auto& nuc {*data::nuclides[j_nuclide]}; if (nuc.fissionable_) { const auto& rxn {*nuc.fission_rx_[0]}; @@ -849,7 +849,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); const auto& nuc {*data::nuclides[j_nuclide]}; if (nuc.fissionable_) { const auto& rxn {*nuc.fission_rx_[0]}; @@ -893,7 +893,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); const auto& nuc {*data::nuclides[j_nuclide]}; if (nuc.fissionable_) { const auto& rxn {*nuc.fission_rx_[0]}; @@ -924,7 +924,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); if (p.neutron_xs(j_nuclide).elastic == CACHE_INVALID) data::nuclides[j_nuclide]->calculate_elastic_xs(p); score += p.neutron_xs(j_nuclide).elastic * atom_density * flux; @@ -964,6 +964,15 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, if (delayed_groups.size() == settings::ifp_n_generation) { if (delayed_groups[0] > 0) { score = p.wgt_last(); + if (tally.delayedgroup_filter_ != C_NONE) { + auto i_dg_filt = tally.filters()[tally.delayedgroup_filter_]; + const DelayedGroupFilter& filt { + *dynamic_cast( + model::tally_filters[i_dg_filt].get())}; + score_fission_delayed_dg(i_tally, delayed_groups[0] - 1, + score, score_index, p.filter_matches()); + continue; + } } } } @@ -1025,7 +1034,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); score += p.neutron_xs(j_nuclide).reaction[m] * atom_density * flux; } } @@ -1079,7 +1088,7 @@ void score_general_ce_nonanalog(Particle& p, int i_tally, int start_index, const Material& material {*model::materials[p.material()]}; for (auto i = 0; i < material.nuclide_.size(); ++i) { auto j_nuclide = material.nuclide_[i]; - auto atom_density = material.atom_density_(i); + auto atom_density = material.atom_density(i, p.density_mult()); score += get_nuclide_xs(p, j_nuclide, score_bin) * atom_density * flux; } @@ -1624,8 +1633,7 @@ void score_general_mg(Particle& p, int i_tally, int start_index, tally.estimator_ == TallyEstimator::COLLISION) { if (settings::survival_biasing) { // Determine weight that was absorbed - wgt_absorb = p.wgt_last() * p.neutron_xs(p.event_nuclide()).absorption / - p.neutron_xs(p.event_nuclide()).total; + wgt_absorb = p.wgt_last() * p.macro_xs().absorption / p.macro_xs().total; // Then we either are alive and had a scatter (and so g changed), // or are dead and g did not change @@ -2383,7 +2391,8 @@ void score_analog_tally_mg(Particle& p) model::materials[p.material()]->mat_nuclide_index_[i_nuclide]; if (j == C_NONE) continue; - atom_density = model::materials[p.material()]->atom_density_(j); + atom_density = + model::materials[p.material()]->atom_density(j, p.density_mult()); } score_general_mg(p, i_tally, i * tally.scores_.size(), filter_index, @@ -2404,15 +2413,13 @@ void score_analog_tally_mg(Particle& p) match.bins_present_ = false; } -void score_tracklength_tally(Particle& p, double distance) +void score_tracklength_tally_general( + Particle& p, double flux, const vector& tallies) { - // Determine the tracklength estimate of the flux - double flux = p.wgt() * distance; - // Set 'none' value for log union grid index int i_log_union = C_NONE; - for (auto i_tally : model::active_tracklength_tallies) { + for (auto i_tally : tallies) { const Tally& tally {*model::tallies[i_tally]}; // Initialize an iterator over valid filter bin combinations. If there are @@ -2451,8 +2458,9 @@ void score_tracklength_tally(Particle& p, double distance) atom_density = 1.0; } } else { - atom_density = - tally.multiply_density() ? mat->atom_density_(j) : 1.0; + atom_density = tally.multiply_density() + ? mat->atom_density(j, p.density_mult()) + : 1.0; } } } @@ -2481,6 +2489,57 @@ void score_tracklength_tally(Particle& p, double distance) match.bins_present_ = false; } +void score_timed_tracklength_tally(Particle& p, double total_distance) +{ + double speed = p.speed(); + double total_dt = total_distance / speed; + + // save particle last state + auto time_last = p.time_last(); + auto r_last = p.r_last(); + + // move particle back + p.move_distance(-total_distance); + p.time() -= total_dt; + p.lifetime() -= total_dt; + + double distance_traveled = 0.0; + while (distance_traveled < total_distance) { + + double distance = std::min(distance_to_time_boundary(p.time(), speed), + total_distance - distance_traveled); + double dt = distance / speed; + + // Save particle last state for tracklength tallies + p.time_last() = p.time(); + p.r_last() = p.r(); + + // Advance particle in space and time + p.move_distance(distance); + p.time() += dt; + p.lifetime() += dt; + + // Determine the tracklength estimate of the flux + double flux = p.wgt() * distance; + + score_tracklength_tally_general( + p, flux, model::active_timed_tracklength_tallies); + distance_traveled += distance; + } + + p.time_last() = time_last; + p.r_last() = r_last; +} + +void score_tracklength_tally(Particle& p, double distance) +{ + + // Determine the tracklength estimate of the flux + double flux = p.wgt() * distance; + + score_tracklength_tally_general(p, flux, model::active_tracklength_tallies); +} + void score_collision_tally(Particle& p) { // Determine the collision estimate of the flux @@ -2530,8 +2589,9 @@ void score_collision_tally(Particle& p) atom_density = 1.0; } } else { - atom_density = - tally.multiply_density() ? mat->atom_density_(j) : 1.0; + atom_density = tally.multiply_density() + ? mat->atom_density(j, p.density_mult()) + : 1.0; } } diff --git a/src/weight_windows.cpp b/src/weight_windows.cpp index 26762ad18a..9333800bc3 100644 --- a/src/weight_windows.cpp +++ b/src/weight_windows.cpp @@ -26,6 +26,7 @@ #include "openmc/random_ray/flat_source_domain.h" #include "openmc/search.h" #include "openmc/settings.h" +#include "openmc/simulation.h" #include "openmc/tallies/filter_energy.h" #include "openmc/tallies/filter_mesh.h" #include "openmc/tallies/filter_particle.h" @@ -546,8 +547,10 @@ void WeightWindows::update_weights(const Tally* tally, const std::string& value, // build a shape for a view of the tally results, this will always be // dimension 5 (3 filter dimensions, 1 score dimension, 1 results dimension) - std::array shape = { - 1, 1, 1, tally->n_scores(), static_cast(TallyResult::SIZE)}; + // Look for the size of the last dimension of the results array + const auto& results_arr = tally->results(); + const int results_dim = static_cast(results_arr.shape()[2]); + std::array shape = {1, 1, 1, tally->n_scores(), results_dim}; // set the shape for the filters applied on the tally for (int i = 0; i < tally->filters().size(); i++) { @@ -585,7 +588,7 @@ void WeightWindows::update_weights(const Tally* tally, const std::string& value, // get a fully reshaped view of the tally according to tally ordering of // filters - auto tally_values = xt::reshape_view(tally->results(), shape); + auto tally_values = xt::reshape_view(results_arr, shape); // get a that is (particle, energy, mesh, scores, values) auto transposed_view = xt::transpose(tally_values, transpose); @@ -966,11 +969,17 @@ void WeightWindowsGenerator::update() const Tally* tally = model::tallies[tally_idx_].get(); - // if we're beyond the number of max realizations or not at the corrrect - // update interval, skip the update - if (max_realizations_ < tally->n_realizations_ || - tally->n_realizations_ % update_interval_ != 0) + // If in random ray mode, only update on the last batch + if (settings::solver_type == SolverType::RANDOM_RAY) { + if (simulation::current_batch != settings::n_batches) { + return; + } + // If in Monte Carlo mode and beyond the number of max realizations or + // not at the correct update interval, skip the update + } else if (max_realizations_ < tally->n_realizations_ || + tally->n_realizations_ % update_interval_ != 0) { return; + } wws->update_weights(tally, tally_value_, threshold_, ratio_, method_); @@ -1328,6 +1337,10 @@ extern "C" int openmc_weight_windows_import(const char* filename) hid_t weight_windows_group = open_group(ww_file, "weight_windows"); + hid_t mesh_group = open_group(ww_file, "meshes"); + + read_meshes(mesh_group); + std::vector names = group_names(weight_windows_group); for (const auto& name : names) { diff --git a/tests/conftest.py b/tests/conftest.py index fa6718502d..71dd5ebf5d 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -29,12 +29,29 @@ def run_in_tmpdir(tmpdir): yield finally: orig.chdir() - + @pytest.fixture(scope="module") def endf_data(): - return os.environ['OPENMC_ENDF_DATA'] + return os.environ['OPENMC_ENDF_DATA'] @pytest.fixture(scope='session', autouse=True) def resolve_paths(): with openmc.config.patch('resolve_paths', False): yield + + +@pytest.fixture(scope='session', autouse=True) +def disable_depletion_multiprocessing_under_mpi(): + """Fork-based depletion multiprocessing may deadlock if MPI is active.""" + if not regression_config['mpi']: + yield + return + + from openmc.deplete import pool + + original_setting = pool.USE_MULTIPROCESSING + pool.USE_MULTIPROCESSING = False + try: + yield + finally: + pool.USE_MULTIPROCESSING = original_setting diff --git a/tests/cpp_unit_tests/CMakeLists.txt b/tests/cpp_unit_tests/CMakeLists.txt index 8fedc2daa5..5f87db9eac 100644 --- a/tests/cpp_unit_tests/CMakeLists.txt +++ b/tests/cpp_unit_tests/CMakeLists.txt @@ -5,6 +5,7 @@ set(TEST_NAMES test_interpolate test_math test_mcpl_stat_sum + test_mesh # Add additional unit test files here ) diff --git a/tests/cpp_unit_tests/test_mesh.cpp b/tests/cpp_unit_tests/test_mesh.cpp new file mode 100644 index 0000000000..24c4f77373 --- /dev/null +++ b/tests/cpp_unit_tests/test_mesh.cpp @@ -0,0 +1,257 @@ +#include +#include +#include + +#include +#include + +#include "openmc/hdf5_interface.h" +#include "openmc/mesh.h" + +using namespace openmc; + +TEST_CASE("Test mesh hdf5 roundtrip - regular") +{ + // The XML data as a string + std::string xml_string = R"( + + 3 4 5 + -2 -3 -5 + 2 3 5 + + )"; + + // Create a pugixml document object + pugi::xml_document doc; + + // Load the XML from the string + pugi::xml_parse_result result = doc.load_string(xml_string.c_str()); + + pugi::xml_node root = doc.child("mesh"); + + auto mesh = RegularMesh(root); + + hid_t file_id = file_open("mesh.h5", 'w'); + + mesh.to_hdf5(file_id); + + file_close(file_id); + + hid_t file_id2 = file_open("mesh.h5", 'r'); + + hid_t group = open_group(file_id2, "mesh 1"); + + auto mesh2 = RegularMesh(group); + + file_close(file_id2); + + remove("mesh.h5"); + + REQUIRE(mesh2.shape_ == mesh.shape_); + + REQUIRE(mesh2.lower_left() == mesh.lower_left()); + + REQUIRE(mesh2.upper_right() == mesh.upper_right()); +} + +TEST_CASE("Test mesh hdf5 roundtrip - rectilinear") +{ + // The XML data as a string + std::string xml_string = R"( + + 0.0 1.0 5.0 10.0 + -10.0 -5.0 0.0 + -100.0 0.0 100.0 + + )"; + + // Create a pugixml document object + pugi::xml_document doc; + + // Load the XML from the string + pugi::xml_parse_result result = doc.load_string(xml_string.c_str()); + + pugi::xml_node root = doc.child("mesh"); + + auto mesh = RectilinearMesh(root); + + hid_t file_id = file_open("mesh.h5", 'w'); + + mesh.to_hdf5(file_id); + + file_close(file_id); + + hid_t file_id2 = file_open("mesh.h5", 'r'); + + hid_t group = open_group(file_id2, "mesh 1"); + + auto mesh2 = RectilinearMesh(group); + + file_close(file_id2); + + remove("mesh.h5"); + + REQUIRE(mesh2.shape_ == mesh.shape_); + + REQUIRE(mesh2.grid_ == mesh.grid_); +} + +TEST_CASE("Test mesh hdf5 roundtrip - cylindrical") +{ + // The XML data as a string + std::string xml_string = R"( + + 0.1 0.2 0.5 1.0 + 0.0 6.283185307179586 + 0.1 0.2 0.4 0.6 1.0 + 0 0 0 + + )"; + + // Create a pugixml document object + pugi::xml_document doc; + + // Load the XML from the string + pugi::xml_parse_result result = doc.load_string(xml_string.c_str()); + + pugi::xml_node root = doc.child("mesh"); + + auto mesh = CylindricalMesh(root); + + hid_t file_id = file_open("mesh.h5", 'w'); + + mesh.to_hdf5(file_id); + + file_close(file_id); + + hid_t file_id2 = file_open("mesh.h5", 'r'); + + hid_t group = open_group(file_id2, "mesh 1"); + + auto mesh2 = CylindricalMesh(group); + + file_close(file_id2); + + remove("mesh.h5"); + + REQUIRE(mesh2.shape_ == mesh.shape_); + + REQUIRE(mesh2.grid_ == mesh.grid_); +} + +TEST_CASE("Test mesh hdf5 roundtrip - spherical") +{ + // The XML data as a string + std::string xml_string = R"( + + 0.1 0.2 0.5 1.0 + 0.0 3.141592653589793 + 0.0 6.283185307179586 + 0.0 0.0 0.0 + ' + )"; + + // Create a pugixml document object + pugi::xml_document doc; + + // Load the XML from the string + pugi::xml_parse_result result = doc.load_string(xml_string.c_str()); + + pugi::xml_node root = doc.child("mesh"); + + auto mesh = SphericalMesh(root); + + hid_t file_id = file_open("mesh.h5", 'w'); + + mesh.to_hdf5(file_id); + + file_close(file_id); + + hid_t file_id2 = file_open("mesh.h5", 'r'); + + hid_t group = open_group(file_id2, "mesh 1"); + + auto mesh2 = SphericalMesh(group); + + file_close(file_id2); + + remove("mesh.h5"); + + REQUIRE(mesh2.shape_ == mesh.shape_); + + REQUIRE(mesh2.grid_ == mesh.grid_); +} + +TEST_CASE("Test multiple meshes HDF5 roundtrip - spherical") +{ + // The XML data as a string + std::string xml_string = R"( + + + 0.1 0.2 0.5 1.0 + 0.0 3.141592653589793 + 0.0 6.283185307179586 + 0.0 0.0 0.0 + + + 3 4 5 + -2 -3 -5 + 2 3 5 + + + )"; + + // Create a pugixml document object + pugi::xml_document doc; + + // Load the XML from the string + pugi::xml_parse_result result = doc.load_string(xml_string.c_str()); + + pugi::xml_node root = doc.child("meshes"); + + read_meshes(root); + + const auto spherical_mesh_xml = + dynamic_cast(model::meshes[0].get()); + const auto regular_mesh_xml = + dynamic_cast(model::meshes[1].get()); + + hid_t file_id = file_open("meshes.h5", 'w'); + + hid_t root_group = create_group(file_id, "root"); + + open_group(file_id, "root"); + + meshes_to_hdf5(root_group); + + close_group(root_group); + + file_close(file_id); + + hid_t file_id2 = file_open("meshes.h5", 'r'); + + hid_t root_group_read = open_group(file_id2, "root"); + + hid_t mesh_group_read = open_group(root_group_read, "meshes"); + + read_meshes(mesh_group_read); + + // increment mesh IDs to avoid collision during read + for (auto& mesh : model::meshes) { + mesh->set_id(mesh->id() + 10); + } + + const auto spherical_mesh_hdf5 = dynamic_cast( + model::meshes[model::mesh_map[spherical_mesh_xml->id_]].get()); + const auto regular_mesh_hdf5 = dynamic_cast( + model::meshes[model::mesh_map[regular_mesh_xml->id_]].get()); + + remove("meshes.h5"); + + REQUIRE(spherical_mesh_hdf5->shape_ == spherical_mesh_xml->shape_); + REQUIRE(spherical_mesh_hdf5->grid_ == spherical_mesh_xml->grid_); + + REQUIRE(regular_mesh_hdf5->shape_ == regular_mesh_xml->shape_); + REQUIRE(regular_mesh_hdf5->lower_left() == regular_mesh_xml->lower_left()); + REQUIRE(regular_mesh_hdf5->upper_right() == regular_mesh_xml->upper_right()); +} diff --git a/tests/regression_tests/adj_cell_rotation/results_true.dat b/tests/regression_tests/adj_cell_rotation/results_true.dat index b3df12e71f..ddb1546b5b 100644 --- a/tests/regression_tests/adj_cell_rotation/results_true.dat +++ b/tests/regression_tests/adj_cell_rotation/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.403987E-01 1.514158E-03 +4.368327E-01 1.953533E-03 diff --git a/tests/regression_tests/albedo_box/results_true.dat b/tests/regression_tests/albedo_box/results_true.dat index 0f571f2459..dca80abcd8 100644 --- a/tests/regression_tests/albedo_box/results_true.dat +++ b/tests/regression_tests/albedo_box/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.590800E+00 4.251788E-03 +1.593206E+00 2.925742E-03 diff --git a/tests/regression_tests/asymmetric_lattice/results_true.dat b/tests/regression_tests/asymmetric_lattice/results_true.dat index 741327d80b..3d6b610a69 100644 --- a/tests/regression_tests/asymmetric_lattice/results_true.dat +++ b/tests/regression_tests/asymmetric_lattice/results_true.dat @@ -1 +1 @@ -b0ca1fb0436732188b1a199b3250ca9a33782f8fc379b0f7ff9c582e0c794b0a0470df063cafd0b05e802b26f61eaaf9ff5c0a8a672a933246acf49eed3ebf9f \ No newline at end of file +cc76769636be4f681137598cf366e978d7347425a1dfa1b293d17a28381b2b62595fb7f0d2f126dd06972ff9e79089a18dd53aba45fa2b1f316515b91fe6495a \ No newline at end of file diff --git a/tests/regression_tests/cmfd_feed/results_true.dat b/tests/regression_tests/cmfd_feed/results_true.dat index f5f22d9acd..1ef9624d4c 100644 --- a/tests/regression_tests/cmfd_feed/results_true.dat +++ b/tests/regression_tests/cmfd_feed/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.164262E+00 9.207592E-03 +1.181723E+00 9.944883E-03 tally 1: -1.156972E+01 -1.339924E+01 -2.136306E+01 -4.567185E+01 -2.859527E+01 -8.195821E+01 -3.470754E+01 -1.207851E+02 -3.766403E+01 -1.422263E+02 -3.778821E+01 -1.432660E+02 -3.573197E+01 -1.278854E+02 -2.849979E+01 -8.135515E+01 -2.073803E+01 -4.303374E+01 -1.112117E+01 -1.242944E+01 +1.169899E+01 +1.373251E+01 +2.142380E+01 +4.605511E+01 +2.968085E+01 +8.838716E+01 +3.561418E+01 +1.271206E+02 +3.777783E+01 +1.428817E+02 +3.805832E+01 +1.450213E+02 +3.439836E+01 +1.184892E+02 +2.852438E+01 +8.161896E+01 +2.088423E+01 +4.376204E+01 +1.076670E+01 +1.168108E+01 tally 2: -2.388054E+01 -2.875255E+01 -1.667791E+01 -1.403426E+01 -4.224771E+01 -8.942109E+01 -2.993088E+01 -4.490335E+01 -5.689839E+01 -1.625557E+02 -4.043633E+01 -8.212299E+01 -6.764024E+01 -2.297126E+02 -4.807902E+01 -1.161468E+02 -7.314835E+01 -2.684645E+02 -5.203584E+01 -1.359261E+02 -7.375727E+01 -2.733105E+02 -5.252944E+01 -1.386205E+02 -6.909571E+01 -2.397721E+02 -4.922548E+01 -1.217465E+02 -5.685978E+01 -1.621746E+02 -4.051938E+01 -8.237277E+01 -4.185562E+01 -8.784067E+01 -2.983570E+01 -4.467414E+01 -2.238373E+01 -2.520356E+01 -1.566758E+01 -1.234103E+01 +2.321241E+01 +2.702156E+01 +1.620912E+01 +1.317752E+01 +4.197404E+01 +8.845008E+01 +2.982666E+01 +4.469221E+01 +5.810089E+01 +1.695857E+02 +4.134123E+01 +8.588866E+01 +6.982488E+01 +2.447068E+02 +4.966939E+01 +1.238763E+02 +7.428421E+01 +2.767613E+02 +5.287955E+01 +1.403163E+02 +7.447402E+01 +2.785012E+02 +5.324628E+01 +1.423393E+02 +6.895164E+01 +2.381937E+02 +4.916366E+01 +1.211701E+02 +5.679253E+01 +1.617881E+02 +4.043125E+01 +8.204061E+01 +4.218618E+01 +8.933666E+01 +2.978592E+01 +4.456592E+01 +2.196426E+01 +2.435867E+01 +1.525576E+01 +1.175879E+01 tally 3: -1.609520E+01 -1.307542E+01 -1.033429E+00 -5.510889E-02 -2.877073E+01 -4.149542E+01 -1.964219E+00 -1.954692E-01 -3.896816E+01 -7.629752E+01 -2.484053E+00 -3.103733E-01 -4.634285E+01 -1.079367E+02 -2.974750E+00 -4.468223E-01 -5.007964E+01 -1.259202E+02 -3.181802E+00 -5.103621E-01 -5.058915E+01 -1.286193E+02 -3.249442E+00 -5.337712E-01 -4.744464E+01 -1.131026E+02 -3.067644E+00 -4.736335E-01 -3.900632E+01 -7.634433E+01 -2.443552E+00 -3.028060E-01 -2.874166E+01 -4.146375E+01 -1.810421E+00 -1.671667E-01 -1.509222E+01 -1.145579E+01 -1.014919E+00 -5.391053E-02 +1.563788E+01 +1.226528E+01 +1.053289E+00 +5.666942E-02 +2.870755E+01 +4.139654E+01 +1.838017E+00 +1.710528E-01 +3.978616E+01 +7.955764E+01 +2.560657E+00 +3.334449E-01 +4.780385E+01 +1.147770E+02 +3.139243E+00 +4.967628E-01 +5.106650E+01 +1.308704E+02 +3.170056E+00 +5.078920E-01 +5.123992E+01 +1.318586E+02 +3.211706E+00 +5.205979E-01 +4.729862E+01 +1.121695E+02 +3.068662E+00 +4.749488E-01 +3.898816E+01 +7.630564E+01 +2.516911E+00 +3.199696E-01 +2.865357E+01 +4.125742E+01 +1.852314E+00 +1.741116E-01 +1.467340E+01 +1.088460E+01 +9.268633E-01 +4.450662E-02 tally 4: -3.148231E+00 -4.974555E-01 +3.029754E+00 +4.613561E-01 0.000000E+00 0.000000E+00 -2.805439E+00 -3.982239E-01 -5.574031E+00 -1.561105E+00 +2.832501E+00 +4.049252E-01 +5.517243E+00 +1.527794E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.574031E+00 -1.561105E+00 -2.805439E+00 -3.982239E-01 -5.171038E+00 -1.344877E+00 -7.372031E+00 -2.725420E+00 +5.517243E+00 +1.527794E+00 +2.832501E+00 +4.049252E-01 +5.117178E+00 +1.316972E+00 +7.333303E+00 +2.701677E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.372031E+00 -2.725420E+00 -5.171038E+00 -1.344877E+00 -6.946847E+00 -2.424850E+00 -8.496610E+00 -3.627542E+00 +7.333303E+00 +2.701677E+00 +5.117178E+00 +1.316972E+00 +7.248464E+00 +2.641591E+00 +8.817788E+00 +3.905530E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.496610E+00 -3.627542E+00 -6.946847E+00 -2.424850E+00 -8.479501E+00 -3.607280E+00 -9.261869E+00 -4.305912E+00 +8.817788E+00 +3.905530E+00 +7.248464E+00 +2.641591E+00 +8.646465E+00 +3.749847E+00 +9.460948E+00 +4.495388E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.261869E+00 -4.305912E+00 -8.479501E+00 -3.607280E+00 -9.232858E+00 -4.278432E+00 -9.306384E+00 -4.348594E+00 +9.460948E+00 +4.495388E+00 +8.646465E+00 +3.749847E+00 +9.379341E+00 +4.415049E+00 +9.278640E+00 +4.320720E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.306384E+00 -4.348594E+00 -9.232858E+00 -4.278432E+00 -9.299764E+00 -4.347828E+00 -8.511976E+00 -3.639893E+00 +9.278640E+00 +4.320720E+00 +9.379341E+00 +4.415049E+00 +9.465746E+00 +4.498591E+00 +8.656146E+00 +3.760545E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.511976E+00 -3.639893E+00 -9.299764E+00 -4.347828E+00 -8.726086E+00 -3.819567E+00 -7.147277E+00 -2.562747E+00 +8.656146E+00 +3.760545E+00 +9.465746E+00 +4.498591E+00 +8.589782E+00 +3.700308E+00 +6.996002E+00 +2.456935E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.147277E+00 -2.562747E+00 -8.726086E+00 -3.819567E+00 -7.218790E+00 -2.612243E+00 -5.018287E+00 -1.263077E+00 +6.996002E+00 +2.456935E+00 +8.589782E+00 +3.700308E+00 +7.352050E+00 +2.714808E+00 +5.105164E+00 +1.312559E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.018287E+00 -1.263077E+00 -7.218790E+00 -2.612243E+00 -5.443494E+00 -1.487018E+00 -2.732334E+00 -3.773047E-01 +5.105164E+00 +1.312559E+00 +7.352050E+00 +2.714808E+00 +5.442756E+00 +1.486776E+00 +2.697305E+00 +3.675580E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.732334E+00 -3.773047E-01 -5.443494E+00 -1.487018E+00 -3.044773E+00 -4.655756E-01 +2.697305E+00 +3.675580E-01 +5.442756E+00 +1.486776E+00 +3.017025E+00 +4.571443E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,144 +345,144 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -1.609029E+01 -1.306718E+01 -2.230601E+00 -2.559496E-01 -2.876780E+01 -4.148686E+01 -3.835952E+00 -7.456562E-01 -3.895738E+01 -7.625344E+01 -4.841024E+00 -1.197335E+00 -4.633595E+01 -1.079043E+02 -6.236821E+00 -1.963311E+00 -5.007472E+01 -1.258967E+02 -6.749745E+00 -2.297130E+00 -5.058336E+01 -1.285894E+02 -6.727612E+00 -2.315656E+00 -4.743869E+01 -1.130735E+02 -6.338193E+00 -2.042159E+00 -3.899838E+01 -7.631289E+01 -5.187573E+00 -1.359733E+00 -2.873434E+01 -4.144233E+01 -3.815610E+00 -7.367619E-01 -1.509020E+01 -1.145268E+01 -2.125767E+00 -2.341894E-01 +1.563588E+01 +1.226217E+01 +2.209027E+00 +2.507131E-01 +2.870034E+01 +4.137550E+01 +3.726620E+00 +7.021948E-01 +3.977762E+01 +7.952285E+01 +5.304975E+00 +1.427333E+00 +4.779747E+01 +1.147456E+02 +6.528302E+00 +2.151715E+00 +5.105366E+01 +1.308037E+02 +6.986782E+00 +2.467487E+00 +5.123380E+01 +1.318264E+02 +6.845633E+00 +2.383542E+00 +4.729296E+01 +1.121433E+02 +6.252695E+00 +1.977351E+00 +3.898236E+01 +7.628315E+01 +5.461495E+00 +1.528579E+00 +2.864576E+01 +4.123538E+01 +3.857301E+00 +7.581323E-01 +1.467047E+01 +1.088031E+01 +2.277024E+00 +2.679801E-01 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.129918E+00 -1.143848E+00 -1.147976E+00 -1.151534E+00 -1.152378E+00 -1.148219E+00 -1.150402E+00 -1.154647E+00 -1.156159E+00 -1.160048E+00 -1.167441E+00 -1.168163E+00 -1.168629E+00 -1.164120E+00 -1.165051E+00 -1.169177E+00 +1.169107E+00 +1.175079E+00 +1.173912E+00 +1.175368E+00 +1.174026E+00 +1.181745E+00 +1.182261E+00 +1.183559E+00 +1.178691E+00 +1.179222E+00 +1.179017E+00 +1.172979E+00 +1.175043E+00 +1.173458E+00 +1.174152E+00 +1.171451E+00 cmfd entropy -3.224769E+00 -3.225945E+00 -3.227421E+00 -3.226174E+00 -3.224429E+00 -3.227049E+00 -3.230710E+00 -3.230315E+00 -3.226825E+00 -3.226655E+00 -3.226588E+00 -3.224155E+00 -3.223246E+00 -3.222640E+00 -3.223920E+00 -3.222838E+00 +3.207640E+00 +3.210547E+00 +3.212218E+00 +3.209573E+00 +3.211619E+00 +3.212126E+00 +3.213163E+00 +3.214288E+00 +3.215737E+00 +3.213677E+00 +3.214925E+00 +3.215612E+00 +3.216708E+00 +3.221454E+00 +3.219048E+00 +3.218387E+00 cmfd balance -3.90454E-03 -4.08089E-03 -3.46511E-03 -4.09535E-03 -2.62009E-03 -2.23559E-03 -2.54033E-03 -2.12799E-03 -2.25864E-03 -1.85766E-03 -1.49916E-03 -1.63471E-03 -1.48377E-03 -1.59800E-03 -1.37354E-03 -1.32853E-03 +4.88208E-03 +4.75139E-03 +3.15783E-03 +3.67091E-03 +2.99797E-03 +2.91060E-03 +2.06576E-03 +1.83482E-03 +1.56292E-03 +1.58659E-03 +2.32986E-03 +1.47376E-03 +1.46673E-03 +1.22627E-03 +1.31963E-03 +1.26456E-03 cmfd dominance ratio -5.539E-01 -5.537E-01 -5.536E-01 -5.515E-01 -5.512E-01 -5.514E-01 -5.518E-01 -5.507E-01 -5.500E-01 -5.497E-01 -5.477E-01 -5.461E-01 -5.444E-01 -5.445E-01 -5.454E-01 +5.467E-01 +5.453E-01 +5.458E-01 +5.436E-01 +5.442E-01 +5.406E-01 +5.401E-01 +5.413E-01 +4.995E-01 +5.396E-01 +5.409E-01 +5.414E-01 +5.423E-01 +5.456E-01 +5.442E-01 5.441E-01 cmfd openmc source comparison -9.875240E-03 -1.106163E-02 -9.847628E-03 -6.065921E-03 -5.772039E-03 -4.615656E-03 -4.244331E-03 -3.694299E-03 -3.545814E-03 -3.213063E-03 -3.467537E-03 -3.383489E-03 -3.697591E-03 -3.937358E-03 -3.369124E-03 -3.190359E-03 +9.587418E-03 +8.150978E-03 +6.677661E-03 +6.334727E-03 +5.153692E-03 +5.082964E-03 +4.633153E-03 +4.037383E-03 +3.528742E-03 +4.559089E-03 +3.517370E-03 +3.306117E-03 +2.913809E-03 +1.906045E-03 +1.932794E-03 +1.711341E-03 cmfd source -4.360494E-02 -8.397599E-02 -1.074181E-01 -1.294531E-01 -1.385611E-01 -1.407934E-01 -1.325191E-01 -1.044311E-01 -7.660359E-02 -4.263941E-02 +4.496492E-02 +7.869674E-02 +1.100280E-01 +1.354045E-01 +1.363339E-01 +1.380533E-01 +1.314512E-01 +1.077480E-01 +7.847306E-02 +3.884630E-02 diff --git a/tests/regression_tests/cmfd_feed_2g/results_true.dat b/tests/regression_tests/cmfd_feed_2g/results_true.dat index 2b61d9f4e8..e66eae13c4 100644 --- a/tests/regression_tests/cmfd_feed_2g/results_true.dat +++ b/tests/regression_tests/cmfd_feed_2g/results_true.dat @@ -1,112 +1,112 @@ k-combined: -1.035567E+00 9.463160E-03 +1.027434E+00 6.509170E-03 tally 1: -1.146535E+02 -1.315267E+03 -1.157458E+02 -1.340166E+03 -1.140491E+02 -1.301364E+03 -1.146589E+02 -1.315433E+03 +1.162758E+02 +1.352562E+03 +1.138125E+02 +1.295815E+03 +1.143712E+02 +1.308316E+03 +1.150293E+02 +1.323834E+03 tally 2: -4.319968E+01 -9.360083E+01 -6.373035E+01 -2.038056E+02 -1.889646E+02 -1.812892E+03 -1.024866E+02 -5.254528E+02 -4.323262E+01 -9.360200E+01 -6.363111E+01 -2.028178E+02 -1.849746E+02 -1.711533E+03 -1.034532E+02 -5.352768E+02 -4.296541E+01 -9.249656E+01 -6.346919E+01 -2.018659E+02 -1.888697E+02 -1.812037E+03 -1.025707E+02 -5.262261E+02 -4.691085E+01 -1.269707E+02 -6.299377E+01 -1.990497E+02 -1.853864E+02 -1.719984E+03 -1.023015E+02 -5.235858E+02 +4.284580E+01 +9.207089E+01 +6.335165E+01 +2.014931E+02 +1.894187E+02 +1.818190E+03 +1.033212E+02 +5.340768E+02 +4.282771E+01 +9.186295E+01 +6.295029E+01 +1.983895E+02 +1.834276E+02 +1.684375E+03 +1.022482E+02 +5.228403E+02 +4.330690E+01 +9.402038E+01 +6.395965E+01 +2.053163E+02 +1.851113E+02 +1.714198E+03 +1.030809E+02 +5.314535E+02 +4.337097E+01 +9.426435E+01 +6.417590E+01 +2.063443E+02 +1.846817E+02 +1.706518E+03 +1.027233E+02 +5.279582E+02 tally 3: -6.034963E+01 -1.827718E+02 +5.992726E+01 +1.803120E+02 0.000000E+00 0.000000E+00 -1.865665E-02 -4.244195E-05 -4.170941E+00 -8.769372E-01 -3.453368E+00 -5.989168E-01 +2.172646E-02 +4.414237E-05 +4.181401E+00 +8.912796E-01 +3.536506E+00 +6.287425E-01 0.000000E+00 0.000000E+00 -9.743205E+01 -4.749420E+02 -8.570316E-01 -3.807993E-02 -6.005903E+01 -1.807233E+02 +9.824432E+01 +4.828691E+02 +9.116848E-01 +4.231247E-02 +5.955090E+01 +1.775522E+02 0.000000E+00 0.000000E+00 -1.885450E-02 -3.653402E-05 -4.323863E+00 -9.447512E-01 -3.465465E+00 -6.022861E-01 +1.893222E-02 +3.288000E-05 +4.048183E+00 +8.291130E-01 +3.384041E+00 +5.742363E-01 0.000000E+00 0.000000E+00 -9.843481E+01 -4.846158E+02 -9.048150E-01 -4.205551E-02 -5.996660E+01 -1.802150E+02 +9.734253E+01 +4.738861E+02 +9.157632E-01 +4.329280E-02 +6.045835E+01 +1.835255E+02 0.000000E+00 0.000000E+00 -1.221444E-02 -2.263445E-05 -4.301287E+00 -9.309882E-01 -3.456076E+00 -5.992144E-01 +1.501842E-02 +1.896931E-05 +4.289989E+00 +9.251538E-01 +3.481357E+00 +6.071667E-01 0.000000E+00 0.000000E+00 -9.761231E+01 -4.765834E+02 -8.434644E-01 -3.728180E-02 -5.961891E+01 -1.783106E+02 +9.799829E+01 +4.803591E+02 +8.899390E-01 +4.078750E-02 +6.064531E+01 +1.842746E+02 0.000000E+00 0.000000E+00 -1.500709E-02 -3.541280E-05 -4.155669E+00 -8.713442E-01 -3.455342E+00 -6.006426E-01 +1.495496E-02 +3.082640E-05 +4.321537E+00 +9.371611E-01 +3.453767E+00 +5.983727E-01 0.000000E+00 0.000000E+00 -9.726798E+01 -4.733393E+02 -9.202611E-01 -4.390503E-02 +9.771776E+01 +4.777781E+02 +8.975444E-01 +4.157471E-02 tally 4: 0.000000E+00 0.000000E+00 @@ -116,14 +116,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.943264E+00 -4.008855E+00 -3.661063E+01 -6.704808E+01 -8.945553E+00 -4.011707E+00 -3.696832E+01 -6.835286E+01 +8.840487E+00 +3.915792E+00 +3.700362E+01 +6.851588E+01 +8.756789E+00 +3.844443E+00 +3.672366E+01 +6.747174E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -132,14 +132,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.844569E+00 -3.924591E+00 -3.666726E+01 -6.726522E+01 -8.769637E+00 -3.855006E+00 -3.654115E+01 -6.680777E+01 +8.860460E+00 +3.940908E+00 +3.704658E+01 +6.864069E+01 +8.832046E+00 +3.916611E+00 +3.736239E+01 +6.982147E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -156,14 +156,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.945553E+00 -4.011707E+00 -3.696832E+01 -6.835286E+01 -8.943264E+00 -4.008855E+00 -3.661063E+01 -6.704808E+01 +8.756789E+00 +3.844443E+00 +3.672366E+01 +6.747174E+01 +8.840487E+00 +3.915792E+00 +3.700362E+01 +6.851588E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -180,14 +180,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.648474E+00 -3.752219E+00 -3.689442E+01 -6.808997E+01 -8.757378E+00 -3.850408E+00 -3.716920E+01 -6.909715E+01 +8.892576E+00 +3.964978E+00 +3.703525E+01 +6.860645E+01 +8.824229E+00 +3.906925E+00 +3.685909E+01 +6.796123E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -212,22 +212,22 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.783669E+00 -3.870748E+00 -3.687358E+01 -6.802581E+01 -8.755250E+00 -3.846298E+00 -3.660278E+01 -6.704349E+01 -8.769637E+00 -3.855006E+00 -3.654115E+01 -6.680777E+01 -8.844569E+00 -3.924591E+00 -3.666726E+01 -6.726522E+01 +9.050876E+00 +4.111409E+00 +3.656082E+01 +6.687580E+01 +9.042402E+00 +4.105842E+00 +3.687247E+01 +6.801050E+01 +8.832046E+00 +3.916611E+00 +3.736239E+01 +6.982147E+01 +8.860460E+00 +3.940908E+00 +3.704658E+01 +6.864069E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -252,14 +252,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.755250E+00 -3.846298E+00 -3.660278E+01 -6.704349E+01 -8.783669E+00 -3.870748E+00 -3.687358E+01 -6.802581E+01 +9.042402E+00 +4.105842E+00 +3.687247E+01 +6.801050E+01 +9.050876E+00 +4.111409E+00 +3.656082E+01 +6.687580E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -268,14 +268,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.757378E+00 -3.850408E+00 -3.716920E+01 -6.909715E+01 -8.648474E+00 -3.752219E+00 -3.689442E+01 -6.808997E+01 +8.824229E+00 +3.906925E+00 +3.685909E+01 +6.796123E+01 +8.892576E+00 +3.964978E+00 +3.703525E+01 +6.860645E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -301,133 +301,133 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -6.036829E+01 -1.828885E+02 -1.008777E+02 -5.091033E+02 -1.353211E+01 -9.188155E+00 -4.618716E+01 -1.067410E+02 -6.007789E+01 -1.808371E+02 -1.018892E+02 -5.192269E+02 -1.357961E+01 -9.247052E+00 -4.618560E+01 -1.067058E+02 -5.997882E+01 -1.802895E+02 -1.010597E+02 -5.108478E+02 -1.374955E+01 -9.502494E+00 -4.619500E+01 -1.067547E+02 -5.963392E+01 -1.783999E+02 -1.007134E+02 -5.074700E+02 -1.319398E+01 -8.734106E+00 -4.586295E+01 -1.052870E+02 +5.994898E+01 +1.804403E+02 +1.017670E+02 +5.181130E+02 +1.354160E+01 +9.220935E+00 +4.648971E+01 +1.081636E+02 +5.956983E+01 +1.776668E+02 +1.007226E+02 +5.073592E+02 +1.347883E+01 +9.120344E+00 +4.609907E+01 +1.063127E+02 +6.047337E+01 +1.836168E+02 +1.014777E+02 +5.150557E+02 +1.390508E+01 +9.722899E+00 +4.629251E+01 +1.072027E+02 +6.066027E+01 +1.843661E+02 +1.011648E+02 +5.120629E+02 +1.365982E+01 +9.372236E+00 +4.602994E+01 +1.060579E+02 cmfd indices 2.000000E+00 2.000000E+00 1.000000E+00 2.000000E+00 k cmfd -1.018115E+00 -1.022665E+00 -1.020323E+00 -1.020653E+00 -1.021036E+00 -1.020623E+00 -1.021482E+00 -1.025450E+00 -1.027292E+00 -1.028065E+00 -1.027065E+00 -1.024275E+00 -1.025309E+00 -1.026039E+00 -1.026700E+00 -1.023865E+00 +1.013488E+00 +1.024396E+00 +1.015533E+00 +1.009319E+00 +1.012726E+00 +1.014831E+00 +1.021757E+00 +1.022002E+00 +1.023619E+00 +1.020953E+00 +1.023910E+00 +1.027657E+00 +1.024501E+00 +1.023838E+00 +1.025464E+00 +1.022802E+00 cmfd entropy -1.998965E+00 -1.999214E+00 -1.999348E+00 -1.999366E+00 -1.999564E+00 -1.999453E+00 -1.999533E+00 -1.999630E+00 -1.999739E+00 -1.999588E+00 -1.999581E+00 -1.999719E+00 -1.999773E+00 -1.999764E+00 -1.999821E+00 -1.999843E+00 +1.998974E+00 +1.998742E+00 +1.999128E+00 +1.998952E+00 +1.998951E+00 +1.999439E+00 +1.999626E+00 +1.999826E+00 +1.999513E+00 +1.999451E+00 +1.999514E+00 +1.999590E+00 +1.999563E+00 +1.999604E+00 +1.999742E+00 +1.999736E+00 cmfd balance -5.73174E-04 -7.55398E-04 -1.46671E-03 -6.39625E-04 -8.19008E-04 -1.93449E-03 -1.15900E-03 -1.01690E-03 -5.62788E-04 -6.90450E-04 -6.01060E-04 -5.73418E-04 -4.37190E-04 -4.82966E-04 -4.09700E-04 -3.45096E-04 +9.79896E-04 +4.24873E-04 +8.05696E-04 +1.92071E-03 +3.70731E-04 +2.81424E-04 +8.28991E-04 +6.12217E-04 +5.29185E-04 +4.97799E-04 +3.09154E-04 +1.73703E-04 +2.56689E-04 +2.64938E-04 +1.96305E-04 +1.82702E-04 cmfd dominance ratio -6.264E-03 -6.142E-03 -5.987E-03 -6.082E-03 -5.895E-03 -5.939E-03 -5.910E-03 -5.948E-03 -6.013E-03 -6.017E-03 -6.024E-03 -6.008E-03 -5.976E-03 -5.987E-03 -5.967E-03 -5.929E-03 +6.304E-03 +6.246E-03 +6.159E-03 +6.249E-03 +6.101E-03 +6.155E-03 +6.010E-03 +6.177E-03 +6.349E-03 +6.241E-03 +6.244E-03 +6.249E-03 +6.270E-03 +6.272E-03 +6.278E-03 +6.290E-03 cmfd openmc source comparison -4.832872E-05 -6.552342E-05 -7.516800E-05 -7.916087E-05 -9.022260E-05 -8.574478E-05 -7.891622E-05 -7.281636E-05 -7.750571E-05 -6.565408E-05 -6.078665E-05 -5.834343E-05 -4.758176E-05 -5.723990E-05 -4.994116E-05 -4.116808E-05 +4.046094E-05 +5.979431E-05 +3.836521E-05 +4.577591E-05 +5.012911E-05 +2.114677E-05 +2.074571E-05 +3.042280E-05 +2.408163E-05 +2.434542E-05 +1.190699E-05 +9.499301E-06 +2.354221E-05 +2.937924E-05 +1.889875E-05 +1.913866E-05 cmfd source -2.455663E-01 -2.553511E-01 -2.512257E-01 -2.478570E-01 +2.489706E-01 +2.426801E-01 +2.532142E-01 +2.551351E-01 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/tests/regression_tests/cmfd_feed_expanding_window/results_true.dat b/tests/regression_tests/cmfd_feed_expanding_window/results_true.dat index 8fd8cdbb84..b39f82f96e 100644 --- a/tests/regression_tests/cmfd_feed_expanding_window/results_true.dat +++ b/tests/regression_tests/cmfd_feed_expanding_window/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.167865E+00 7.492213E-03 +1.170835E+00 5.423480E-03 tally 1: -1.146860E+01 -1.318884E+01 -2.161527E+01 -4.685283E+01 -2.951158E+01 -8.733566E+01 -3.521610E+01 -1.242821E+02 -3.774236E+01 -1.426501E+02 -3.727918E+01 -1.391158E+02 -3.377176E+01 -1.143839E+02 -2.904497E+01 -8.452907E+01 -2.090871E+01 -4.384549E+01 -1.078642E+01 -1.168086E+01 +1.205100E+01 +1.456707E+01 +2.183882E+01 +4.781179E+01 +2.844010E+01 +8.102358E+01 +3.356334E+01 +1.130832E+02 +3.660829E+01 +1.344973E+02 +3.697740E+01 +1.371500E+02 +3.400119E+01 +1.160196E+02 +2.839868E+01 +8.083199E+01 +2.140398E+01 +4.615447E+01 +1.118179E+01 +1.262942E+01 tally 2: -1.136810E+00 -1.292338E+00 -7.987303E-01 -6.379700E-01 -2.266938E+00 -5.139009E+00 -1.613483E+00 -2.603328E+00 -3.046349E+00 -9.280239E+00 -2.182459E+00 -4.763126E+00 -3.568068E+00 -1.273111E+01 -2.532456E+00 -6.413333E+00 -3.989504E+00 -1.591614E+01 -2.848301E+00 -8.112818E+00 -3.853133E+00 -1.484663E+01 -2.718493E+00 -7.390202E+00 -3.478138E+00 -1.209745E+01 -2.467281E+00 -6.087476E+00 -2.952220E+00 -8.715605E+00 -2.103261E+00 -4.423706E+00 -1.917459E+00 -3.676649E+00 -1.378369E+00 -1.899902E+00 -1.048240E+00 -1.098807E+00 -7.511947E-01 -5.642934E-01 +1.218245E+00 +1.484121E+00 +8.387442E-01 +7.034918E-01 +2.142134E+00 +4.588738E+00 +1.526727E+00 +2.330895E+00 +2.736157E+00 +7.486556E+00 +1.973921E+00 +3.896363E+00 +3.606244E+00 +1.300500E+01 +2.537580E+00 +6.439313E+00 +3.668958E+00 +1.346126E+01 +2.599095E+00 +6.755294E+00 +3.647982E+00 +1.330777E+01 +2.539750E+00 +6.450332E+00 +3.118921E+00 +9.727669E+00 +2.186447E+00 +4.780549E+00 +2.881110E+00 +8.300795E+00 +2.042635E+00 +4.172360E+00 +2.045602E+00 +4.184486E+00 +1.458384E+00 +2.126884E+00 +1.022124E+00 +1.044738E+00 +7.112678E-01 +5.059018E-01 tally 3: -7.701233E-01 -5.930898E-01 -4.481585E-02 -2.008461E-03 -1.547307E+00 -2.394158E+00 -1.226539E-01 -1.504398E-02 -2.106373E+00 -4.436806E+00 -1.450618E-01 -2.104294E-02 -2.437654E+00 -5.942157E+00 -1.521380E-01 -2.314598E-02 -2.754639E+00 -7.588038E+00 -1.745460E-01 -3.046629E-02 -2.623852E+00 -6.884601E+00 -1.851602E-01 -3.428432E-02 -2.376886E+00 -5.649588E+00 -1.615729E-01 -2.610582E-02 -2.021856E+00 -4.087900E+00 -1.533174E-01 -2.350622E-02 -1.333190E+00 -1.777397E+00 -7.076188E-02 -5.007243E-03 -7.258527E-01 -5.268622E-01 -3.656030E-02 -1.336656E-03 +8.048428E-01 +6.477720E-01 +6.603741E-02 +4.360940E-03 +1.466886E+00 +2.151755E+00 +1.002354E-01 +1.004713E-02 +1.909238E+00 +3.645189E+00 +1.202824E-01 +1.446786E-02 +2.443130E+00 +5.968886E+00 +1.627351E-01 +2.648270E-02 +2.492602E+00 +6.213064E+00 +1.910368E-01 +3.649506E-02 +2.437262E+00 +5.940245E+00 +1.568389E-01 +2.459843E-02 +2.104091E+00 +4.427200E+00 +1.450465E-01 +2.103848E-02 +1.965900E+00 +3.864762E+00 +1.367918E-01 +1.871199E-02 +1.402871E+00 +1.968047E+00 +1.061316E-01 +1.126391E-02 +6.832689E-01 +4.668565E-01 +4.599034E-02 +2.115112E-03 tally 4: -1.667432E-01 -2.780328E-02 +1.497312E-01 +2.241943E-02 0.000000E+00 0.000000E+00 -1.292567E-01 -1.670730E-02 -2.813370E-01 -7.915052E-02 +1.535839E-01 +2.358801E-02 +2.882052E-01 +8.306225E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.813370E-01 -7.915052E-02 -1.292567E-01 -1.670730E-02 -2.670549E-01 -7.131835E-02 -4.055324E-01 -1.644566E-01 +2.882052E-01 +8.306225E-02 +1.535839E-01 +2.358801E-02 +2.526805E-01 +6.384743E-02 +3.616220E-01 +1.307705E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.055324E-01 -1.644566E-01 -2.670549E-01 -7.131835E-02 -3.848125E-01 -1.480807E-01 -4.809430E-01 -2.313062E-01 +3.616220E-01 +1.307705E-01 +2.526805E-01 +6.384743E-02 +3.594306E-01 +1.291904E-01 +4.229730E-01 +1.789062E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.809430E-01 -2.313062E-01 -3.848125E-01 -1.480807E-01 -4.543918E-01 -2.064719E-01 -5.106133E-01 -2.607260E-01 +4.229730E-01 +1.789062E-01 +3.594306E-01 +1.291904E-01 +3.973299E-01 +1.578711E-01 +4.255879E-01 +1.811250E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.106133E-01 -2.607260E-01 -4.543918E-01 -2.064719E-01 -4.543120E-01 -2.063994E-01 -4.626328E-01 -2.140291E-01 +4.255879E-01 +1.811250E-01 +3.973299E-01 +1.578711E-01 +4.633933E-01 +2.147333E-01 +4.672837E-01 +2.183540E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.626328E-01 -2.140291E-01 -4.543120E-01 -2.063994E-01 -4.827759E-01 -2.330726E-01 -4.442622E-01 -1.973689E-01 +4.672837E-01 +2.183540E-01 +4.633933E-01 +2.147333E-01 +4.251073E-01 +1.807162E-01 +3.842922E-01 +1.476805E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.442622E-01 -1.973689E-01 -4.827759E-01 -2.330726E-01 -4.630420E-01 -2.144079E-01 -3.886524E-01 -1.510507E-01 +3.842922E-01 +1.476805E-01 +4.251073E-01 +1.807162E-01 +4.045096E-01 +1.636280E-01 +3.192860E-01 +1.019436E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.886524E-01 -1.510507E-01 -4.630420E-01 -2.144079E-01 -3.535870E-01 -1.250237E-01 -2.530312E-01 -6.402478E-02 +3.192860E-01 +1.019436E-01 +4.045096E-01 +1.636280E-01 +3.738326E-01 +1.397508E-01 +2.598153E-01 +6.750398E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.530312E-01 -6.402478E-02 -3.535870E-01 -1.250237E-01 -2.465524E-01 -6.078808E-02 -1.197152E-01 -1.433173E-02 +2.598153E-01 +6.750398E-02 +3.738326E-01 +1.397508E-01 +2.453191E-01 +6.018146E-02 +1.098964E-01 +1.207721E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -1.197152E-01 -1.433173E-02 -2.465524E-01 -6.078808E-02 -1.369631E-01 -1.875888E-02 +1.098964E-01 +1.207721E-02 +2.453191E-01 +6.018146E-02 +1.458094E-01 +2.126039E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,119 +345,119 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -7.701233E-01 -5.930898E-01 -1.386250E-01 -1.921688E-02 -1.547307E+00 -2.394158E+00 -2.630277E-01 -6.918357E-02 -2.106373E+00 -4.436806E+00 -2.807880E-01 -7.884187E-02 -2.435849E+00 -5.933361E+00 -3.322060E-01 -1.103608E-01 -2.753634E+00 -7.582501E+00 -3.825922E-01 -1.463768E-01 -2.623852E+00 -6.884601E+00 -3.888710E-01 -1.512206E-01 -2.376886E+00 -5.649588E+00 -3.196217E-01 -1.021581E-01 -2.021856E+00 -4.087900E+00 -2.897881E-01 -8.397715E-02 -1.333190E+00 -1.777397E+00 -1.627110E-01 -2.647486E-02 -7.258527E-01 -5.268622E-01 -9.348666E-02 -8.739755E-03 +8.048428E-01 +6.477720E-01 +1.018934E-01 +1.038226E-02 +1.466886E+00 +2.151755E+00 +1.414681E-01 +2.001322E-02 +1.909238E+00 +3.645189E+00 +2.450211E-01 +6.003535E-02 +2.443130E+00 +5.968886E+00 +3.360056E-01 +1.128997E-01 +2.492602E+00 +6.213064E+00 +3.266277E-01 +1.066856E-01 +2.437262E+00 +5.940245E+00 +2.878100E-01 +8.283461E-02 +2.104091E+00 +4.427200E+00 +3.440457E-01 +1.183675E-01 +1.965900E+00 +3.864762E+00 +2.880615E-01 +8.297945E-02 +1.401955E+00 +1.965478E+00 +1.646479E-01 +2.710892E-02 +6.832689E-01 +4.668565E-01 +1.147413E-01 +1.316557E-02 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.149077E+00 -1.156751E+00 -1.158648E+00 -1.159506E+00 -1.156567E+00 -1.160259E+00 -1.150345E+00 -1.149846E+00 -1.151606E+00 -1.164544E+00 -1.174648E+00 +1.181376E+00 +1.176656E+00 +1.161939E+00 +1.163552E+00 +1.163035E+00 +1.170382E+00 +1.160597E+00 +1.154301E+00 +1.159007E+00 +1.148290E+00 +1.157088E+00 cmfd entropy -3.216173E+00 -3.228717E+00 -3.220402E+00 -3.214352E+00 -3.215636E+00 -3.213599E+00 -3.212854E+00 -3.213131E+00 -3.213196E+00 -3.205474E+00 -3.202869E+00 +3.246419E+00 +3.246511E+00 +3.252247E+00 +3.240919E+00 +3.237600E+00 +3.233990E+00 +3.234226E+00 +3.229356E+00 +3.224272E+00 +3.225381E+00 +3.226778E+00 cmfd balance -3.08825E-03 -1.42345E-03 -1.21253E-03 -1.17694E-03 -1.05901E-03 -9.29611E-04 -1.35587E-03 -1.13579E-03 -1.14964E-03 -1.29313E-03 -1.46566E-03 +4.18486E-03 +1.72126E-03 +1.10899E-03 +1.88170E-03 +1.31646E-03 +1.34128E-03 +1.57944E-03 +2.11251E-03 +1.79912E-03 +1.86000E-03 +1.47765E-03 cmfd dominance ratio 5.524E-01 -5.614E-01 -5.522E-01 -5.487E-01 -5.482E-01 -5.446E-01 -5.437E-01 -5.429E-01 -5.407E-01 -5.380E-01 -5.377E-01 +5.597E-01 +5.622E-01 +5.544E-01 +5.541E-01 +5.519E-01 +5.532E-01 +5.550E-01 +5.484E-01 +5.497E-01 +5.500E-01 cmfd openmc source comparison -1.586045E-02 -6.953134E-03 -6.860419E-03 -6.198467E-03 -5.142854E-03 -4.373354E-03 -5.564831E-03 -4.184765E-03 -1.867780E-03 -2.734784E-03 -2.523985E-03 +1.905464E-03 +4.145126E-03 +2.465876E-03 +2.346755E-03 +1.848120E-03 +3.263822E-03 +3.641639E-03 +4.031509E-03 +4.999010E-03 +6.640746E-03 +5.691414E-03 cmfd source -4.241440E-02 -8.226026E-02 -1.180811E-01 -1.328433E-01 -1.412410E-01 -1.424902E-01 -1.269340E-01 -1.096490E-01 -6.953251E-02 -3.455422E-02 +4.951338E-02 +8.478025E-02 +1.083132E-01 +1.301432E-01 +1.341190E-01 +1.445825E-01 +1.255119E-01 +1.063303E-01 +7.830158E-02 +3.840469E-02 diff --git a/tests/regression_tests/cmfd_feed_ng/results_true.dat b/tests/regression_tests/cmfd_feed_ng/results_true.dat index 153238bfeb..4ea1515f18 100644 --- a/tests/regression_tests/cmfd_feed_ng/results_true.dat +++ b/tests/regression_tests/cmfd_feed_ng/results_true.dat @@ -1,208 +1,208 @@ k-combined: -1.005987E+00 1.354263E-02 +1.008852E+00 9.028695E-03 tally 1: -1.140273E+02 -1.301245E+03 -1.147962E+02 -1.319049E+03 -1.151426E+02 -1.326442E+03 -1.149265E+02 -1.321518E+03 +1.151271E+02 +1.325871E+03 +1.143934E+02 +1.309051E+03 +1.142507E+02 +1.306616E+03 +1.140242E+02 +1.300786E+03 tally 2: -3.462748E+01 -7.542476E+01 -5.129219E+01 -1.658142E+02 -1.034704E+01 -6.730603E+00 -8.672967E+00 -4.715295E+00 -1.344669E+02 -1.132019E+03 -7.262519E+01 -3.300787E+02 -3.447358E+01 -7.459545E+01 -5.075836E+01 -1.619570E+02 -1.080516E+01 -7.366369E+00 -8.908065E+00 -4.991975E+00 -1.354224E+02 -1.146824E+03 -7.300078E+01 -3.332531E+02 -3.432298E+01 -7.388666E+01 -5.096378E+01 -1.627979E+02 -1.053664E+01 -7.029789E+00 -8.826624E+00 -4.904429E+00 -1.388389E+02 -1.207280E+03 -7.376623E+01 -3.403211E+02 -4.383841E+01 -1.943331E+02 -5.165881E+01 -1.675923E+02 -1.059646E+01 -7.048052E+00 -8.763673E+00 -4.823505E+00 -1.378179E+02 -1.188104E+03 -7.431708E+01 -3.453746E+02 +3.403617E+01 +7.260478E+01 +5.031678E+01 +1.588977E+02 +1.003700E+01 +6.373741E+00 +8.514575E+00 +4.571811E+00 +1.413036E+02 +1.264708E+03 +7.321799E+01 +3.353408E+02 +3.354839E+01 +7.052647E+01 +4.895930E+01 +1.501243E+02 +9.972495E+00 +6.271276E+00 +8.436263E+00 +4.481319E+00 +1.353506E+02 +1.146040E+03 +7.309382E+01 +3.341751E+02 +3.389861E+01 +7.205501E+01 +5.005946E+01 +1.571210E+02 +1.041650E+01 +6.810868E+00 +8.839753E+00 +4.897617E+00 +1.344145E+02 +1.130242E+03 +7.270373E+01 +3.307223E+02 +3.347928E+01 +7.040185E+01 +4.940585E+01 +1.535767E+02 +9.898649E+00 +6.175319E+00 +8.406032E+00 +4.442856E+00 +1.374544E+02 +1.182191E+03 +7.334301E+01 +3.365399E+02 tally 3: -4.858880E+01 -1.488705E+02 +4.755532E+01 +1.419592E+02 0.000000E+00 0.000000E+00 -8.148667E-03 -1.337050E-05 +1.628248E-02 +3.680742E-05 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.347376E+00 -7.045574E-01 -2.433484E+00 -3.727266E-01 +3.347160E+00 +7.104290E-01 +2.453669E+00 +3.797470E-01 0.000000E+00 0.000000E+00 -6.095478E+00 -2.332622E+00 +5.925795E+00 +2.220734E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.235421E-01 -1.205155E-03 -3.647699E-01 -8.953589E-03 +9.542527E-02 +1.118856E-03 +3.018759E-01 +6.371059E-03 0.000000E+00 0.000000E+00 -2.673965E+00 -4.517972E-01 +2.501316E+00 +3.938401E-01 0.000000E+00 0.000000E+00 -6.841105E+01 -2.929195E+02 -5.902473E-01 -2.307683E-02 -4.792291E+01 -1.444397E+02 +6.926265E+01 +3.001504E+02 +6.765221E-01 +2.991787E-02 +4.605523E+01 +1.328435E+02 0.000000E+00 0.000000E+00 -2.183275E-02 -8.061011E-05 +1.687782E-02 +3.921162E-05 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.435826E+00 -7.480244E-01 -2.450829E+00 -3.800327E-01 +3.481608E+00 +7.705602E-01 +2.439374E+00 +3.779705E-01 0.000000E+00 0.000000E+00 -6.331358E+00 -2.530492E+00 +5.855806E+00 +2.162361E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.012941E-01 -8.217580E-04 -2.981274E-01 -5.863186E-03 +1.016677E-01 +9.263706E-04 +3.264878E-01 +7.385168E-03 0.000000E+00 0.000000E+00 -2.535628E+00 -4.048310E-01 +2.519730E+00 +3.986182E-01 0.000000E+00 0.000000E+00 -6.912003E+01 -2.987684E+02 -5.984862E-01 -2.386115E-02 -4.822881E+01 -1.458309E+02 +6.920950E+01 +2.996184E+02 +5.985719E-01 +2.368062E-02 +4.730723E+01 +1.403550E+02 0.000000E+00 0.000000E+00 -1.525590E-02 -3.794082E-05 +6.800415E-03 +1.163614E-05 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.314494E+00 -6.944527E-01 -2.424209E+00 -3.691360E-01 +3.347607E+00 +7.085691E-01 +2.556997E+00 +4.109118E-01 0.000000E+00 0.000000E+00 -6.254897E+00 -2.474317E+00 +6.171063E+00 +2.391770E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.112542E-01 -1.051688E-03 -3.234880E-01 -7.156753E-03 +7.942016E-02 +5.628747E-04 +3.456912E-01 +7.940086E-03 0.000000E+00 0.000000E+00 -2.474142E+00 -3.837496E-01 +2.684459E+00 +4.546338E-01 0.000000E+00 0.000000E+00 -6.987095E+01 -3.053358E+02 -5.928782E-01 -2.368116E-02 -4.885415E+01 -1.499856E+02 +6.850588E+01 +2.936078E+02 +6.458806E-01 +2.672541E-02 +4.673301E+01 +1.374202E+02 0.000000E+00 0.000000E+00 -1.262416E-02 -2.486286E-05 +1.504681E-02 +4.202606E-05 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.426826E+00 -7.480396E-01 -2.487209E+00 -3.903882E-01 +3.139138E+00 +6.206027E-01 +2.341735E+00 +3.454035E-01 0.000000E+00 0.000000E+00 -6.127303E+00 -2.364605E+00 +5.923755E+00 +2.216341E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -9.439007E-02 -1.082564E-03 -2.963491E-01 -5.652952E-03 +7.030156E-02 +4.283974E-04 +3.247594E-01 +7.133772E-03 0.000000E+00 0.000000E+00 -2.620696E+00 -4.311792E-01 +2.559691E+00 +4.119674E-01 0.000000E+00 0.000000E+00 -7.030725E+01 -3.091241E+02 -5.986966E-01 -2.352487E-02 +6.938051E+01 +3.012078E+02 +5.159565E-01 +1.730381E-02 tally 4: 0.000000E+00 0.000000E+00 @@ -216,18 +216,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.028624E+00 -3.105990E+00 -2.154648E+00 -2.948865E-01 -2.714077E+01 -4.607926E+01 -7.035506E+00 -3.118549E+00 -2.085916E+00 -2.730884E-01 -2.750091E+01 -4.731304E+01 +7.028166E+00 +3.103666E+00 +2.028371E+00 +2.606104E-01 +2.715466E+01 +4.614452E+01 +6.981028E+00 +3.059096E+00 +2.032450E+00 +2.610410E-01 +2.734281E+01 +4.675062E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -240,18 +240,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.170567E+00 -3.240715E+00 -2.131758E+00 -2.862355E-01 -2.747702E+01 -4.722977E+01 -7.068817E+00 -3.139275E+00 -2.095865E+00 -2.762179E-01 -2.737835E+01 -4.688689E+01 +6.969559E+00 +3.054867E+00 +2.042871E+00 +2.624815E-01 +2.766332E+01 +4.787778E+01 +7.022610E+00 +3.098329E+00 +2.109973E+00 +2.824233E-01 +2.733826E+01 +4.676309E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -276,18 +276,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.035506E+00 -3.118549E+00 -2.085916E+00 -2.730884E-01 -2.750091E+01 -4.731304E+01 -7.028624E+00 -3.105990E+00 -2.154648E+00 -2.948865E-01 -2.714077E+01 -4.607926E+01 +6.981028E+00 +3.059096E+00 +2.032450E+00 +2.610410E-01 +2.734281E+01 +4.675062E+01 +7.028166E+00 +3.103666E+00 +2.028371E+00 +2.606104E-01 +2.715466E+01 +4.614452E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -312,18 +312,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.103896E+00 -3.171147E+00 -2.095666E+00 -2.756673E-01 -2.711842E+01 -4.600196E+01 -7.197270E+00 -3.255501E+00 -2.046179E+00 -2.630301E-01 -2.729901E+01 -4.662030E+01 +6.782152E+00 +2.885448E+00 +1.951138E+00 +2.400912E-01 +2.739652E+01 +4.697696E+01 +6.873220E+00 +2.965563E+00 +1.999066E+00 +2.521586E-01 +2.732700E+01 +4.670990E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -360,30 +360,30 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.240906E+00 -3.296285E+00 -2.130816E+00 -2.850713E-01 -2.761433E+01 -4.771548E+01 -7.126427E+00 -3.199209E+00 -2.177254E+00 -2.998765E-01 -2.754936E+01 -4.748447E+01 -7.068817E+00 -3.139275E+00 -2.095865E+00 -2.762179E-01 -2.737835E+01 -4.688689E+01 -7.170567E+00 -3.240715E+00 -2.131758E+00 -2.862355E-01 -2.747702E+01 -4.722977E+01 +6.933695E+00 +3.028826E+00 +2.080336E+00 +2.719620E-01 +2.726925E+01 +4.650782E+01 +6.836291E+00 +2.935998E+00 +2.124868E+00 +2.841370E-01 +2.709685E+01 +4.591604E+01 +7.022610E+00 +3.098329E+00 +2.109973E+00 +2.824233E-01 +2.733826E+01 +4.676309E+01 +6.969559E+00 +3.054867E+00 +2.042871E+00 +2.624815E-01 +2.766332E+01 +4.787778E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -420,18 +420,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.126427E+00 -3.199209E+00 -2.177254E+00 -2.998765E-01 -2.754936E+01 -4.748447E+01 -7.240906E+00 -3.296285E+00 -2.130816E+00 -2.850713E-01 -2.761433E+01 -4.771548E+01 +6.836291E+00 +2.935998E+00 +2.124868E+00 +2.841370E-01 +2.709685E+01 +4.591604E+01 +6.933695E+00 +3.028826E+00 +2.080336E+00 +2.719620E-01 +2.726925E+01 +4.650782E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -444,18 +444,18 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.197270E+00 -3.255501E+00 -2.046179E+00 -2.630301E-01 -2.729901E+01 -4.662030E+01 -7.103896E+00 -3.171147E+00 -2.095666E+00 -2.756673E-01 -2.711842E+01 -4.600196E+01 +6.873220E+00 +2.965563E+00 +1.999066E+00 +2.521586E-01 +2.732700E+01 +4.670990E+01 +6.782152E+00 +2.885448E+00 +1.951138E+00 +2.400912E-01 +2.739652E+01 +4.697696E+01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -493,124 +493,124 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -4.859695E+01 -1.489217E+02 -8.528963E+00 -4.561881E+00 -7.144500E+01 -3.194467E+02 -1.120265E+01 -7.944038E+00 -4.009821E+00 -1.012575E+00 -3.235456E+01 -6.558658E+01 -4.794474E+01 -1.445671E+02 -8.782187E+00 -4.852477E+00 -7.195036E+01 -3.237389E+02 -1.075572E+01 -7.333822E+00 -4.084680E+00 -1.054714E+00 -3.267154E+01 -6.675266E+01 -4.824407E+01 -1.459220E+02 -8.679106E+00 -4.742342E+00 -7.266858E+01 -3.302641E+02 -1.094872E+01 -7.536318E+00 -3.935828E+00 -9.749543E-01 -3.319517E+01 -6.894791E+01 -4.886677E+01 -1.500624E+02 -8.614512E+00 -4.662618E+00 -7.321408E+01 -3.352172E+02 -1.095123E+01 -7.574359E+00 -3.885927E+00 -9.539315E-01 -3.334065E+01 -6.953215E+01 +4.757160E+01 +1.420561E+02 +8.379464E+00 +4.426892E+00 +7.205748E+01 +3.248178E+02 +1.047742E+01 +6.922945E+00 +3.879420E+00 +9.517577E-01 +3.297227E+01 +6.802001E+01 +4.607211E+01 +1.329402E+02 +8.295180E+00 +4.334618E+00 +7.205259E+01 +3.247324E+02 +1.059307E+01 +7.039382E+00 +3.783039E+00 +9.030658E-01 +3.288052E+01 +6.762048E+01 +4.731403E+01 +1.403940E+02 +8.728060E+00 +4.774750E+00 +7.152809E+01 +3.200993E+02 +1.074636E+01 +7.270116E+00 +4.007351E+00 +1.010562E+00 +3.249303E+01 +6.611829E+01 +4.674806E+01 +1.375015E+02 +8.265491E+00 +4.296947E+00 +7.226174E+01 +3.267127E+02 +1.079228E+01 +7.340408E+00 +3.843888E+00 +9.273339E-01 +3.300391E+01 +6.823122E+01 cmfd indices 2.000000E+00 2.000000E+00 1.000000E+00 3.000000E+00 k cmfd -1.026473E+00 -1.024183E+00 -1.023151E+00 -1.025047E+00 -1.019801E+00 -1.020492E+00 -1.015249E+00 -1.016714E+00 -1.016047E+00 -1.019687E+00 -1.020955E+00 +1.011190E+00 +1.010705E+00 +1.014132E+00 +1.015900E+00 +1.019132E+00 +1.022616E+00 +1.023007E+00 +1.022300E+00 +1.014692E+00 +1.007628E+00 +1.006204E+00 cmfd entropy -1.999640E+00 -1.999556E+00 -1.999484E+00 -1.999718E+00 -1.999697E+00 -1.999657E+00 -1.999883E+00 -1.999902E+00 -1.999977E+00 -1.999977E+00 -1.999906E+00 +1.999167E+00 +1.999076E+00 +1.998507E+00 +1.997924E+00 +1.997814E+00 +1.997752E+00 +1.997882E+00 +1.998074E+00 +1.998109E+00 +1.998301E+00 +1.998581E+00 cmfd balance -8.10090E-04 -1.28103E-03 -7.97200E-04 -5.82188E-04 -7.20670E-04 -7.31475E-04 -5.71904E-04 -6.14057E-04 -6.00142E-04 -5.47870E-04 -3.53604E-04 +9.30124E-04 +2.56632E-04 +3.62598E-04 +4.17543E-04 +5.25720E-04 +4.90208E-04 +3.61304E-04 +2.24090E-04 +1.86602E-04 +1.78395E-04 +6.42497E-05 cmfd dominance ratio -3.977E-03 -4.018E-03 -3.950E-03 -3.866E-03 -3.840E-03 -3.888E-03 -3.867E-03 -3.896E-03 -3.924E-03 -3.885E-03 -3.913E-03 +4.194E-03 +4.234E-03 +4.149E-03 +4.209E-03 +4.185E-03 +4.197E-03 +4.175E-03 +4.105E-03 +4.056E-03 +4.122E-03 +4.113E-03 cmfd openmc source comparison -4.787501E-05 -4.450525E-05 -2.532345E-05 -3.844307E-05 -4.821504E-05 -4.840760E-05 -3.739246E-05 -3.957960E-05 -4.521480E-05 -4.072007E-05 -2.532636E-05 +2.078995E-05 +2.415218E-05 +3.311536E-05 +3.598613E-05 +3.156455E-05 +2.737017E-05 +2.468500E-05 +2.514215E-05 +1.601626E-05 +1.424027E-05 +4.201148E-06 cmfd source -2.486236E-01 -2.531628E-01 -2.460219E-01 -2.521918E-01 +2.558585E-01 +2.597562E-01 +2.529866E-01 +2.313986E-01 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/tests/regression_tests/cmfd_feed_rectlin/results_true.dat b/tests/regression_tests/cmfd_feed_rectlin/results_true.dat index 600b5d1528..a98f3fbd38 100644 --- a/tests/regression_tests/cmfd_feed_rectlin/results_true.dat +++ b/tests/regression_tests/cmfd_feed_rectlin/results_true.dat @@ -1,149 +1,149 @@ k-combined: -1.160561E+00 1.029736E-02 +1.157362E+00 9.651846E-03 tally 1: -1.089904E+01 -1.193573E+01 -2.026534E+01 -4.113383E+01 -2.723584E+01 -7.440537E+01 -3.309956E+01 -1.101184E+02 -3.659327E+01 -1.341221E+02 -3.780158E+01 -1.430045E+02 -3.520883E+01 -1.241772E+02 -2.961801E+01 -8.784675E+01 -2.182029E+01 -4.781083E+01 -1.180347E+01 -1.399970E+01 +1.160989E+01 +1.351117E+01 +2.127132E+01 +4.540172E+01 +2.903242E+01 +8.450044E+01 +3.443549E+01 +1.188763E+02 +3.678332E+01 +1.355586E+02 +3.760088E+01 +1.418740E+02 +3.433077E+01 +1.181837E+02 +2.861986E+01 +8.231285E+01 +2.182277E+01 +4.792086E+01 +1.138713E+01 +1.304425E+01 tally 2: -8.794706E+00 -3.939413E+00 -6.131113E+00 -1.913116E+00 -3.265522E+01 -5.364042E+01 -2.304238E+01 -2.672742E+01 -2.250225E+01 -2.541491E+01 -1.601668E+01 -1.288405E+01 -5.525355E+01 -1.531915E+02 -3.929637E+01 -7.748545E+01 -3.222711E+01 -5.216630E+01 -2.285375E+01 -2.623641E+01 -7.051908E+01 -2.495413E+02 -5.010064E+01 -1.259701E+02 -3.728726E+01 -6.974440E+01 -2.652872E+01 -3.530919E+01 -3.747306E+01 -7.058235E+01 -2.681415E+01 -3.613314E+01 -7.296802E+01 -2.669214E+02 -5.202502E+01 -1.356733E+02 -3.333947E+01 -5.579355E+01 -2.361733E+01 -2.800800E+01 -5.785916E+01 -1.680561E+02 -4.093282E+01 -8.410711E+01 -2.377151E+01 -2.842464E+01 -1.681789E+01 -1.423646E+01 -3.422028E+01 -5.880493E+01 -2.415199E+01 -2.930240E+01 -8.890608E+00 -3.986356E+00 -6.140159E+00 -1.897764E+00 +8.861425E+00 +3.953963E+00 +6.090757E+00 +1.866235E+00 +3.309260E+01 +5.493482E+01 +2.330765E+01 +2.725350E+01 +2.295343E+01 +2.647375E+01 +1.629166E+01 +1.334081E+01 +5.714234E+01 +1.640293E+02 +4.054051E+01 +8.261123E+01 +3.331786E+01 +5.565082E+01 +2.366345E+01 +2.807637E+01 +7.034800E+01 +2.485209E+02 +5.001286E+01 +1.256087E+02 +3.651223E+01 +6.686058E+01 +2.606851E+01 +3.408881E+01 +3.729833E+01 +6.997492E+01 +2.657970E+01 +3.553107E+01 +7.212382E+01 +2.611253E+02 +5.124647E+01 +1.318756E+02 +3.304529E+01 +5.486643E+01 +2.347504E+01 +2.771353E+01 +5.711252E+01 +1.640619E+02 +4.060288E+01 +8.298231E+01 +2.384078E+01 +2.855909E+01 +1.684046E+01 +1.426180E+01 +3.329487E+01 +5.573544E+01 +2.349871E+01 +2.776487E+01 +8.676886E+00 +3.814132E+00 +5.980976E+00 +1.815143E+00 tally 3: -5.925339E+00 -1.788596E+00 -3.912632E-01 -8.061838E-03 -2.215544E+01 -2.471404E+01 -1.465191E+00 -1.092622E-01 -1.542988E+01 -1.195626E+01 -1.022876E+00 -5.356825E-02 -3.792029E+01 -7.218149E+01 -2.370476E+00 -2.839465E-01 -2.200154E+01 -2.432126E+01 -1.360836E+00 -9.402424E-02 -4.824980E+01 -1.168447E+02 -3.124366E+00 -4.907460E-01 -2.557420E+01 -3.282066E+01 -1.725855E+00 -1.519830E-01 -2.577963E+01 -3.341077E+01 -1.654042E+00 -1.386845E-01 -5.008220E+01 -1.257610E+02 -3.223857E+00 -5.237360E-01 -2.273380E+01 -2.595325E+01 -1.438369E+00 -1.050840E-01 -3.938822E+01 -7.789691E+01 -2.648324E+00 -3.559703E-01 -1.623604E+01 -1.327214E+01 -1.058882E+00 -5.680630E-02 -2.325730E+01 -2.717892E+01 -1.584276E+00 -1.275868E-01 -5.937929E+00 -1.774847E+00 -3.866918E-01 -7.994353E-03 +5.847135E+00 +1.719612E+00 +3.960040E-01 +8.297721E-03 +2.245534E+01 +2.530222E+01 +1.468678E+00 +1.094031E-01 +1.571194E+01 +1.240597E+01 +1.004169E+00 +5.156464E-02 +3.901605E+01 +7.652715E+01 +2.648696E+00 +3.571840E-01 +2.275978E+01 +2.597555E+01 +1.456067E+00 +1.075035E-01 +4.821184E+01 +1.167725E+02 +3.105774E+00 +4.859873E-01 +2.519281E+01 +3.183845E+01 +1.595498E+00 +1.292133E-01 +2.560583E+01 +3.297409E+01 +1.673871E+00 +1.429651E-01 +4.930025E+01 +1.220909E+02 +3.206604E+00 +5.220919E-01 +2.255825E+01 +2.560134E+01 +1.422870E+00 +1.027151E-01 +3.910818E+01 +7.698933E+01 +2.568903E+00 +3.333385E-01 +1.620292E+01 +1.321173E+01 +1.068678E+00 +5.798793E-02 +2.264343E+01 +2.578648E+01 +1.503553E+00 +1.158411E-01 +5.751110E+00 +1.676910E+00 +3.450582E-01 +6.411784E-03 tally 4: -3.063235E+00 -4.714106E-01 +3.051764E+00 +4.671879E-01 0.000000E+00 0.000000E+00 -1.425705E+00 -1.043616E-01 -4.355515E+00 -9.538346E-01 +1.407008E+00 +1.004485E-01 +4.354708E+00 +9.506434E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -160,14 +160,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.355515E+00 -9.538346E-01 -1.425705E+00 -1.043616E-01 -3.859174E+00 -7.519499E-01 -6.350310E+00 -2.024214E+00 +4.354708E+00 +9.506434E-01 +1.407008E+00 +1.004485E-01 +3.852730E+00 +7.498016E-01 +6.382605E+00 +2.043123E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -184,14 +184,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -6.350310E+00 -2.024214E+00 -3.859174E+00 -7.519499E-01 -4.993073E+00 -1.258264E+00 -7.194275E+00 -2.596886E+00 +6.382605E+00 +2.043123E+00 +3.852730E+00 +7.498016E-01 +5.061607E+00 +1.288306E+00 +7.281209E+00 +2.659444E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -208,14 +208,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.194275E+00 -2.596886E+00 -4.993073E+00 -1.258264E+00 -6.786617E+00 -2.312259E+00 -8.306978E+00 -3.459668E+00 +7.281209E+00 +2.659444E+00 +5.061607E+00 +1.288306E+00 +7.096602E+00 +2.527474E+00 +8.632232E+00 +3.736665E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -232,14 +232,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.306978E+00 -3.459668E+00 -6.786617E+00 -2.312259E+00 -7.603410E+00 -2.905228E+00 -8.791222E+00 -3.882935E+00 +8.632232E+00 +3.736665E+00 +7.096602E+00 +2.527474E+00 +7.759456E+00 +3.019026E+00 +8.968687E+00 +4.037738E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -256,14 +256,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.791222E+00 -3.882935E+00 -7.603410E+00 -2.905228E+00 -8.867113E+00 -3.938503E+00 -9.302808E+00 -4.340042E+00 +8.968687E+00 +4.037738E+00 +7.759456E+00 +3.019026E+00 +8.749025E+00 +3.839161E+00 +9.126289E+00 +4.176440E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -280,14 +280,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.302808E+00 -4.340042E+00 -8.867113E+00 -3.938503E+00 -9.270113E+00 -4.306513E+00 -9.263471E+00 -4.302184E+00 +9.126289E+00 +4.176440E+00 +8.749025E+00 +3.839161E+00 +9.259277E+00 +4.304020E+00 +9.165726E+00 +4.216173E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -304,14 +304,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.263471E+00 -4.302184E+00 -9.270113E+00 -4.306513E+00 -9.348712E+00 -4.388570E+00 -8.977713E+00 -4.047349E+00 +9.165726E+00 +4.216173E+00 +9.259277E+00 +4.304020E+00 +9.433925E+00 +4.473551E+00 +8.910566E+00 +3.991458E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -328,14 +328,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.977713E+00 -4.047349E+00 -9.348712E+00 -4.388570E+00 -9.234380E+00 -4.280666E+00 -8.036978E+00 -3.239853E+00 +8.910566E+00 +3.991458E+00 +9.433925E+00 +4.473551E+00 +9.099397E+00 +4.154062E+00 +7.770126E+00 +3.029928E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -352,14 +352,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.036978E+00 -3.239853E+00 -9.234380E+00 -4.280666E+00 -8.713633E+00 -3.808850E+00 -7.160878E+00 -2.572915E+00 +7.770126E+00 +3.029928E+00 +9.099397E+00 +4.154062E+00 +8.575842E+00 +3.694998E+00 +6.934243E+00 +2.418570E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -376,14 +376,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.160878E+00 -2.572915E+00 -8.713633E+00 -3.808850E+00 -7.378538E+00 -2.732122E+00 -5.145728E+00 -1.329190E+00 +6.934243E+00 +2.418570E+00 +8.575842E+00 +3.694998E+00 +7.437526E+00 +2.780629E+00 +5.136923E+00 +1.331553E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -400,14 +400,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.145728E+00 -1.329190E+00 -7.378538E+00 -2.732122E+00 -6.660125E+00 -2.228506E+00 -4.087925E+00 -8.435381E-01 +5.136923E+00 +1.331553E+00 +7.437526E+00 +2.780629E+00 +6.648582E+00 +2.216687E+00 +4.050691E+00 +8.279789E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -424,14 +424,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.087925E+00 -8.435381E-01 -6.660125E+00 -2.228506E+00 -4.466295E+00 -1.002320E+00 -1.468481E+00 -1.099604E-01 +4.050691E+00 +8.279789E-01 +6.648582E+00 +2.216687E+00 +4.390906E+00 +9.686686E-01 +1.391624E+00 +9.861955E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -448,12 +448,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -1.468481E+00 -1.099604E-01 -4.466295E+00 -1.002320E+00 -3.139355E+00 -4.955456E-01 +1.391624E+00 +9.861955E-02 +4.390906E+00 +9.686686E-01 +3.113477E+00 +4.874296E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -473,164 +473,164 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -5.925339E+00 -1.788596E+00 -8.954773E-01 -4.217679E-02 -2.215054E+01 -2.470273E+01 -2.944747E+00 -4.443186E-01 -1.542658E+01 -1.195085E+01 -1.950262E+00 -1.946340E-01 -3.791137E+01 -7.214779E+01 -4.955741E+00 -1.254830E+00 -2.200054E+01 -2.431894E+01 -3.031040E+00 -4.685971E-01 -4.823946E+01 -1.167941E+02 -6.226321E+00 -1.956308E+00 -2.556930E+01 -3.280828E+01 -3.582546E+00 -6.505962E-01 -2.577249E+01 -3.339204E+01 -3.316825E+00 -5.676842E-01 -5.007249E+01 -1.257124E+02 -6.462364E+00 -2.120157E+00 -2.273285E+01 -2.595106E+01 -2.960964E+00 -4.496277E-01 -3.937362E+01 -7.783849E+01 -5.339336E+00 -1.449257E+00 -1.623315E+01 -1.326746E+01 -2.289661E+00 -2.698618E-01 -2.325250E+01 -2.716827E+01 -3.253010E+00 -5.413837E-01 -5.937929E+00 -1.774847E+00 -9.208589E-01 -4.421403E-02 +5.846103E+00 +1.718959E+00 +8.952028E-01 +4.184063E-02 +2.245226E+01 +2.529524E+01 +3.092645E+00 +4.848878E-01 +1.571095E+01 +1.240426E+01 +2.178244E+00 +2.438479E-01 +3.900638E+01 +7.648853E+01 +5.265574E+00 +1.401505E+00 +2.275895E+01 +2.597348E+01 +3.067909E+00 +4.810969E-01 +4.820213E+01 +1.167232E+02 +6.403602E+00 +2.070034E+00 +2.519091E+01 +3.183360E+01 +3.463531E+00 +6.097568E-01 +2.560388E+01 +3.296889E+01 +3.456252E+00 +6.101655E-01 +4.929539E+01 +1.220666E+02 +6.629094E+00 +2.223366E+00 +2.255498E+01 +2.559363E+01 +2.833426E+00 +4.150907E-01 +3.909813E+01 +7.694976E+01 +5.582222E+00 +1.584757E+00 +1.620082E+01 +1.320814E+01 +2.282196E+00 +2.703156E-01 +2.263498E+01 +2.576758E+01 +3.162736E+00 +5.145038E-01 +5.750110E+00 +1.676357E+00 +9.181679E-01 +4.562885E-02 cmfd indices 1.400000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.125528E+00 -1.145509E+00 -1.158948E+00 -1.171983E+00 -1.180649E+00 -1.184072E+00 -1.188112E+00 -1.183095E+00 -1.182269E+00 -1.175467E+00 -1.175184E+00 -1.172637E+00 -1.171593E+00 -1.175439E+00 -1.174650E+00 -1.176474E+00 +1.166740E+00 +1.184008E+00 +1.166534E+00 +1.155559E+00 +1.164960E+00 +1.163229E+00 +1.165897E+00 +1.170104E+00 +1.170207E+00 +1.168091E+00 +1.170940E+00 +1.174589E+00 +1.174609E+00 +1.171505E+00 +1.174456E+00 +1.178370E+00 cmfd entropy -3.607059E+00 -3.604890E+00 -3.601329E+00 -3.597776E+00 -3.597360E+00 -3.597387E+00 -3.595379E+00 -3.596995E+00 -3.600901E+00 -3.601832E+00 -3.601426E+00 -3.604521E+00 -3.602848E+00 -3.603875E+00 -3.605213E+00 -3.606699E+00 +3.594757E+00 +3.587018E+00 +3.590385E+00 +3.595101E+00 +3.592151E+00 +3.600294E+00 +3.602102E+00 +3.604941E+00 +3.605897E+00 +3.604880E+00 +3.601658E+00 +3.602551E+00 +3.600160E+00 +3.604540E+00 +3.604094E+00 +3.602509E+00 cmfd balance -4.46212E-03 -4.66648E-03 -5.04274E-03 -5.21553E-03 -3.92498E-03 -2.97185E-03 -2.79785E-03 -2.66951E-03 -2.17472E-03 -1.98009E-03 -1.77035E-03 -1.51281E-03 -1.52807E-03 -1.33341E-03 -1.18155E-03 -1.07752E-03 +5.52960E-03 +5.42154E-03 +3.62152E-03 +2.92850E-03 +4.08642E-03 +2.07444E-03 +2.03704E-03 +2.06886E-03 +2.09646E-03 +1.94256E-03 +2.02728E-03 +1.89830E-03 +1.83910E-03 +1.48140E-03 +1.47034E-03 +1.64452E-03 cmfd dominance ratio -6.136E-01 -6.127E-01 -6.137E-01 -6.102E-01 -6.067E-01 -6.061E-01 -6.031E-01 6.046E-01 -6.071E-01 -6.089E-01 -6.073E-01 -6.080E-01 -6.080E-01 +6.015E-01 +6.059E-01 +6.060E-01 +6.061E-01 +6.109E-01 +6.110E-01 +6.108E-01 +6.120E-01 +6.124E-01 +6.109E-01 6.090E-01 -6.092E-01 -6.094E-01 +6.116E-01 +6.137E-01 +6.117E-01 +6.131E-01 cmfd openmc source comparison -1.043027E-02 -1.278226E-02 -1.184867E-02 -1.017186E-02 -1.099696E-02 -7.955341E-03 -8.360344E-03 -6.875508E-03 -4.824018E-03 -4.915363E-03 -5.371647E-03 -4.593100E-03 -4.894955E-03 -4.928253E-03 -4.292171E-03 -4.018545E-03 +1.035187E-02 +9.394886E-03 +6.879487E-03 +7.236029E-03 +6.543528E-03 +3.600620E-03 +2.859638E-03 +2.230047E-03 +2.180643E-03 +1.638534E-03 +1.764349E-03 +1.621487E-03 +1.221762E-03 +1.626297E-03 +1.951813E-03 +9.584126E-04 cmfd source -1.600876E-02 -6.000305E-02 -4.248071E-02 -9.935789E-02 -5.768092E-02 -1.338593E-01 -7.417398E-02 -7.102984E-02 -1.382563E-01 -6.181889E-02 -1.142473E-01 -4.571447E-02 -6.864655E-02 -1.672206E-02 +1.677059E-02 +6.229453E-02 +4.278394E-02 +1.134852E-01 +6.231020E-02 +1.327286E-01 +6.808362E-02 +7.130954E-02 +1.362127E-01 +6.048013E-02 +1.094460E-01 +4.546687E-02 +6.403310E-02 +1.459510E-02 diff --git a/tests/regression_tests/cmfd_feed_ref_d/results_true.dat b/tests/regression_tests/cmfd_feed_ref_d/results_true.dat index 9cc26b8cff..34cde1a46e 100644 --- a/tests/regression_tests/cmfd_feed_ref_d/results_true.dat +++ b/tests/regression_tests/cmfd_feed_ref_d/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.167869E+00 7.492916E-03 +1.162249E+00 5.812620E-03 tally 1: -1.146821E+01 -1.318787E+01 -2.161476E+01 -4.685066E+01 -2.951084E+01 -8.733116E+01 -3.521523E+01 -1.242762E+02 -3.774181E+01 -1.426460E+02 -3.727924E+01 -1.391162E+02 -3.377236E+01 -1.143877E+02 -2.904590E+01 -8.453427E+01 -2.090941E+01 -4.384824E+01 -1.078680E+01 -1.168172E+01 +1.153831E+01 +1.338142E+01 +2.155552E+01 +4.659071E+01 +2.813997E+01 +7.941672E+01 +3.270996E+01 +1.073664E+02 +3.639852E+01 +1.329148E+02 +3.729637E+01 +1.393474E+02 +3.443129E+01 +1.186461E+02 +2.832690E+01 +8.040998E+01 +2.177527E+01 +4.771147E+01 +1.146822E+01 +1.328252E+01 tally 2: -1.136805E+00 -1.292326E+00 -7.987282E-01 -6.379667E-01 -2.266961E+00 -5.139112E+00 -1.613498E+00 -2.603376E+00 -3.046379E+00 -9.280427E+00 -2.182480E+00 -4.763219E+00 -3.568101E+00 -1.273134E+01 -2.532478E+00 -6.413444E+00 -3.989532E+00 -1.591637E+01 -2.848319E+00 -8.112921E+00 -3.853139E+00 -1.484668E+01 -2.718497E+00 -7.390223E+00 -3.478134E+00 -1.209742E+01 -2.467279E+00 -6.087465E+00 -2.952214E+00 -8.715569E+00 -2.103257E+00 -4.423688E+00 -1.917446E+00 -3.676599E+00 -1.378361E+00 -1.899878E+00 -1.048230E+00 -1.098785E+00 -7.511876E-01 -5.642828E-01 +1.024353E+00 +1.049299E+00 +6.991057E-01 +4.887487E-01 +2.200432E+00 +4.841901E+00 +1.561655E+00 +2.438768E+00 +2.910400E+00 +8.470426E+00 +2.095155E+00 +4.389674E+00 +3.466006E+00 +1.201320E+01 +2.480456E+00 +6.152662E+00 +3.711781E+00 +1.377732E+01 +2.646019E+00 +7.001418E+00 +3.953648E+00 +1.563133E+01 +2.832759E+00 +8.024524E+00 +3.597870E+00 +1.294467E+01 +2.555396E+00 +6.530048E+00 +2.860871E+00 +8.184585E+00 +2.032282E+00 +4.130169E+00 +2.006740E+00 +4.027007E+00 +1.408150E+00 +1.982886E+00 +1.035163E+00 +1.071562E+00 +7.084068E-01 +5.018402E-01 tally 3: -7.701212E-01 -5.930866E-01 -4.481580E-02 -2.008456E-03 -1.547321E+00 -2.394203E+00 -1.226538E-01 -1.504395E-02 -2.106393E+00 -4.436893E+00 -1.450617E-01 -2.104289E-02 -2.437675E+00 -5.942260E+00 -1.521379E-01 -2.314593E-02 -2.754657E+00 -7.588135E+00 -1.745458E-01 -3.046622E-02 -2.623856E+00 -6.884619E+00 -1.851600E-01 -3.428423E-02 -2.376884E+00 -5.649579E+00 -1.615728E-01 -2.610576E-02 -2.021851E+00 -4.087882E+00 -1.533172E-01 -2.350617E-02 -1.333182E+00 -1.777374E+00 -7.076179E-02 -5.007231E-03 -7.258458E-01 -5.268521E-01 -3.656026E-02 -1.336653E-03 +6.713566E-01 +4.507196E-01 +5.581718E-02 +3.115557E-03 +1.508976E+00 +2.277009E+00 +1.139601E-01 +1.298690E-02 +2.035529E+00 +4.143377E+00 +1.221001E-01 +1.490843E-02 +2.385217E+00 +5.689262E+00 +1.500087E-01 +2.250260E-02 +2.546286E+00 +6.483574E+00 +1.546601E-01 +2.391975E-02 +2.726427E+00 +7.433407E+00 +1.686144E-01 +2.843081E-02 +2.466613E+00 +6.084179E+00 +1.558230E-01 +2.428079E-02 +1.951251E+00 +3.807379E+00 +1.197744E-01 +1.434590E-02 +1.347903E+00 +1.816842E+00 +9.419149E-02 +8.872037E-03 +6.840490E-01 +4.679231E-01 +5.000289E-02 +2.500289E-03 tally 4: -1.667426E-01 -2.780308E-02 +1.561665E-01 +2.438798E-02 0.000000E+00 0.000000E+00 -1.292556E-01 -1.670700E-02 -2.813401E-01 -7.915227E-02 +1.307011E-01 +1.708276E-02 +2.703168E-01 +7.307115E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.813401E-01 -7.915227E-02 -1.292556E-01 -1.670700E-02 -2.670582E-01 -7.132006E-02 -4.055365E-01 -1.644599E-01 +2.703168E-01 +7.307115E-02 +1.307011E-01 +1.708276E-02 +2.637619E-01 +6.957033E-02 +3.685390E-01 +1.358210E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.055365E-01 -1.644599E-01 -2.670582E-01 -7.132006E-02 -3.848164E-01 -1.480837E-01 -4.809472E-01 -2.313102E-01 +3.685390E-01 +1.358210E-01 +2.637619E-01 +6.957033E-02 +3.887017E-01 +1.510890E-01 +4.439407E-01 +1.970834E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.809472E-01 -2.313102E-01 -3.848164E-01 -1.480837E-01 -4.543959E-01 -2.064756E-01 -5.106174E-01 -2.607301E-01 +4.439407E-01 +1.970834E-01 +3.887017E-01 +1.510890E-01 +4.456116E-01 +1.985697E-01 +4.737035E-01 +2.243950E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.106174E-01 -2.607301E-01 -4.543959E-01 -2.064756E-01 -4.543155E-01 -2.064026E-01 -4.626331E-01 -2.140294E-01 +4.737035E-01 +2.243950E-01 +4.456116E-01 +1.985697E-01 +4.760577E-01 +2.266309E-01 +4.703245E-01 +2.212052E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.626331E-01 -2.140294E-01 -4.543155E-01 -2.064026E-01 -4.827763E-01 -2.330729E-01 -4.442611E-01 -1.973679E-01 +4.703245E-01 +2.212052E-01 +4.760577E-01 +2.266309E-01 +4.878056E-01 +2.379543E-01 +4.373120E-01 +1.912418E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.442611E-01 -1.973679E-01 -4.827763E-01 -2.330729E-01 -4.630415E-01 -2.144074E-01 -3.886521E-01 -1.510505E-01 +4.373120E-01 +1.912418E-01 +4.878056E-01 +2.379543E-01 +4.262194E-01 +1.816630E-01 +3.334152E-01 +1.111657E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.886521E-01 -1.510505E-01 -4.630415E-01 -2.144074E-01 -3.535862E-01 -1.250232E-01 -2.530293E-01 -6.402384E-02 +3.334152E-01 +1.111657E-01 +4.262194E-01 +1.816630E-01 +3.560156E-01 +1.267471E-01 +2.409954E-01 +5.807879E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.530293E-01 -6.402384E-02 -3.535862E-01 -1.250232E-01 -2.465508E-01 -6.078730E-02 -1.197139E-01 -1.433141E-02 +2.409954E-01 +5.807879E-02 +3.560156E-01 +1.267471E-01 +2.646501E-01 +7.003965E-02 +1.327244E-01 +1.761576E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -1.197139E-01 -1.433141E-02 -2.465508E-01 -6.078730E-02 -1.369614E-01 -1.875841E-02 +1.327244E-01 +1.761576E-02 +2.646501E-01 +7.003965E-02 +1.480567E-01 +2.192079E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,119 +345,119 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -7.701212E-01 -5.930866E-01 -1.386254E-01 -1.921700E-02 -1.547321E+00 -2.394203E+00 -2.630318E-01 -6.918571E-02 -2.106393E+00 -4.436893E+00 -2.807911E-01 -7.884363E-02 -2.435870E+00 -5.933464E+00 -3.322093E-01 -1.103630E-01 -2.753652E+00 -7.582597E+00 -3.825961E-01 -1.463797E-01 -2.623856E+00 -6.884619E+00 -3.888719E-01 -1.512213E-01 -2.376884E+00 -5.649579E+00 -3.196211E-01 -1.021576E-01 -2.021851E+00 -4.087882E+00 -2.897873E-01 -8.397667E-02 -1.333182E+00 -1.777374E+00 -1.627096E-01 -2.647441E-02 -7.258458E-01 -5.268521E-01 -9.348575E-02 -8.739586E-03 +6.713566E-01 +4.507196E-01 +9.805793E-02 +9.615358E-03 +1.508976E+00 +2.277009E+00 +1.968348E-01 +3.874394E-02 +2.032573E+00 +4.131353E+00 +2.120922E-01 +4.498309E-02 +2.385217E+00 +5.689262E+00 +2.863031E-01 +8.196946E-02 +2.545200E+00 +6.478041E+00 +3.278920E-01 +1.075131E-01 +2.726427E+00 +7.433407E+00 +3.770758E-01 +1.421861E-01 +2.466613E+00 +6.084179E+00 +3.593230E-01 +1.291130E-01 +1.951251E+00 +3.807379E+00 +2.474112E-01 +6.121229E-02 +1.347903E+00 +1.816842E+00 +2.127109E-01 +4.524594E-02 +6.823620E-01 +4.656179E-01 +1.249863E-01 +1.562159E-02 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.149087E+00 -1.156777E+00 -1.158641E+00 -1.159507E+00 -1.156564E+00 -1.160257E+00 -1.150344E+00 -1.149854E+00 -1.151616E+00 -1.164575E+00 -1.174683E+00 +1.181365E+00 +1.176693E+00 +1.161946E+00 +1.163565E+00 +1.163043E+00 +1.169908E+00 +1.149155E+00 +1.142379E+00 +1.152957E+00 +1.137602E+00 +1.141883E+00 cmfd entropy -3.216202E+00 -3.228703E+00 -3.220414E+00 -3.214361E+00 -3.215642E+00 -3.213607E+00 -3.212862E+00 -3.213128E+00 -3.213189E+00 -3.205465E+00 -3.202859E+00 +3.246422E+00 +3.246496E+00 +3.252238E+00 +3.240920E+00 +3.237606E+00 +3.234301E+00 +3.234103E+00 +3.229918E+00 +3.226983E+00 +3.221321E+00 +3.223622E+00 cmfd balance -3.08825E-03 -1.42554E-03 -1.21448E-03 -1.17859E-03 -1.06034E-03 -9.30949E-04 -1.35713E-03 -1.13694E-03 -1.14938E-03 -1.29296E-03 -1.46518E-03 +4.18486E-03 +1.72126E-03 +1.10906E-03 +1.88158E-03 +1.31626E-03 +1.30818E-03 +1.77315E-03 +2.16148E-03 +1.67789E-03 +2.31333E-03 +1.94932E-03 cmfd dominance ratio -5.503E-01 -5.596E-01 5.505E-01 -5.471E-01 -5.468E-01 -5.427E-01 -5.421E-01 -5.412E-01 -5.389E-01 -5.371E-01 -5.329E-01 +5.580E-01 +5.610E-01 +5.526E-01 +5.519E-01 +5.499E-01 +5.504E-01 +5.504E-01 +5.475E-01 +5.465E-01 +5.477E-01 cmfd openmc source comparison -1.571006E-02 -6.945629E-03 -6.838511E-03 -6.183655E-03 -5.138825E-03 -4.362701E-03 -5.558586E-03 -4.188314E-03 -1.837101E-03 -2.737321E-03 -2.529244E-03 +1.902234E-03 +4.110960E-03 +2.452031E-03 +2.337951E-03 +1.838979E-03 +3.138637E-03 +2.684401E-03 +2.912891E-03 +2.823494E-03 +6.391584E-03 +5.904139E-03 cmfd source -4.240947E-02 -8.226746E-02 -1.180848E-01 -1.328470E-01 -1.412449E-01 -1.424870E-01 -1.269297E-01 -1.096476E-01 -6.953001E-02 -3.455212E-02 +4.488002E-02 +8.895136E-02 +1.085930E-01 +1.229651E-01 +1.330479E-01 +1.497140E-01 +1.309102E-01 +1.028556E-01 +7.738878E-02 +4.069397E-02 diff --git a/tests/regression_tests/cmfd_feed_rolling_window/results_true.dat b/tests/regression_tests/cmfd_feed_rolling_window/results_true.dat index 5ff4a132fd..2e31b35bab 100644 --- a/tests/regression_tests/cmfd_feed_rolling_window/results_true.dat +++ b/tests/regression_tests/cmfd_feed_rolling_window/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.173626E+00 1.098719E-02 +1.158333E+00 1.402684E-02 tally 1: -1.101892E+01 -1.218768E+01 -2.036233E+01 -4.152577E+01 -2.937587E+01 -8.637268E+01 -3.502389E+01 -1.231700E+02 -3.804803E+01 -1.453948E+02 -3.822561E+01 -1.465677E+02 -3.456290E+01 -1.198651E+02 -2.904088E+01 -8.470264E+01 -2.111529E+01 -4.463713E+01 -1.147633E+01 -1.326012E+01 +1.169478E+01 +1.373162E+01 +2.192038E+01 +4.844559E+01 +2.913292E+01 +8.542569E+01 +3.446069E+01 +1.201782E+02 +3.624088E+01 +1.320213E+02 +3.569791E+01 +1.278170E+02 +3.340601E+01 +1.119165E+02 +2.908648E+01 +8.514603E+01 +2.175458E+01 +4.767916E+01 +1.171268E+01 +1.378033E+01 tally 2: -1.010478E+00 -1.021066E+00 -6.902031E-01 -4.763804E-01 -1.899891E+00 -3.609584E+00 -1.322615E+00 -1.749312E+00 -2.756419E+00 -7.597845E+00 -1.955934E+00 -3.825676E+00 -3.818740E+00 -1.458278E+01 -2.704746E+00 -7.315652E+00 -3.920857E+00 -1.537312E+01 -2.843144E+00 -8.083470E+00 -3.835060E+00 -1.470768E+01 -2.728705E+00 -7.445831E+00 -3.510590E+00 -1.232424E+01 -2.497237E+00 -6.236191E+00 -2.717388E+00 -7.384198E+00 -1.903638E+00 -3.623837E+00 -2.207863E+00 -4.874659E+00 -1.563588E+00 -2.444808E+00 -1.289027E+00 -1.661591E+00 -9.022714E-01 -8.140937E-01 +1.132414E+00 +1.282361E+00 +7.822980E-01 +6.119901E-01 +2.124428E+00 +4.513196E+00 +1.490832E+00 +2.222581E+00 +3.158472E+00 +9.975946E+00 +2.221665E+00 +4.935795E+00 +3.994786E+00 +1.595831E+01 +2.828109E+00 +7.998199E+00 +3.491035E+00 +1.218732E+01 +2.461223E+00 +6.057617E+00 +3.461784E+00 +1.198395E+01 +2.473337E+00 +6.117398E+00 +3.027132E+00 +9.163527E+00 +2.150455E+00 +4.624458E+00 +2.471217E+00 +6.106911E+00 +1.737168E+00 +3.017752E+00 +1.880969E+00 +3.538044E+00 +1.316574E+00 +1.733367E+00 +1.233103E+00 +1.520543E+00 +8.543318E-01 +7.298828E-01 tally 3: -6.593197E-01 -4.347024E-01 -5.216387E-02 -2.721069E-03 -1.266446E+00 -1.603885E+00 -8.298797E-02 -6.887003E-03 -1.888709E+00 -3.567222E+00 -1.398940E-01 -1.957033E-02 -2.616078E+00 -6.843867E+00 -1.588627E-01 -2.523735E-02 -2.733300E+00 -7.470927E+00 -1.944290E-01 -3.780262E-02 -2.643656E+00 -6.988917E+00 -1.612338E-01 -2.599633E-02 -2.410643E+00 -5.811199E+00 -1.754603E-01 -3.078631E-02 -1.838012E+00 -3.378288E+00 -1.126265E-01 -1.268473E-02 -1.500033E+00 -2.250100E+00 -1.102554E-01 -1.215626E-02 -8.750096E-01 -7.656418E-01 -6.757592E-02 -4.566505E-03 +7.540113E-01 +5.685330E-01 +6.367610E-02 +4.054646E-03 +1.436984E+00 +2.064922E+00 +8.961822E-02 +8.031425E-03 +2.132240E+00 +4.546449E+00 +1.356065E-01 +1.838913E-02 +2.726356E+00 +7.433016E+00 +1.780572E-01 +3.170438E-02 +2.379700E+00 +5.662970E+00 +1.544735E-01 +2.386206E-02 +2.383471E+00 +5.680933E+00 +1.568319E-01 +2.459624E-02 +2.047271E+00 +4.191318E+00 +1.662654E-01 +2.764418E-02 +1.673107E+00 +2.799287E+00 +1.132020E-01 +1.281468E-02 +1.271576E+00 +1.616906E+00 +7.546797E-02 +5.695415E-03 +8.249906E-01 +6.806094E-01 +5.660098E-02 +3.203671E-03 tally 4: -1.490605E-01 -2.221904E-02 +1.551630E-01 +2.407556E-02 0.000000E+00 0.000000E+00 -1.139233E-01 -1.297851E-02 -2.549497E-01 -6.499934E-02 +1.487992E-01 +2.214121E-02 +2.878091E-01 +8.283409E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.549497E-01 -6.499934E-02 -1.139233E-01 -1.297851E-02 -2.191337E-01 -4.801958E-02 -3.295187E-01 -1.085826E-01 +2.878091E-01 +8.283409E-02 +1.487992E-01 +2.214121E-02 +2.936596E-01 +8.623595E-02 +3.954149E-01 +1.563529E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.295187E-01 -1.085826E-01 -2.191337E-01 -4.801958E-02 -3.872400E-01 -1.499548E-01 -4.595835E-01 -2.112170E-01 +3.954149E-01 +1.563529E-01 +2.936596E-01 +8.623595E-02 +3.991153E-01 +1.592930E-01 +4.758410E-01 +2.264247E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.595835E-01 -2.112170E-01 -3.872400E-01 -1.499548E-01 -4.668106E-01 -2.179121E-01 -5.112307E-01 -2.613569E-01 +4.758410E-01 +2.264247E-01 +3.991153E-01 +1.592930E-01 +4.850882E-01 +2.353106E-01 +5.210840E-01 +2.715285E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.112307E-01 -2.613569E-01 -4.668106E-01 -2.179121E-01 -4.716605E-01 -2.224636E-01 -4.916148E-01 -2.416851E-01 +5.210840E-01 +2.715285E-01 +4.850882E-01 +2.353106E-01 +4.790245E-01 +2.294645E-01 +4.570092E-01 +2.088574E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.916148E-01 -2.416851E-01 -4.716605E-01 -2.224636E-01 -4.696777E-01 -2.205972E-01 -4.365150E-01 -1.905453E-01 +4.570092E-01 +2.088574E-01 +4.790245E-01 +2.294645E-01 +4.505886E-01 +2.030301E-01 +3.884038E-01 +1.508575E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -4.365150E-01 -1.905453E-01 -4.696777E-01 -2.205972E-01 -4.179902E-01 -1.747158E-01 -3.350564E-01 -1.122628E-01 +3.884038E-01 +1.508575E-01 +4.505886E-01 +2.030301E-01 +3.986999E-01 +1.589616E-01 +3.220889E-01 +1.037412E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -3.350564E-01 -1.122628E-01 -4.179902E-01 -1.747158E-01 -3.743487E-01 -1.401370E-01 -2.400661E-01 -5.763172E-02 +3.220889E-01 +1.037412E-01 +3.986999E-01 +1.589616E-01 +3.319083E-01 +1.101631E-01 +2.101261E-01 +4.415297E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.400661E-01 -5.763172E-02 -3.743487E-01 -1.401370E-01 -3.063657E-01 -9.385994E-02 -1.605078E-01 -2.576275E-02 +2.101261E-01 +4.415297E-02 +3.319083E-01 +1.101631E-01 +2.795459E-01 +7.814588E-02 +1.306499E-01 +1.706938E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -1.605078E-01 -2.576275E-02 -3.063657E-01 -9.385994E-02 -1.700639E-01 -2.892174E-02 +1.306499E-01 +1.706938E-02 +2.795459E-01 +7.814588E-02 +1.585507E-01 +2.513833E-02 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,119 +345,119 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -6.593197E-01 -4.347024E-01 -1.314196E-01 -1.727112E-02 -1.266446E+00 -1.603885E+00 -2.002491E-01 -4.009970E-02 -1.888709E+00 -3.567222E+00 -2.444522E-01 -5.975686E-02 -2.616078E+00 -6.843867E+00 -3.234935E-01 -1.046481E-01 -2.733300E+00 -7.470927E+00 -3.309500E-01 -1.095279E-01 -2.643656E+00 -6.988917E+00 -4.025014E-01 -1.620074E-01 -2.410643E+00 -5.811199E+00 -3.050040E-01 -9.302747E-02 -1.838012E+00 -3.378288E+00 -2.800764E-01 -7.844279E-02 -1.500033E+00 -2.250100E+00 -2.324765E-01 -5.404531E-02 -8.750096E-01 -7.656418E-01 -1.256919E-01 -1.579844E-02 +7.530237E-01 +5.670447E-01 +1.178984E-01 +1.390004E-02 +1.436984E+00 +2.064922E+00 +1.458395E-01 +2.126916E-02 +2.132240E+00 +4.546449E+00 +2.950109E-01 +8.703141E-02 +2.726356E+00 +7.433016E+00 +3.397288E-01 +1.154157E-01 +2.379700E+00 +5.662970E+00 +3.113206E-01 +9.692053E-02 +2.383471E+00 +5.680933E+00 +3.455611E-01 +1.194125E-01 +2.047271E+00 +4.191318E+00 +2.910986E-01 +8.473841E-02 +1.673107E+00 +2.799287E+00 +2.381996E-01 +5.673907E-02 +1.270672E+00 +1.614606E+00 +1.795241E-01 +3.222889E-02 +8.249906E-01 +6.806094E-01 +1.201397E-01 +1.443354E-02 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.166297E+00 -1.148237E+00 -1.162472E+00 -1.187078E+00 -1.188411E+00 -1.194879E+00 -1.216739E+00 -1.216829E+00 -1.196596E+00 -1.199223E+00 -1.211817E+00 +1.184474E+00 +1.188170E+00 +1.165127E+00 +1.135010E+00 +1.145439E+00 +1.158451E+00 +1.154420E+00 +1.179615E+00 +1.197843E+00 +1.181252E+00 +1.186316E+00 cmfd entropy -3.215349E+00 -3.225577E+00 -3.223357E+00 -3.208828E+00 -3.211072E+00 -3.206578E+00 -3.195799E+00 -3.198236E+00 -3.220074E+00 -3.230249E+00 -3.238015E+00 +3.243654E+00 +3.244091E+00 +3.249203E+00 +3.249952E+00 +3.245538E+00 +3.240838E+00 +3.238919E+00 +3.223131E+00 +3.216002E+00 +3.220324E+00 +3.224804E+00 cmfd balance -2.07468E-03 -2.39687E-03 -1.51020E-03 -2.07618E-03 -1.89367E-03 -2.00902E-03 -2.54856E-03 -2.43636E-03 -2.48527E-03 -3.07775E-03 -3.37967E-03 +4.21104E-03 +1.38052E-03 +1.34642E-03 +2.39255E-03 +2.07426E-03 +1.27927E-03 +2.26249E-03 +2.72103E-03 +2.71504E-03 +2.19156E-03 +1.91989E-03 cmfd dominance ratio -5.505E-01 -5.558E-01 -5.584E-01 -5.477E-01 -5.477E-01 -5.426E-01 -5.335E-01 -5.305E-01 -5.427E-01 +5.520E-01 +5.535E-01 +5.628E-01 +5.696E-01 +5.723E-01 +5.651E-01 +5.648E-01 +5.555E-01 +5.448E-01 +5.488E-01 5.484E-01 -5.465E-01 cmfd openmc source comparison -5.598628E-03 -1.162952E-02 -1.083004E-02 -1.037470E-02 -5.649750E-03 -5.137914E-03 -3.868209E-03 -1.208756E-02 -5.398131E-03 -8.119598E-03 -4.573105E-03 +1.713810E-03 +2.429503E-03 +4.526209E-03 +7.978149E-03 +3.320012E-03 +3.880041E-03 +1.580215E-02 +1.663452E-02 +1.878103E-02 +7.436342E-03 +3.724478E-03 cmfd source -4.219187E-02 -8.692096E-02 -1.061389E-01 -1.199181E-01 -1.377328E-01 -1.326161E-01 -1.345872E-01 -1.112871E-01 -7.569533E-02 -5.291175E-02 +4.688167E-02 +9.066303E-02 +1.150679E-01 +1.430247E-01 +1.370466E-01 +1.267615E-01 +1.244218E-01 +1.048774E-01 +7.083441E-02 +4.042108E-02 diff --git a/tests/regression_tests/cmfd_nofeed/results_true.dat b/tests/regression_tests/cmfd_nofeed/results_true.dat index 756aa45701..ea1a0230b9 100644 --- a/tests/regression_tests/cmfd_nofeed/results_true.dat +++ b/tests/regression_tests/cmfd_nofeed/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.172893E+00 8.095197E-03 +1.169143E+00 7.248013E-03 tally 1: -1.156995E+01 -1.347019E+01 -2.120053E+01 -4.531200E+01 -2.995993E+01 -8.997889E+01 -3.498938E+01 -1.226414E+02 -3.794510E+01 -1.442188E+02 -3.798115E+01 -1.446436E+02 -3.415954E+01 -1.171635E+02 -2.960329E+01 -8.785532E+01 -2.182231E+01 -4.782353E+01 -1.147379E+01 -1.321150E+01 +1.115130E+01 +1.249933E+01 +2.147608E+01 +4.643964E+01 +2.923697E+01 +8.598273E+01 +3.439175E+01 +1.189653E+02 +3.729169E+01 +1.395456E+02 +3.709975E+01 +1.380839E+02 +3.415420E+01 +1.168226E+02 +2.895696E+01 +8.419764E+01 +2.140382E+01 +4.646784E+01 +1.125483E+01 +1.275812E+01 tally 2: -2.345900E+01 -2.783672E+01 -1.627300E+01 -1.339749E+01 -4.127267E+01 -8.563716E+01 -2.934800E+01 -4.334439E+01 -5.742644E+01 -1.658158E+02 -4.092600E+01 -8.423842E+01 -6.740126E+01 -2.279288E+02 -4.796500E+01 -1.154602E+02 -7.340327E+01 -2.701349E+02 -5.235900E+01 -1.374186E+02 -7.387392E+01 -2.740829E+02 -5.277400E+01 -1.398425E+02 -6.733428E+01 -2.274414E+02 -4.800100E+01 -1.156206E+02 -5.794970E+01 -1.685421E+02 -4.124600E+01 -8.540686E+01 -4.257013E+01 -9.092401E+01 -3.014500E+01 -4.566369E+01 -2.300274E+01 -2.659051E+01 -1.613400E+01 -1.307448E+01 +2.275147E+01 +2.604974E+01 +1.587800E+01 +1.271197E+01 +4.191959E+01 +8.846441E+01 +2.966500E+01 +4.430669E+01 +5.699815E+01 +1.637359E+02 +4.037600E+01 +8.219353E+01 +6.656851E+01 +2.228703E+02 +4.718000E+01 +1.119941E+02 +7.334215E+01 +2.701014E+02 +5.223500E+01 +1.370726E+02 +7.394394E+01 +2.748295E+02 +5.273400E+01 +1.397334E+02 +6.931604E+01 +2.406234E+02 +4.949000E+01 +1.226886E+02 +5.799672E+01 +1.687992E+02 +4.142300E+01 +8.612116E+01 +4.320102E+01 +9.402138E+01 +3.068300E+01 +4.749148E+01 +2.295257E+01 +2.657057E+01 +1.606200E+01 +1.301453E+01 tally 3: -1.564900E+01 -1.239852E+01 -1.086873E+00 -6.047264E-02 -2.821700E+01 -4.006730E+01 -1.855830E+00 -1.755984E-01 -3.946300E+01 -7.833997E+01 -2.523142E+00 -3.210725E-01 -4.622500E+01 -1.072588E+02 -2.919735E+00 -4.340292E-01 -5.033400E+01 -1.270010E+02 -3.243022E+00 -5.318534E-01 -5.082400E+01 -1.297502E+02 -3.313898E+00 -5.546608E-01 -4.623700E+01 -1.072944E+02 -2.887766E+00 -4.203084E-01 -3.975000E+01 -7.934279E+01 -2.567158E+00 -3.333121E-01 -2.903500E+01 -4.237270E+01 -1.852070E+00 -1.733821E-01 -1.557800E+01 -1.219084E+01 -9.951884E-01 -5.121758E-02 +1.528200E+01 +1.177982E+01 +1.040687E+00 +5.586386E-02 +2.857900E+01 +4.113603E+01 +1.871515E+00 +1.774689E-01 +3.888800E+01 +7.626262E+01 +2.534433E+00 +3.274088E-01 +4.541400E+01 +1.037867E+02 +2.926509E+00 +4.319780E-01 +5.034500E+01 +1.273517E+02 +3.215813E+00 +5.215716E-01 +5.076100E+01 +1.295218E+02 +3.194424E+00 +5.165993E-01 +4.768100E+01 +1.138949E+02 +3.058255E+00 +4.732131E-01 +3.995800E+01 +8.015691E+01 +2.454286E+00 +3.044948E-01 +2.957000E+01 +4.412743E+01 +1.938963E+00 +1.908501E-01 +1.544000E+01 +1.202869E+01 +1.038073E+00 +5.487827E-02 tally 4: -3.111000E+00 -4.872850E-01 +3.086000E+00 +4.780160E-01 0.000000E+00 0.000000E+00 -2.794000E+00 -3.972060E-01 -5.520000E+00 -1.535670E+00 +2.739000E+00 +3.790990E-01 +5.478000E+00 +1.505928E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.520000E+00 -1.535670E+00 -2.794000E+00 -3.972060E-01 -5.071000E+00 -1.305697E+00 -7.303000E+00 -2.685365E+00 +5.478000E+00 +1.505928E+00 +2.739000E+00 +3.790990E-01 +5.094000E+00 +1.310476E+00 +7.282000E+00 +2.669810E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.303000E+00 -2.685365E+00 -5.071000E+00 -1.305697E+00 -7.015000E+00 -2.471981E+00 -8.545000E+00 -3.670539E+00 +7.282000E+00 +2.669810E+00 +5.094000E+00 +1.310476E+00 +6.987000E+00 +2.461137E+00 +8.487000E+00 +3.624153E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.545000E+00 -3.670539E+00 -7.015000E+00 -2.471981E+00 -8.431000E+00 -3.570057E+00 -9.224000E+00 -4.268004E+00 +8.487000E+00 +3.624153E+00 +6.987000E+00 +2.461137E+00 +8.250000E+00 +3.421824E+00 +9.022000E+00 +4.088536E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.224000E+00 -4.268004E+00 -8.431000E+00 -3.570057E+00 -9.217000E+00 -4.259749E+00 -9.305000E+00 -4.340149E+00 +9.022000E+00 +4.088536E+00 +8.250000E+00 +3.421824E+00 +9.300000E+00 +4.344142E+00 +9.262000E+00 +4.308946E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.305000E+00 -4.340149E+00 -9.217000E+00 -4.259749E+00 -9.374000E+00 -4.415290E+00 -8.611000E+00 -3.718227E+00 +9.262000E+00 +4.308946E+00 +9.300000E+00 +4.344142E+00 +9.267000E+00 +4.310941E+00 +8.487000E+00 +3.613257E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.611000E+00 -3.718227E+00 -9.374000E+00 -4.415290E+00 -8.515000E+00 -3.639945E+00 -7.056000E+00 -2.501658E+00 +8.487000E+00 +3.613257E+00 +9.267000E+00 +4.310941E+00 +8.682000E+00 +3.778194E+00 +7.123000E+00 +2.544345E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.056000E+00 -2.501658E+00 -8.515000E+00 -3.639945E+00 -7.385000E+00 -2.737677E+00 -5.194000E+00 -1.356022E+00 +7.123000E+00 +2.544345E+00 +8.682000E+00 +3.778194E+00 +7.421000E+00 +2.773897E+00 +5.198000E+00 +1.369216E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.194000E+00 -1.356022E+00 -7.385000E+00 -2.737677E+00 -5.436000E+00 -1.481654E+00 -2.756000E+00 -3.843860E-01 +5.198000E+00 +1.369216E+00 +7.421000E+00 +2.773897E+00 +5.567000E+00 +1.561013E+00 +2.763000E+00 +3.882750E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.756000E+00 -3.843860E-01 -5.436000E+00 -1.481654E+00 -3.030000E+00 -4.643920E-01 +2.763000E+00 +3.882750E-01 +5.567000E+00 +1.561013E+00 +3.106000E+00 +4.853380E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,144 +345,144 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -1.564300E+01 -1.238861E+01 -2.090227E+00 -2.262627E-01 -2.821400E+01 -4.005826E+01 -3.870834E+00 -7.614623E-01 -3.945400E+01 -7.830326E+01 -5.290557E+00 -1.422339E+00 -4.621500E+01 -1.072116E+02 -6.144745E+00 -1.903309E+00 -5.032900E+01 -1.269756E+02 -6.867524E+00 -2.373593E+00 -5.081000E+01 -1.296784E+02 -6.456283E+00 -2.130767E+00 -4.623000E+01 -1.072613E+02 -5.931623E+00 -1.776451E+00 -3.974500E+01 -7.932288E+01 -5.339603E+00 -1.456812E+00 -2.902800E+01 -4.235232E+01 -4.102240E+00 -8.519551E-01 -1.557800E+01 -1.219084E+01 -2.137954E+00 -2.347770E-01 +1.527700E+01 +1.177204E+01 +2.285003E+00 +2.661382E-01 +2.857200E+01 +4.111506E+01 +4.126099E+00 +8.737996E-01 +3.887800E+01 +7.622094E+01 +5.121343E+00 +1.333837E+00 +4.540600E+01 +1.037492E+02 +6.160114E+00 +1.913665E+00 +5.033400E+01 +1.272949E+02 +6.859861E+00 +2.384476E+00 +5.075800E+01 +1.295055E+02 +6.929393E+00 +2.443364E+00 +4.767500E+01 +1.138658E+02 +6.385463E+00 +2.080293E+00 +3.995300E+01 +8.013651E+01 +5.620641E+00 +1.603844E+00 +2.956200E+01 +4.410395E+01 +3.952701E+00 +7.877105E-01 +1.543500E+01 +1.202080E+01 +2.203583E+00 +2.512936E-01 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.129918E+00 -1.148352E+00 -1.143137E+00 -1.145795E+00 -1.147285E+00 -1.148588E+00 -1.148151E+00 -1.162118E+00 -1.165380E+00 -1.162851E+00 -1.163379E+00 -1.166986E+00 -1.167838E+00 -1.171743E+00 -1.170398E+00 -1.169773E+00 +1.169107E+00 +1.173852E+00 +1.181921E+00 +1.187733E+00 +1.185766E+00 +1.177020E+00 +1.181200E+00 +1.180088E+00 +1.180676E+00 +1.174948E+00 +1.174167E+00 +1.174935E+00 +1.169912E+00 +1.169058E+00 +1.170366E+00 +1.169774E+00 cmfd entropy -3.224769E+00 -3.222795E+00 -3.221174E+00 -3.222164E+00 -3.221025E+00 -3.220967E+00 -3.223497E+00 -3.219213E+00 -3.221679E+00 -3.222084E+00 -3.222281E+00 -3.222540E+00 -3.224614E+00 -3.224193E+00 -3.224925E+00 -3.224367E+00 +3.207640E+00 +3.212075E+00 +3.215463E+00 +3.219545E+00 +3.225225E+00 +3.227103E+00 +3.229048E+00 +3.228263E+00 +3.229077E+00 +3.229932E+00 +3.229351E+00 +3.228195E+00 +3.228493E+00 +3.227823E+00 +3.225830E+00 +3.227270E+00 cmfd balance -3.90454E-03 -4.33180E-03 -3.77057E-03 -3.16391E-03 -3.11765E-03 -2.59886E-03 -2.81060E-03 -3.25473E-03 -2.68544E-03 -2.01716E-03 -1.89350E-03 -1.79159E-03 -1.51353E-03 -1.48514E-03 -1.50207E-03 -1.44045E-03 +4.88208E-03 +4.63702E-03 +3.41158E-03 +2.99755E-03 +2.78360E-03 +3.31542E-03 +2.64344E-03 +2.04609E-03 +1.84340E-03 +1.65450E-03 +1.70816E-03 +1.69952E-03 +1.51417E-03 +1.32738E-03 +1.41435E-03 +1.01462E-03 cmfd dominance ratio -5.539E-01 -5.522E-01 -5.491E-01 -5.511E-01 -5.506E-01 -5.523E-01 -5.523E-01 +5.467E-01 +5.468E-01 +5.448E-01 +5.457E-01 +5.457E-01 +5.485E-01 +5.500E-01 +5.497E-01 +5.495E-01 +5.499E-01 +5.502E-01 +5.485E-01 +5.492E-01 +5.483E-01 5.473E-01 -5.478E-01 -5.461E-01 -5.462E-01 -5.459E-01 -5.475E-01 -5.463E-01 5.466E-01 -5.469E-01 cmfd openmc source comparison -9.875240E-03 -1.119358E-02 -8.513903E-03 -7.728971E-03 -5.993771E-03 -5.837301E-03 -4.861789E-03 -5.624038E-03 -4.297229E-03 -4.029732E-03 -3.669197E-03 -3.598834E-03 -3.023310E-03 -3.347346E-03 -2.943658E-03 -2.764986E-03 +9.587418E-03 +7.785087E-03 +6.798967E-03 +5.947641E-03 +4.980801E-03 +4.272665E-03 +4.073759E-03 +4.305612E-03 +3.572759E-03 +3.785830E-03 +3.766828E-03 +3.495462E-03 +3.017281E-03 +2.857633E-03 +2.858606E-03 +2.449010E-03 cmfd source -4.561921E-02 -7.896381E-02 -1.084687E-01 -1.264057E-01 -1.408942E-01 -1.438180E-01 -1.247333E-01 -1.100896E-01 -7.897187E-02 -4.203556E-02 +4.390084E-02 +7.966902E-02 +1.087889E-01 +1.263915E-01 +1.394331E-01 +1.383156E-01 +1.319970E-01 +1.051339E-01 +8.248244E-02 +4.388774E-02 diff --git a/tests/regression_tests/cmfd_restart/results_true.dat b/tests/regression_tests/cmfd_restart/results_true.dat index f5f22d9acd..1ef9624d4c 100644 --- a/tests/regression_tests/cmfd_restart/results_true.dat +++ b/tests/regression_tests/cmfd_restart/results_true.dat @@ -1,117 +1,117 @@ k-combined: -1.164262E+00 9.207592E-03 +1.181723E+00 9.944883E-03 tally 1: -1.156972E+01 -1.339924E+01 -2.136306E+01 -4.567185E+01 -2.859527E+01 -8.195821E+01 -3.470754E+01 -1.207851E+02 -3.766403E+01 -1.422263E+02 -3.778821E+01 -1.432660E+02 -3.573197E+01 -1.278854E+02 -2.849979E+01 -8.135515E+01 -2.073803E+01 -4.303374E+01 -1.112117E+01 -1.242944E+01 +1.169899E+01 +1.373251E+01 +2.142380E+01 +4.605511E+01 +2.968085E+01 +8.838716E+01 +3.561418E+01 +1.271206E+02 +3.777783E+01 +1.428817E+02 +3.805832E+01 +1.450213E+02 +3.439836E+01 +1.184892E+02 +2.852438E+01 +8.161896E+01 +2.088423E+01 +4.376204E+01 +1.076670E+01 +1.168108E+01 tally 2: -2.388054E+01 -2.875255E+01 -1.667791E+01 -1.403426E+01 -4.224771E+01 -8.942109E+01 -2.993088E+01 -4.490335E+01 -5.689839E+01 -1.625557E+02 -4.043633E+01 -8.212299E+01 -6.764024E+01 -2.297126E+02 -4.807902E+01 -1.161468E+02 -7.314835E+01 -2.684645E+02 -5.203584E+01 -1.359261E+02 -7.375727E+01 -2.733105E+02 -5.252944E+01 -1.386205E+02 -6.909571E+01 -2.397721E+02 -4.922548E+01 -1.217465E+02 -5.685978E+01 -1.621746E+02 -4.051938E+01 -8.237277E+01 -4.185562E+01 -8.784067E+01 -2.983570E+01 -4.467414E+01 -2.238373E+01 -2.520356E+01 -1.566758E+01 -1.234103E+01 +2.321241E+01 +2.702156E+01 +1.620912E+01 +1.317752E+01 +4.197404E+01 +8.845008E+01 +2.982666E+01 +4.469221E+01 +5.810089E+01 +1.695857E+02 +4.134123E+01 +8.588866E+01 +6.982488E+01 +2.447068E+02 +4.966939E+01 +1.238763E+02 +7.428421E+01 +2.767613E+02 +5.287955E+01 +1.403163E+02 +7.447402E+01 +2.785012E+02 +5.324628E+01 +1.423393E+02 +6.895164E+01 +2.381937E+02 +4.916366E+01 +1.211701E+02 +5.679253E+01 +1.617881E+02 +4.043125E+01 +8.204061E+01 +4.218618E+01 +8.933666E+01 +2.978592E+01 +4.456592E+01 +2.196426E+01 +2.435867E+01 +1.525576E+01 +1.175879E+01 tally 3: -1.609520E+01 -1.307542E+01 -1.033429E+00 -5.510889E-02 -2.877073E+01 -4.149542E+01 -1.964219E+00 -1.954692E-01 -3.896816E+01 -7.629752E+01 -2.484053E+00 -3.103733E-01 -4.634285E+01 -1.079367E+02 -2.974750E+00 -4.468223E-01 -5.007964E+01 -1.259202E+02 -3.181802E+00 -5.103621E-01 -5.058915E+01 -1.286193E+02 -3.249442E+00 -5.337712E-01 -4.744464E+01 -1.131026E+02 -3.067644E+00 -4.736335E-01 -3.900632E+01 -7.634433E+01 -2.443552E+00 -3.028060E-01 -2.874166E+01 -4.146375E+01 -1.810421E+00 -1.671667E-01 -1.509222E+01 -1.145579E+01 -1.014919E+00 -5.391053E-02 +1.563788E+01 +1.226528E+01 +1.053289E+00 +5.666942E-02 +2.870755E+01 +4.139654E+01 +1.838017E+00 +1.710528E-01 +3.978616E+01 +7.955764E+01 +2.560657E+00 +3.334449E-01 +4.780385E+01 +1.147770E+02 +3.139243E+00 +4.967628E-01 +5.106650E+01 +1.308704E+02 +3.170056E+00 +5.078920E-01 +5.123992E+01 +1.318586E+02 +3.211706E+00 +5.205979E-01 +4.729862E+01 +1.121695E+02 +3.068662E+00 +4.749488E-01 +3.898816E+01 +7.630564E+01 +2.516911E+00 +3.199696E-01 +2.865357E+01 +4.125742E+01 +1.852314E+00 +1.741116E-01 +1.467340E+01 +1.088460E+01 +9.268633E-01 +4.450662E-02 tally 4: -3.148231E+00 -4.974555E-01 +3.029754E+00 +4.613561E-01 0.000000E+00 0.000000E+00 -2.805439E+00 -3.982239E-01 -5.574031E+00 -1.561105E+00 +2.832501E+00 +4.049252E-01 +5.517243E+00 +1.527794E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -128,14 +128,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.574031E+00 -1.561105E+00 -2.805439E+00 -3.982239E-01 -5.171038E+00 -1.344877E+00 -7.372031E+00 -2.725420E+00 +5.517243E+00 +1.527794E+00 +2.832501E+00 +4.049252E-01 +5.117178E+00 +1.316972E+00 +7.333303E+00 +2.701677E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -152,14 +152,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.372031E+00 -2.725420E+00 -5.171038E+00 -1.344877E+00 -6.946847E+00 -2.424850E+00 -8.496610E+00 -3.627542E+00 +7.333303E+00 +2.701677E+00 +5.117178E+00 +1.316972E+00 +7.248464E+00 +2.641591E+00 +8.817788E+00 +3.905530E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -176,14 +176,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.496610E+00 -3.627542E+00 -6.946847E+00 -2.424850E+00 -8.479501E+00 -3.607280E+00 -9.261869E+00 -4.305912E+00 +8.817788E+00 +3.905530E+00 +7.248464E+00 +2.641591E+00 +8.646465E+00 +3.749847E+00 +9.460948E+00 +4.495388E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -200,14 +200,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.261869E+00 -4.305912E+00 -8.479501E+00 -3.607280E+00 -9.232858E+00 -4.278432E+00 -9.306384E+00 -4.348594E+00 +9.460948E+00 +4.495388E+00 +8.646465E+00 +3.749847E+00 +9.379341E+00 +4.415049E+00 +9.278640E+00 +4.320720E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -224,14 +224,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -9.306384E+00 -4.348594E+00 -9.232858E+00 -4.278432E+00 -9.299764E+00 -4.347828E+00 -8.511976E+00 -3.639893E+00 +9.278640E+00 +4.320720E+00 +9.379341E+00 +4.415049E+00 +9.465746E+00 +4.498591E+00 +8.656146E+00 +3.760545E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -248,14 +248,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -8.511976E+00 -3.639893E+00 -9.299764E+00 -4.347828E+00 -8.726086E+00 -3.819567E+00 -7.147277E+00 -2.562747E+00 +8.656146E+00 +3.760545E+00 +9.465746E+00 +4.498591E+00 +8.589782E+00 +3.700308E+00 +6.996002E+00 +2.456935E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -272,14 +272,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -7.147277E+00 -2.562747E+00 -8.726086E+00 -3.819567E+00 -7.218790E+00 -2.612243E+00 -5.018287E+00 -1.263077E+00 +6.996002E+00 +2.456935E+00 +8.589782E+00 +3.700308E+00 +7.352050E+00 +2.714808E+00 +5.105164E+00 +1.312559E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -296,14 +296,14 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -5.018287E+00 -1.263077E+00 -7.218790E+00 -2.612243E+00 -5.443494E+00 -1.487018E+00 -2.732334E+00 -3.773047E-01 +5.105164E+00 +1.312559E+00 +7.352050E+00 +2.714808E+00 +5.442756E+00 +1.486776E+00 +2.697305E+00 +3.675580E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -320,12 +320,12 @@ tally 4: 0.000000E+00 0.000000E+00 0.000000E+00 -2.732334E+00 -3.773047E-01 -5.443494E+00 -1.487018E+00 -3.044773E+00 -4.655756E-01 +2.697305E+00 +3.675580E-01 +5.442756E+00 +1.486776E+00 +3.017025E+00 +4.571443E-01 0.000000E+00 0.000000E+00 0.000000E+00 @@ -345,144 +345,144 @@ tally 4: 0.000000E+00 0.000000E+00 tally 5: -1.609029E+01 -1.306718E+01 -2.230601E+00 -2.559496E-01 -2.876780E+01 -4.148686E+01 -3.835952E+00 -7.456562E-01 -3.895738E+01 -7.625344E+01 -4.841024E+00 -1.197335E+00 -4.633595E+01 -1.079043E+02 -6.236821E+00 -1.963311E+00 -5.007472E+01 -1.258967E+02 -6.749745E+00 -2.297130E+00 -5.058336E+01 -1.285894E+02 -6.727612E+00 -2.315656E+00 -4.743869E+01 -1.130735E+02 -6.338193E+00 -2.042159E+00 -3.899838E+01 -7.631289E+01 -5.187573E+00 -1.359733E+00 -2.873434E+01 -4.144233E+01 -3.815610E+00 -7.367619E-01 -1.509020E+01 -1.145268E+01 -2.125767E+00 -2.341894E-01 +1.563588E+01 +1.226217E+01 +2.209027E+00 +2.507131E-01 +2.870034E+01 +4.137550E+01 +3.726620E+00 +7.021948E-01 +3.977762E+01 +7.952285E+01 +5.304975E+00 +1.427333E+00 +4.779747E+01 +1.147456E+02 +6.528302E+00 +2.151715E+00 +5.105366E+01 +1.308037E+02 +6.986782E+00 +2.467487E+00 +5.123380E+01 +1.318264E+02 +6.845633E+00 +2.383542E+00 +4.729296E+01 +1.121433E+02 +6.252695E+00 +1.977351E+00 +3.898236E+01 +7.628315E+01 +5.461495E+00 +1.528579E+00 +2.864576E+01 +4.123538E+01 +3.857301E+00 +7.581323E-01 +1.467047E+01 +1.088031E+01 +2.277024E+00 +2.679801E-01 cmfd indices 1.000000E+01 1.000000E+00 1.000000E+00 1.000000E+00 k cmfd -1.129918E+00 -1.143848E+00 -1.147976E+00 -1.151534E+00 -1.152378E+00 -1.148219E+00 -1.150402E+00 -1.154647E+00 -1.156159E+00 -1.160048E+00 -1.167441E+00 -1.168163E+00 -1.168629E+00 -1.164120E+00 -1.165051E+00 -1.169177E+00 +1.169107E+00 +1.175079E+00 +1.173912E+00 +1.175368E+00 +1.174026E+00 +1.181745E+00 +1.182261E+00 +1.183559E+00 +1.178691E+00 +1.179222E+00 +1.179017E+00 +1.172979E+00 +1.175043E+00 +1.173458E+00 +1.174152E+00 +1.171451E+00 cmfd entropy -3.224769E+00 -3.225945E+00 -3.227421E+00 -3.226174E+00 -3.224429E+00 -3.227049E+00 -3.230710E+00 -3.230315E+00 -3.226825E+00 -3.226655E+00 -3.226588E+00 -3.224155E+00 -3.223246E+00 -3.222640E+00 -3.223920E+00 -3.222838E+00 +3.207640E+00 +3.210547E+00 +3.212218E+00 +3.209573E+00 +3.211619E+00 +3.212126E+00 +3.213163E+00 +3.214288E+00 +3.215737E+00 +3.213677E+00 +3.214925E+00 +3.215612E+00 +3.216708E+00 +3.221454E+00 +3.219048E+00 +3.218387E+00 cmfd balance -3.90454E-03 -4.08089E-03 -3.46511E-03 -4.09535E-03 -2.62009E-03 -2.23559E-03 -2.54033E-03 -2.12799E-03 -2.25864E-03 -1.85766E-03 -1.49916E-03 -1.63471E-03 -1.48377E-03 -1.59800E-03 -1.37354E-03 -1.32853E-03 +4.88208E-03 +4.75139E-03 +3.15783E-03 +3.67091E-03 +2.99797E-03 +2.91060E-03 +2.06576E-03 +1.83482E-03 +1.56292E-03 +1.58659E-03 +2.32986E-03 +1.47376E-03 +1.46673E-03 +1.22627E-03 +1.31963E-03 +1.26456E-03 cmfd dominance ratio -5.539E-01 -5.537E-01 -5.536E-01 -5.515E-01 -5.512E-01 -5.514E-01 -5.518E-01 -5.507E-01 -5.500E-01 -5.497E-01 -5.477E-01 -5.461E-01 -5.444E-01 -5.445E-01 -5.454E-01 +5.467E-01 +5.453E-01 +5.458E-01 +5.436E-01 +5.442E-01 +5.406E-01 +5.401E-01 +5.413E-01 +4.995E-01 +5.396E-01 +5.409E-01 +5.414E-01 +5.423E-01 +5.456E-01 +5.442E-01 5.441E-01 cmfd openmc source comparison -9.875240E-03 -1.106163E-02 -9.847628E-03 -6.065921E-03 -5.772039E-03 -4.615656E-03 -4.244331E-03 -3.694299E-03 -3.545814E-03 -3.213063E-03 -3.467537E-03 -3.383489E-03 -3.697591E-03 -3.937358E-03 -3.369124E-03 -3.190359E-03 +9.587418E-03 +8.150978E-03 +6.677661E-03 +6.334727E-03 +5.153692E-03 +5.082964E-03 +4.633153E-03 +4.037383E-03 +3.528742E-03 +4.559089E-03 +3.517370E-03 +3.306117E-03 +2.913809E-03 +1.906045E-03 +1.932794E-03 +1.711341E-03 cmfd source -4.360494E-02 -8.397599E-02 -1.074181E-01 -1.294531E-01 -1.385611E-01 -1.407934E-01 -1.325191E-01 -1.044311E-01 -7.660359E-02 -4.263941E-02 +4.496492E-02 +7.869674E-02 +1.100280E-01 +1.354045E-01 +1.363339E-01 +1.380533E-01 +1.314512E-01 +1.077480E-01 +7.847306E-02 +3.884630E-02 diff --git a/tests/regression_tests/statepoint_batch/__init__.py b/tests/regression_tests/collision_track/__init__.py similarity index 100% rename from tests/regression_tests/statepoint_batch/__init__.py rename to tests/regression_tests/collision_track/__init__.py diff --git a/tests/regression_tests/collision_track/case_1_Reactions/inputs_true.dat b/tests/regression_tests/collision_track/case_1_Reactions/inputs_true.dat new file mode 100644 index 0000000000..7533616c05 --- /dev/null +++ b/tests/regression_tests/collision_track/case_1_Reactions/inputs_true.dat @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + (n,fission) 101 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_1_Reactions/results_true.dat b/tests/regression_tests/collision_track/case_1_Reactions/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_1_Reactions/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_2_Cell_ID/inputs_true.dat b/tests/regression_tests/collision_track/case_2_Cell_ID/inputs_true.dat new file mode 100644 index 0000000000..55fb835de0 --- /dev/null +++ b/tests/regression_tests/collision_track/case_2_Cell_ID/inputs_true.dat @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 22 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_2_Cell_ID/results_true.dat b/tests/regression_tests/collision_track/case_2_Cell_ID/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_2_Cell_ID/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_3_Material_ID/inputs_true.dat b/tests/regression_tests/collision_track/case_3_Material_ID/inputs_true.dat new file mode 100644 index 0000000000..61890414ba --- /dev/null +++ b/tests/regression_tests/collision_track/case_3_Material_ID/inputs_true.dat @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 1 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_3_Material_ID/results_true.dat b/tests/regression_tests/collision_track/case_3_Material_ID/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_3_Material_ID/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_4_Nuclide_ID/inputs_true.dat b/tests/regression_tests/collision_track/case_4_Nuclide_ID/inputs_true.dat new file mode 100644 index 0000000000..8960dde5cb --- /dev/null +++ b/tests/regression_tests/collision_track/case_4_Nuclide_ID/inputs_true.dat @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + O16 U235 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_4_Nuclide_ID/results_true.dat b/tests/regression_tests/collision_track/case_4_Nuclide_ID/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_4_Nuclide_ID/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_5_Universe_ID/inputs_true.dat b/tests/regression_tests/collision_track/case_5_Universe_ID/inputs_true.dat new file mode 100644 index 0000000000..8c0d7aa8ee --- /dev/null +++ b/tests/regression_tests/collision_track/case_5_Universe_ID/inputs_true.dat @@ -0,0 +1,59 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 22 + 77 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_5_Universe_ID/results_true.dat b/tests/regression_tests/collision_track/case_5_Universe_ID/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_5_Universe_ID/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/inputs_true.dat b/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/inputs_true.dat new file mode 100644 index 0000000000..5173dc35cf --- /dev/null +++ b/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/inputs_true.dat @@ -0,0 +1,58 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 550000.0 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/results_true.dat b/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_6_deposited_energy_threshold/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_7_all_parameters_used_together/inputs_true.dat b/tests/regression_tests/collision_track/case_7_all_parameters_used_together/inputs_true.dat new file mode 100644 index 0000000000..005d9feb27 --- /dev/null +++ b/tests/regression_tests/collision_track/case_7_all_parameters_used_together/inputs_true.dat @@ -0,0 +1,63 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 22 33 + elastic 18 (n,disappear) + 77 + 1 11 + U238 U235 H1 U234 + 100000.0 + 300 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_7_all_parameters_used_together/results_true.dat b/tests/regression_tests/collision_track/case_7_all_parameters_used_together/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_7_all_parameters_used_together/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/case_8_2threads/inputs_true.dat b/tests/regression_tests/collision_track/case_8_2threads/inputs_true.dat new file mode 100644 index 0000000000..514932c1a6 --- /dev/null +++ b/tests/regression_tests/collision_track/case_8_2threads/inputs_true.dat @@ -0,0 +1,57 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 5 + 1 + + + -2.0 -2.0 -2.0 2.0 2.0 2.0 + + + true + + + + 200 + + 1 + + diff --git a/tests/regression_tests/collision_track/case_8_2threads/results_true.dat b/tests/regression_tests/collision_track/case_8_2threads/results_true.dat new file mode 100644 index 0000000000..d4d1d1e5ad --- /dev/null +++ b/tests/regression_tests/collision_track/case_8_2threads/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/collision_track/test.py b/tests/regression_tests/collision_track/test.py new file mode 100644 index 0000000000..00e1e3de41 --- /dev/null +++ b/tests/regression_tests/collision_track/test.py @@ -0,0 +1,255 @@ +"""Test the 'collision_track' setting. + +Results +------- + +All results are generated using only 1 MPI process. + +All results are generated using 1 thread except for "test_consistency_low_realization_number". +This specific test verifies that when the number of realization (i.e., point being candidate +to be stored) is lower than the capacity, results are reproducible even with multiple +threads (i.e., there is no potential thread competition that would produce different +results in that case). + +All results are generated using the history-based mode except for cases e01 to e03. + +All results are visually verified using the '_visualize.py' script in the regression test folder. + +OpenMC models +------------- + +Four OpenMC models with CSG-only geometries are used to cover the transmission, vacuum, +reflective and periodic Boundary Conditions (BC): + +- model_1: cylindrical core in 2 boxes (vacuum and transmission BC), + +# Test cases for simulation parameters using CSG-only geometries +# ============================================================ +# Each test case is defined by a combination of folder name, model name, and specific parameters. +# Below is a summary of the parameters used in the test cases: +# +# - max_collisions: Maximum number of particles to track in the simulation. +# - reactions: List of MT numbers (reaction types- 2 for scattering, 18 for fission, 101 for absorbtion). +# - cell_ids: IDs of specific cells in the model. +# - mat_ids: Material IDs for filtering particles. +# - nuclides: Nuclides for filtering particles. +# - univ_ids: Universe IDs for filtering particles. +# - E_threshold: Energy threshold for filtering particles (optional). +# +# The test cases are designed to validate the behavior of the simulation under various configurations. + +*: BC stands for Boundary Conditions, T for Transmission, R for Reflective, and V for Vacuum. + +An additional case, called 'case-a01', is used to check that the results are comparable when +the number of threads is set to 2 if the number of realization is lower than the capacity. + + +*: BC stands for Boundary Conditions, T for Transmission, and V for Vacuum. + +Notes: + +- The test cases list is non-exhaustive compared to the number of possible combinations. + Test cases have been selected based on use and internal code logic. + + + +TODO: + +- Test with a lattice. + +""" + +import os + +import openmc +import openmc.lib +import pytest + +from tests.testing_harness import CollisionTrackTestHarness +from tests.regression_tests import config + + +@pytest.fixture(scope="function") +def two_threads(monkeypatch): + """Set the number of OMP threads to 2 for the test.""" + monkeypatch.setenv("OMP_NUM_THREADS", "2") + + +@pytest.fixture(scope="function") +def single_process(monkeypatch): + """Set the number of MPI process to 1 for the test.""" + monkeypatch.setitem(config, "mpi_np", "1") + + +@pytest.fixture(scope="module") +def model_1(): + """Cylindrical core contained in a first box which is contained in a larger box. + A lower universe is used to describe the interior of the first box which + contains the core and its surrounding space. + + """ + openmc.reset_auto_ids() + model = openmc.Model() + + # ============================================================================= + # Materials + # ============================================================================= + + fuel = openmc.Material(material_id=1) + fuel.add_nuclide("U234", 0.0004524) + fuel.add_nuclide("U235", 0.0506068) + fuel.add_nuclide("U238", 0.9487090) + fuel.add_nuclide("U236", 0.0002318) + fuel.add_nuclide("O16", 2.0) + fuel.set_density("g/cm3", 11.0) + + water = openmc.Material(material_id=11) + water.add_nuclide("H1", 2.0) + water.add_nuclide("O16", 1.0) + water.set_density("g/cm3", 1.0) + + # ============================================================================= + # Geometry + # ============================================================================= + + # ----------------------------------------------------------------------------- + # Cylindrical core + # ----------------------------------------------------------------------------- + + # Parameters + core_radius = 2.0 + core_height = 4.0 + + # Surfaces + core_cylinder = openmc.ZCylinder(r=core_radius) + core_lower_plane = openmc.ZPlane(-core_height / 2.0) + core_upper_plane = openmc.ZPlane(core_height / 2.0) + + # Region + core_region = -core_cylinder & +core_lower_plane & -core_upper_plane + + # Cells + core = openmc.Cell(fill=fuel, region=core_region, cell_id=22) + outside_core_region = +core_cylinder | -core_lower_plane | +core_upper_plane + outside_core = openmc.Cell( + fill=water, region=outside_core_region, cell_id=33) + + # Universe + inside_box1_universe = openmc.Universe( + cells=[core, outside_core], universe_id=77) + + # ----------------------------------------------------------------------------- + # Box 1 + # ----------------------------------------------------------------------------- + + # Parameters + box1_size = 6.0 + + # Surfaces + box1_rpp = openmc.model.RectangularParallelepiped( + -box1_size / 2.0, box1_size / 2.0, + -box1_size / 2.0, box1_size / 2.0, + -box1_size / 2.0, box1_size / 2.0, + ) + + # Cell + box1 = openmc.Cell(fill=inside_box1_universe, region=-box1_rpp, cell_id=5) + + # ----------------------------------------------------------------------------- + # Box 2 + # ----------------------------------------------------------------------------- + + # Parameters + box2_size = 8 + + # Surfaces + box2_rpp = openmc.model.RectangularParallelepiped( + -box2_size / 2.0, box2_size / 2.0, + -box2_size / 2.0, box2_size / 2.0, + -box2_size / 2.0, box2_size / 2.0, + boundary_type="vacuum" + ) + + # Cell + box2 = openmc.Cell(fill=water, region=-box2_rpp & +box1_rpp, cell_id=8) + + # Register geometry + model.geometry = openmc.Geometry([box1, box2]) + + # ============================================================================= + # Settings + # ============================================================================= + + model.settings = openmc.Settings() + model.settings.particles = 100 + model.settings.batches = 5 + model.settings.inactive = 1 + model.settings.seed = 1 + + bounds = [ + -core_radius, + -core_radius, + -core_height / 2.0, + core_radius, + core_radius, + core_height / 2.0, + ] + distribution = openmc.stats.Box(bounds[:3], bounds[3:]) + model.settings.source = openmc.IndependentSource( + space=distribution, constraints={'fissionable': True}) + + return model + + +@pytest.mark.parametrize( + "folder, model_name, parameter", + [("case_1_Reactions", "model_1", {"max_collisions": 300, "reactions": ["(n,fission)", 101]}), + ("case_2_Cell_ID", "model_1", { + "max_collisions": 300, "cell_ids": [22]}), + ("case_3_Material_ID", "model_1", { + "max_collisions": 300, "material_ids": [1]}), + ("case_4_Nuclide_ID", "model_1", { + "max_collisions": 300, "nuclides": ["O16", "U235"]}), + ("case_5_Universe_ID", "model_1", { + "max_collisions": 300, "cell_ids": [22], "universe_ids": [77]}), + ("case_6_deposited_energy_threshold", "model_1", { + "max_collisions": 300, "deposited_E_threshold": 5.5e5}), + ("case_7_all_parameters_used_together", "model_1", { + "max_collisions": 300, + "reactions": ["elastic", 18, "(n,disappear)"], + "material_ids": [1, 11], + "universe_ids": [77], + "nuclides": ["U238", "U235", "H1", "U234"], + "cell_ids": [22, 33], + "deposited_E_threshold": 1e5}) + ], +) +def test_collision_track_several_cases( + folder, model_name, parameter, request +): + # Since for these tests the actual number of collisions recorded is < max_collisions, + # we can run them with 1 or 2 threads, and in history or event mode. + model = request.getfixturevalue(model_name) + model.settings.collision_track = parameter + harness = CollisionTrackTestHarness( + "statepoint.5.h5", model=model, workdir=folder + ) + harness.main() + + +@pytest.mark.skipif(config["event"], reason="Results from history-based mode.") +def test_collision_track_2threads(model_1, two_threads, single_process): + # This test checks that the `max_collisions` setting is honored: + # no collisions beyond the specified limit should be recorded. + # + # For the result to be reproducible, the number of threads and + # the transport mode (history vs. event) must remain fixed. + assert os.environ["OMP_NUM_THREADS"] == "2" + assert config["mpi_np"] == "1" + model_1.settings.collision_track = { + "max_collisions": 200 + } + harness = CollisionTrackTestHarness( + "statepoint.5.h5", model=model_1, workdir="case_8_2threads" + ) + harness.main() diff --git a/tests/regression_tests/complex_cell/results_true.dat b/tests/regression_tests/complex_cell/results_true.dat index 3ce3d7cbc7..ddedb07ff0 100644 --- a/tests/regression_tests/complex_cell/results_true.dat +++ b/tests/regression_tests/complex_cell/results_true.dat @@ -1,11 +1,11 @@ k-combined: -2.564169E-01 4.095378E-03 +2.603220E-01 1.429366E-03 tally 1: -2.607144E+00 -1.360414E+00 -2.681079E+00 -1.439354E+00 -9.627534E-01 -1.855496E-01 -1.123751E-01 +2.624819E+00 +1.378200E+00 +2.730035E+00 +1.492361E+00 +1.013707E+00 +2.055807E-01 +1.123257E-01 2.530233E-03 diff --git a/tests/regression_tests/confidence_intervals/results_true.dat b/tests/regression_tests/confidence_intervals/results_true.dat index 6a906d07e7..8ca2566249 100644 --- a/tests/regression_tests/confidence_intervals/results_true.dat +++ b/tests/regression_tests/confidence_intervals/results_true.dat @@ -1,5 +1,5 @@ k-combined: -2.759923E-01 6.988588E-03 +2.850178E-01 9.646334E-03 tally 1: -6.167984E+01 -4.772717E+02 +6.234169E+01 +4.884167E+02 diff --git a/tests/regression_tests/cpp_driver/driver.cpp b/tests/regression_tests/cpp_driver/driver.cpp index 48ed7f3171..a99c97b64e 100644 --- a/tests/regression_tests/cpp_driver/driver.cpp +++ b/tests/regression_tests/cpp_driver/driver.cpp @@ -15,14 +15,16 @@ using namespace openmc; -int main(int argc, char** argv) { +int main(int argc, char** argv) +{ #ifdef OPENMC_MPI MPI_Comm world {MPI_COMM_WORLD}; int err = openmc_init(argc, argv, &world); #else int err = openmc_init(argc, argv, nullptr); #endif - if (err) fatal_error(openmc_err_msg); + if (err) + fatal_error(openmc_err_msg); // create a new cell filter auto cell_filter = Filter::create(); @@ -30,7 +32,7 @@ int main(int argc, char** argv) { // add all cells to the cell filter std::vector cell_indices; for (auto& entry : openmc::model::cell_map) { - cell_indices.push_back(entry.second); + cell_indices.push_back(entry.second); } // enable distribcells offsets for all cells prepare_distribcell(&cell_indices); @@ -39,7 +41,6 @@ int main(int argc, char** argv) { std::sort(cell_indices.begin(), cell_indices.end()); cell_filter->set_cells(cell_indices); - // create a new tally auto tally = Tally::create(); std::vector filters = {cell_filter}; @@ -60,14 +61,19 @@ int main(int argc, char** argv) { } } - // set a higher temperature for only one of the lattice cells (ID is 4 in the model) + // set a higher temperature for only one of the lattice cells (ID is 4 in the + // model) model::cells[model::cell_map[4]]->set_temperature(400.0, 3, true); + // set the density of another lattice cell to 2 + model::cells[model::cell_map[4]]->set_density(2.0, 2, true); + // the summary file will be used to check that // temperatures were set correctly so clear // error output can be provided #ifdef OPENMC_MPI - if (openmc::mpi::master) openmc::write_summary(); + if (openmc::mpi::master) + openmc::write_summary(); #else openmc::write_summary(); #endif diff --git a/tests/regression_tests/cpp_driver/results_true.dat b/tests/regression_tests/cpp_driver/results_true.dat index c2b0b8d6f3..09f188db6b 100644 --- a/tests/regression_tests/cpp_driver/results_true.dat +++ b/tests/regression_tests/cpp_driver/results_true.dat @@ -1,13 +1,13 @@ k-combined: -1.933305E+00 1.300360E-02 +1.874924E+00 2.180236E-02 tally 1: -9.552846E+01 -1.019358E+03 -2.887973E+01 -9.308509E+01 -9.732441E+01 -1.059022E+03 -2.217326E+02 -5.486892E+03 -2.217326E+02 -5.486892E+03 +9.484447E+01 +1.002269E+03 +2.746252E+01 +8.406603E+01 +9.833099E+01 +1.076376E+03 +2.206380E+02 +5.417609E+03 +2.206380E+02 +5.417609E+03 diff --git a/tests/regression_tests/dagmc/external/main.cpp b/tests/regression_tests/dagmc/external/main.cpp index 3765cf79ae..e78ab03fa2 100644 --- a/tests/regression_tests/dagmc/external/main.cpp +++ b/tests/regression_tests/dagmc/external/main.cpp @@ -100,6 +100,9 @@ int main(int argc, char* argv[]) } } + // Finalize cell densities + openmc::finalize_cell_densities(); + // Run OpenMC openmc_err = openmc_run(); if (openmc_err) diff --git a/tests/regression_tests/dagmc/external/results_true.dat b/tests/regression_tests/dagmc/external/results_true.dat index cda6569378..9a6b481b7f 100644 --- a/tests/regression_tests/dagmc/external/results_true.dat +++ b/tests/regression_tests/dagmc/external/results_true.dat @@ -1,5 +1,5 @@ k-combined: -9.118190E-01 3.615552E-02 +1.083415E+00 5.991738E-02 tally 1: -8.430103E+00 -1.442878E+01 +8.862860E+00 +1.602117E+01 diff --git a/tests/regression_tests/dagmc/legacy/results_true.dat b/tests/regression_tests/dagmc/legacy/results_true.dat index cda6569378..9a6b481b7f 100644 --- a/tests/regression_tests/dagmc/legacy/results_true.dat +++ b/tests/regression_tests/dagmc/legacy/results_true.dat @@ -1,5 +1,5 @@ k-combined: -9.118190E-01 3.615552E-02 +1.083415E+00 5.991738E-02 tally 1: -8.430103E+00 -1.442878E+01 +8.862860E+00 +1.602117E+01 diff --git a/tests/regression_tests/dagmc/refl/results_true.dat b/tests/regression_tests/dagmc/refl/results_true.dat index 533c62a902..b49a4a7a49 100644 --- a/tests/regression_tests/dagmc/refl/results_true.dat +++ b/tests/regression_tests/dagmc/refl/results_true.dat @@ -1,5 +1,5 @@ k-combined: -2.035173E+00 3.967029E-02 +2.047107E+00 8.605767E-02 tally 1: -1.064492E+01 -2.301019E+01 +1.145034E+01 +2.636875E+01 diff --git a/tests/regression_tests/dagmc/universes/inputs_true.dat b/tests/regression_tests/dagmc/universes/inputs_true.dat index 2fa79d831e..be1a17383c 100644 --- a/tests/regression_tests/dagmc/universes/inputs_true.dat +++ b/tests/regression_tests/dagmc/universes/inputs_true.dat @@ -48,6 +48,14 @@ 100 10 5 + + + -10.0 -10.0 -24.0 10.0 10.0 24.0 + + + true + + false diff --git a/tests/regression_tests/dagmc/universes/results_true.dat b/tests/regression_tests/dagmc/universes/results_true.dat index 76cbc9db0c..aacb7d1ab5 100644 --- a/tests/regression_tests/dagmc/universes/results_true.dat +++ b/tests/regression_tests/dagmc/universes/results_true.dat @@ -1,13 +1,13 @@ k-combined: -9.887663E-01 1.510336E-02 +9.719586E-01 3.630894E-02 tally 1: -4.340758E+00 -4.265459E+00 -4.712319E+00 -4.654778E+00 -4.151897E+00 -3.588090E+00 -2.965925E+00 -1.852746E+00 +4.463288E+00 +4.136647E+00 +4.769631E+00 +4.622840E+00 +4.315273E+00 +3.871129E+00 +4.091804E+00 +3.582192E+00 0.000000E+00 0.000000E+00 diff --git a/tests/regression_tests/dagmc/universes/test.py b/tests/regression_tests/dagmc/universes/test.py index 057a7b0d47..d68c6b11cf 100644 --- a/tests/regression_tests/dagmc/universes/test.py +++ b/tests/regression_tests/dagmc/universes/test.py @@ -11,81 +11,87 @@ pytestmark = pytest.mark.skipif( reason="DAGMC CAD geometry is not enabled.") -class DAGMCUniverseTest(PyAPITestHarness): - def __init__(self, *args, **kwargs): - super().__init__(*args, **kwargs) +@pytest.fixture +def pin_lattice_model(): + ### MATERIALS ### + fuel = openmc.Material(name='no-void fuel') + fuel.set_density('g/cc', 10.29769) + fuel.add_nuclide('U234', 0.93120485) + fuel.add_nuclide('U235', 0.00055815) + fuel.add_nuclide('U238', 0.022408) + fuel.add_nuclide('O16', 0.045829) - ### MATERIALS ### - fuel = openmc.Material(name='no-void fuel') - fuel.set_density('g/cc', 10.29769) - fuel.add_nuclide('U234', 0.93120485) - fuel.add_nuclide('U235', 0.00055815) - fuel.add_nuclide('U238', 0.022408) - fuel.add_nuclide('O16', 0.045829) + cladding = openmc.Material(name='clad') + cladding.set_density('g/cc', 6.55) + cladding.add_nuclide('Zr90', 0.021827) + cladding.add_nuclide('Zr91', 0.00476) + cladding.add_nuclide('Zr92', 0.0072758) + cladding.add_nuclide('Zr94', 0.0073734) + cladding.add_nuclide('Zr96', 0.0011879) - cladding = openmc.Material(name='clad') - cladding.set_density('g/cc', 6.55) - cladding.add_nuclide('Zr90', 0.021827) - cladding.add_nuclide('Zr91', 0.00476) - cladding.add_nuclide('Zr92', 0.0072758) - cladding.add_nuclide('Zr94', 0.0073734) - cladding.add_nuclide('Zr96', 0.0011879) + water = openmc.Material(name='water') + water.set_density('g/cc', 0.740582) + water.add_nuclide('H1', 0.049457) + water.add_nuclide('O16', 0.024672) + water.add_nuclide('B10', 8.0042e-06) + water.add_nuclide('B11', 3.2218e-05) + water.add_s_alpha_beta('c_H_in_H2O') - water = openmc.Material(name='water') - water.set_density('g/cc', 0.740582) - water.add_nuclide('H1', 0.049457) - water.add_nuclide('O16', 0.024672) - water.add_nuclide('B10', 8.0042e-06) - water.add_nuclide('B11', 3.2218e-05) - water.add_s_alpha_beta('c_H_in_H2O') + model = openmc.Model() + model.materials = openmc.Materials([fuel, cladding, water]) - self._model.materials = openmc.Materials([fuel, cladding, water]) + ### GEOMETRY ### + # create the DAGMC universe + pincell_univ = openmc.DAGMCUniverse(filename='dagmc.h5m', auto_geom_ids=True) - ### GEOMETRY ### - # create the DAGMC universe - pincell_univ = openmc.DAGMCUniverse(filename='dagmc.h5m', auto_geom_ids=True) + # creates another DAGMC universe, this time with within a bounded cell + bound_pincell_universe = openmc.DAGMCUniverse(filename='dagmc.h5m').bounded_universe() + # uses the bound_dag_cell as the root argument to test the type checks in openmc.Geometry + bound_pincell_geometry = openmc.Geometry(root=bound_pincell_universe) + # assigns the bound_dag_geometry to the model to test the type checks in model.Geometry setter + model.geometry = bound_pincell_geometry - # creates another DAGMC universe, this time with within a bounded cell - bound_pincell_universe = openmc.DAGMCUniverse(filename='dagmc.h5m').bounded_universe() - # uses the bound_dag_cell as the root argument to test the type checks in openmc.Geometry - bound_pincell_geometry = openmc.Geometry(root=bound_pincell_universe) - # assigns the bound_dag_geometry to the model to test the type checks in model.Geometry setter - self._model.geometry = bound_pincell_geometry + # create a 2 x 2 lattice using the DAGMC pincell + pitch = np.asarray((24.0, 24.0)) + lattice = openmc.RectLattice() + lattice.pitch = pitch + lattice.universes = [[pincell_univ] * 2] * 2 + lattice.lower_left = -pitch - # create a 2 x 2 lattice using the DAGMC pincell - pitch = np.asarray((24.0, 24.0)) - lattice = openmc.RectLattice() - lattice.pitch = pitch - lattice.universes = [[pincell_univ] * 2] * 2 - lattice.lower_left = -pitch + left = openmc.XPlane(x0=-pitch[0], name='left', boundary_type='reflective') + right = openmc.XPlane(x0=pitch[0], name='right', boundary_type='reflective') + front = openmc.YPlane(y0=-pitch[1], name='front', boundary_type='reflective') + back = openmc.YPlane(y0=pitch[1], name='back', boundary_type='reflective') + # clip the DAGMC geometry at +/- 10 cm w/ CSG planes + bottom = openmc.ZPlane(z0=-10.0, name='bottom', boundary_type='reflective') + top = openmc.ZPlane(z0=10.0, name='top', boundary_type='reflective') - left = openmc.XPlane(x0=-pitch[0], name='left', boundary_type='reflective') - right = openmc.XPlane(x0=pitch[0], name='right', boundary_type='reflective') - front = openmc.YPlane(y0=-pitch[1], name='front', boundary_type='reflective') - back = openmc.YPlane(y0=pitch[1], name='back', boundary_type='reflective') - # clip the DAGMC geometry at +/- 10 cm w/ CSG planes - bottom = openmc.ZPlane(z0=-10.0, name='bottom', boundary_type='reflective') - top = openmc.ZPlane(z0=10.0, name='top', boundary_type='reflective') + bounding_region = +left & -right & +front & -back & +bottom & -top + bounding_cell = openmc.Cell(fill=lattice, region=bounding_region) - bounding_region = +left & -right & +front & -back & +bottom & -top - bounding_cell = openmc.Cell(fill=lattice, region=bounding_region) + model.geometry = openmc.Geometry([bounding_cell]) - self._model.geometry = openmc.Geometry([bounding_cell]) + # add a cell instance tally + tally = openmc.Tally(name='cell instance tally') + # using scattering + cell_instance_filter = openmc.CellInstanceFilter(((4, 0), (4, 1), (4, 2), (4, 3), (4, 4))) + tally.filters = [cell_instance_filter] + tally.scores = ['scatter'] + model.tallies = [tally] - # add a cell instance tally - tally = openmc.Tally(name='cell instance tally') - # using scattering - cell_instance_filter = openmc.CellInstanceFilter(((4, 0), (4, 1), (4, 2), (4, 3), (4, 4))) - tally.filters = [cell_instance_filter] - tally.scores = ['scatter'] - self._model.tallies = [tally] + # settings + model.settings.particles = 100 + model.settings.batches = 10 + model.settings.inactive = 5 + model.settings.output = {'summary' : False} + model.settings.source = openmc.IndependentSource( + space=openmc.stats.Box((-10., -10., -24.), (10., 10., 24.)), + constraints={'fissionable': True}, + ) - # settings - self._model.settings.particles = 100 - self._model.settings.batches = 10 - self._model.settings.inactive = 5 - self._model.settings.output = {'summary' : False} + return model -def test_univ(): - harness = DAGMCUniverseTest('statepoint.10.h5', model=openmc.Model()) + +def test_univ(pin_lattice_model): + harness = PyAPITestHarness('statepoint.10.h5', model=pin_lattice_model) harness.main() diff --git a/tests/regression_tests/density/results_true.dat b/tests/regression_tests/density/results_true.dat index c8e3b1ede8..42dc0c19f3 100644 --- a/tests/regression_tests/density/results_true.dat +++ b/tests/regression_tests/density/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.110057E+00 1.303260E-02 +1.082191E+00 3.064029E-02 diff --git a/tests/regression_tests/deplete_no_transport/test.py b/tests/regression_tests/deplete_no_transport/test.py index 63ae584e11..5550ad0481 100644 --- a/tests/regression_tests/deplete_no_transport/test.py +++ b/tests/regression_tests/deplete_no_transport/test.py @@ -76,6 +76,8 @@ def test_against_self(run_in_tmpdir, dt = [360] # single step # Perform simulation using the predictor algorithm + if config['mpi'] and multiproc: + pytest.skip("Multiprocessing depletion is disabled when MPI is enabled.") openmc.deplete.pool.USE_MULTIPROCESSING = multiproc openmc.deplete.PredictorIntegrator(op, dt, @@ -135,6 +137,8 @@ def test_against_coupled(run_in_tmpdir, dt = [dt] # single step # Perform simulation using the predictor algorithm + if config['mpi'] and multiproc: + pytest.skip("Multiprocessing depletion is disabled when MPI is enabled.") openmc.deplete.pool.USE_MULTIPROCESSING = multiproc openmc.deplete.PredictorIntegrator( op, dt, power=174, timestep_units=time_units).integrate() diff --git a/tests/regression_tests/deplete_no_transport/test_reference_coupled_days.h5 b/tests/regression_tests/deplete_no_transport/test_reference_coupled_days.h5 index 5fdc656d97..9757c9791b 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_coupled_days.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_coupled_days.h5 differ diff --git a/tests/regression_tests/deplete_no_transport/test_reference_coupled_hours.h5 b/tests/regression_tests/deplete_no_transport/test_reference_coupled_hours.h5 index 65bfc19a91..08d4d3eedc 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_coupled_hours.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_coupled_hours.h5 differ diff --git a/tests/regression_tests/deplete_no_transport/test_reference_coupled_minutes.h5 b/tests/regression_tests/deplete_no_transport/test_reference_coupled_minutes.h5 index 294cb589f7..41b5235bb6 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_coupled_minutes.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_coupled_minutes.h5 differ diff --git a/tests/regression_tests/deplete_no_transport/test_reference_coupled_months.h5 b/tests/regression_tests/deplete_no_transport/test_reference_coupled_months.h5 index ed62e46104..53d80aff0f 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_coupled_months.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_coupled_months.h5 differ diff --git a/tests/regression_tests/deplete_no_transport/test_reference_fission_q.h5 b/tests/regression_tests/deplete_no_transport/test_reference_fission_q.h5 index 9d32d89fe2..fe695692d6 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_fission_q.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_fission_q.h5 differ diff --git a/tests/regression_tests/deplete_no_transport/test_reference_source_rate.h5 b/tests/regression_tests/deplete_no_transport/test_reference_source_rate.h5 index 3f3b4aa2ac..c9c7e9e363 100644 Binary files a/tests/regression_tests/deplete_no_transport/test_reference_source_rate.h5 and b/tests/regression_tests/deplete_no_transport/test_reference_source_rate.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_ext_source.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_ext_source.h5 index aa09e1bcf4..2f9951a42a 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_ext_source.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_ext_source.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_feed.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_feed.h5 index 284d5cbe4e..25ab31041c 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_feed.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_feed.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_redox.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_redox.h5 new file mode 100644 index 0000000000..c7f002ba14 Binary files /dev/null and b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_redox.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal.h5 index 271af24103..c3121a9535 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal_and_redox.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_depletion_with_removal_and_redox.h5 new file mode 100644 index 0000000000..80ce771fce Binary files /dev/null and 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b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_feed.h5 index d080b44709..af67333406 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_feed.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_feed.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_removal.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_removal.h5 index 36f89e0090..59c65427c0 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_removal.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_only_removal.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_ext_source.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_ext_source.h5 index f3b1b171eb..cceb7fc780 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_ext_source.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_ext_source.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_transfer.h5 b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_transfer.h5 index b0ba997407..a1c0e5b415 100644 Binary files a/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_transfer.h5 and b/tests/regression_tests/deplete_with_transfer_rates/ref_no_depletion_with_transfer.h5 differ diff --git a/tests/regression_tests/deplete_with_transfer_rates/test.py b/tests/regression_tests/deplete_with_transfer_rates/test.py index 4ad009d22e..461287f6e6 100644 --- a/tests/regression_tests/deplete_with_transfer_rates/test.py +++ b/tests/regression_tests/deplete_with_transfer_rates/test.py @@ -12,7 +12,6 @@ from openmc.deplete import CoupledOperator from tests.regression_tests import config, assert_reaction_rates_equal, \ assert_atoms_equal - @pytest.fixture def model(): openmc.reset_auto_ids() @@ -40,10 +39,9 @@ def model(): geometry = openmc.Geometry([cell_f, cell_w]) settings = openmc.Settings() - settings.particles = 100 + settings.particles = 150 settings.inactive = 0 settings.batches = 10 - settings.seed = 1 return openmc.Model(geometry, materials, settings) @@ -55,6 +53,9 @@ def model(): (-1e-5, None, 174.0, 'depletion_with_feed'), (-1e-5, 'w', 0.0, 'no_depletion_with_transfer'), (1e-5, 'w', 174.0, 'depletion_with_transfer'), + (0.0, None, 174.0, 'depletion_with_redox'), + (1e-5, None, 174.0, 'depletion_with_removal_and_redox'), + (1e-5, 'w', 174.0, 'depletion_with_transfer_and_redox'), ]) def test_transfer_rates(run_in_tmpdir, model, rate, dest_mat, power, ref_result): """Tests transfer_rates depletion class with transfer rates""" @@ -62,13 +63,18 @@ def test_transfer_rates(run_in_tmpdir, model, rate, dest_mat, power, ref_result) chain_file = Path(__file__).parents[2] / 'chain_simple.xml' transfer_elements = ['Xe'] + os = {'I': -1, 'Xe':0, 'Cs': 1, 'Gd': 3, 'U': 4} op = CoupledOperator(model, chain_file) op.round_number = True integrator = openmc.deplete.PredictorIntegrator( op, [1], power, timestep_units = 'd') - integrator.add_transfer_rate('f', transfer_elements, rate, - destination_material=dest_mat) + if rate != 0.0: + integrator.add_transfer_rate('f', transfer_elements, rate, + destination_material=dest_mat) + if 'redox' in ref_result.split('_'): + integrator.add_redox('f', {'Gd157':1}, os) + integrator.integrate() # Get path to test and reference results @@ -84,9 +90,8 @@ def test_transfer_rates(run_in_tmpdir, model, rate, dest_mat, power, ref_result) res_ref = openmc.deplete.Results(path_reference) res_test = openmc.deplete.Results(path_test) - assert_atoms_equal(res_ref, res_test) - assert_reaction_rates_equal(res_ref, res_test) - + assert_atoms_equal(res_ref, res_test, tol=1e-3) + assert_reaction_rates_equal(res_ref, res_test, tol=1e-3) @pytest.mark.parametrize("rate, power, ref_result", [ (1e-1, 0.0, 'no_depletion_with_ext_source'), @@ -119,5 +124,5 @@ def test_external_source_rates(run_in_tmpdir, model, rate, power, ref_result): res_ref = openmc.deplete.Results(path_reference) res_test = openmc.deplete.Results(path_test) - assert_atoms_equal(res_ref, res_test) - assert_reaction_rates_equal(res_ref, res_test) + assert_atoms_equal(res_ref, res_test, tol=1e-3) + assert_reaction_rates_equal(res_ref, res_test, tol=1e-3) diff --git a/tests/regression_tests/deplete_with_transport/last_step_reference_materials.xml b/tests/regression_tests/deplete_with_transport/last_step_reference_materials.xml index 242e2e7db5..2dca559925 100644 --- a/tests/regression_tests/deplete_with_transport/last_step_reference_materials.xml +++ b/tests/regression_tests/deplete_with_transport/last_step_reference_materials.xml @@ -4,993 +4,993 @@ - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + - - - - - - - - - + + + + + + + + + diff --git a/tests/regression_tests/deplete_with_transport/test.py b/tests/regression_tests/deplete_with_transport/test.py index 0f7ebf00f3..a2be22c565 100644 --- a/tests/regression_tests/deplete_with_transport/test.py +++ b/tests/regression_tests/deplete_with_transport/test.py @@ -65,6 +65,8 @@ def test_full(run_in_tmpdir, problem, multiproc): power = 2.337e15*4*JOULE_PER_EV*1e6 # MeV/second cm from CASMO # Perform simulation using the predictor algorithm + if config['mpi'] and multiproc: + pytest.skip("Multiprocessing depletion is disabled when MPI is enabled.") openmc.deplete.pool.USE_MULTIPROCESSING = multiproc openmc.deplete.PredictorIntegrator(op, dt, power).integrate() diff --git a/tests/regression_tests/deplete_with_transport/test_reference.h5 b/tests/regression_tests/deplete_with_transport/test_reference.h5 index e8478250be..cc616e7910 100644 Binary files a/tests/regression_tests/deplete_with_transport/test_reference.h5 and b/tests/regression_tests/deplete_with_transport/test_reference.h5 differ diff --git a/tests/regression_tests/diff_tally/results_true.dat b/tests/regression_tests/diff_tally/results_true.dat index 14729c8214..a88081b7c1 100644 --- a/tests/regression_tests/diff_tally/results_true.dat +++ b/tests/regression_tests/diff_tally/results_true.dat @@ -1,27 +1,27 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. -3,,density,flux,-8.7368155e+00,1.5577812e+00 -3,,density,flux,-1.4842625e+01,2.2947682e+00 -1,,density,flux,-2.0922686e-01,4.9935069e-02 -1,,density,flux,-3.4582490e-01,1.7454386e-01 -1,O16,nuclide_density,flux,1.1301782e+01,2.2440389e+01 -1,O16,nuclide_density,flux,3.2481563e+00,3.2342885e+01 -1,U235,nuclide_density,flux,-1.5048665e+03,5.9045681e+02 -1,U235,nuclide_density,flux,-1.6193231e+03,9.7230073e+02 -1,,temperature,flux,-1.0891931e-04,2.3076849e-04 -1,,temperature,flux,-1.3563853e-04,2.0952841e-04 -3,,density,total,-3.9155374e+00,5.4862771e-01 -3,,density,absorption,-4.9210534e-01,3.4700776e-02 -3,,density,scatter,-3.4234320e+00,5.1443821e-01 -3,,density,fission,-3.1088949e-01,8.0540906e-02 -3,,density,nu-fission,-7.6137447e-01,1.9548876e-01 -3,,density,total,-3.8615156e-01,1.0175701e-01 -3,,density,absorption,-3.4458071e-01,9.3381192e-02 -3,,density,scatter,-4.1570854e-02,8.6942039e-03 -3,,density,fission,-2.9864832e-01,8.4711885e-02 -3,,density,nu-fission,-7.2797006e-01,2.0640455e-01 -3,,density,total,1.0491251e+01,9.1787723e+00 -3,,density,absorption,2.9819000e-01,3.0887165e-01 -3,,density,scatter,1.0193061e+01,8.8715930e+00 +3,,density,flux,-9.2822822e+00,1.6880315e+00 +3,,density,flux,-2.0591270e+01,3.0043477e+00 +1,,density,flux,-2.9765141e-01,5.2949290e-02 +1,,density,flux,-4.0095723e-01,1.1716168e-01 +1,O16,nuclide_density,flux,-1.4245069e+01,6.3028710e+00 +1,O16,nuclide_density,flux,-2.5098326e+01,5.7525657e+00 +1,U235,nuclide_density,flux,-2.1513560e+03,6.7234014e+02 +1,U235,nuclide_density,flux,-2.4222736e+03,7.7715656e+02 +1,,temperature,flux,-1.1242141e-04,8.1692839e-05 +1,,temperature,flux,6.1357500e-06,7.4812624e-05 +3,,density,total,-4.2880614e+00,7.0021512e-01 +3,,density,absorption,-5.0324695e-01,4.9079615e-02 +3,,density,scatter,-3.7848144e+00,6.5868388e-01 +3,,density,fission,-2.7732455e-01,6.4647487e-02 +3,,density,nu-fission,-6.7990282e-01,1.5692707e-01 +3,,density,total,-3.8043572e-01,9.6222860e-02 +3,,density,absorption,-3.3518262e-01,8.6810436e-02 +3,,density,scatter,-4.5253106e-02,9.5205809e-03 +3,,density,fission,-2.6400028e-01,6.8175997e-02 +3,,density,nu-fission,-6.4353897e-01,1.6613026e-01 +3,,density,total,-3.2070285e-01,2.8328990e+00 +3,,density,absorption,2.5921007e-02,2.2141808e-02 +3,,density,scatter,-3.4662385e-01,2.8171749e+00 3,,density,fission,0.0000000e+00,0.0000000e+00 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 3,,density,total,0.0000000e+00,0.0000000e+00 @@ -29,19 +29,19 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. 3,,density,scatter,0.0000000e+00,0.0000000e+00 3,,density,fission,0.0000000e+00,0.0000000e+00 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,density,total,4.7128871e-01,5.7197095e-02 -1,,density,absorption,2.1981833e-02,1.7427232e-02 -1,,density,scatter,4.4930687e-01,4.0030120e-02 -1,,density,fission,6.0712328e-03,1.3719512e-02 -1,,density,nu-fission,1.5474650e-02,3.3437103e-02 -1,,density,total,1.2203418e-02,1.5798741e-02 -1,,density,absorption,7.0228085e-03,1.5294984e-02 -1,,density,scatter,5.1806097e-03,5.0807003e-04 -1,,density,fission,4.1074923e-03,1.3759608e-02 -1,,density,nu-fission,1.0046778e-02,3.3529881e-02 -1,,density,total,-5.2100220e-01,2.7618985e-01 -1,,density,absorption,-1.1039048e-02,6.2043549e-03 -1,,density,scatter,-5.0996315e-01,2.7027892e-01 +1,,density,total,4.0321800e-01,3.5365140e-02 +1,,density,absorption,4.8426976e-03,8.3784362e-03 +1,,density,scatter,3.9837530e-01,2.9076664e-02 +1,,density,fission,-5.4793062e-03,7.1720201e-03 +1,,density,nu-fission,-1.2481616e-02,1.7542625e-02 +1,,density,total,-3.6063021e-03,7.1950060e-03 +1,,density,absorption,-8.2666439e-03,6.9274342e-03 +1,,density,scatter,4.6603417e-03,4.1803496e-04 +1,,density,fission,-7.6315741e-03,7.1774359e-03 +1,,density,nu-fission,-1.8551295e-02,1.7493106e-02 +1,,density,total,-6.2852725e-01,1.9776006e-01 +1,,density,absorption,-1.4850233e-02,4.3086611e-03 +1,,density,scatter,-6.1367701e-01,1.9363188e-01 1,,density,fission,0.0000000e+00,0.0000000e+00 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 1,,density,total,0.0000000e+00,0.0000000e+00 @@ -49,19 +49,19 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. 1,,density,scatter,0.0000000e+00,0.0000000e+00 1,,density,fission,0.0000000e+00,0.0000000e+00 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,O16,nuclide_density,total,5.5744608e+01,1.3811361e+01 -1,O16,nuclide_density,absorption,2.1284059e+00,3.3353171e+00 -1,O16,nuclide_density,scatter,5.3616202e+01,1.0494347e+01 -1,O16,nuclide_density,fission,6.6058671e-01,1.9263932e+00 -1,O16,nuclide_density,nu-fission,1.5973305e+00,4.6977280e+00 -1,O16,nuclide_density,total,9.8433784e-01,2.4053581e+00 -1,O16,nuclide_density,absorption,9.1167507e-01,2.2565683e+00 -1,O16,nuclide_density,scatter,7.2662768e-02,1.5198625e-01 -1,O16,nuclide_density,fission,6.8845700e-01,1.9451444e+00 -1,O16,nuclide_density,nu-fission,1.6768628e+00,4.7395897e+00 -1,O16,nuclide_density,total,8.1604245e+00,3.7248338e+01 -1,O16,nuclide_density,absorption,2.4903834e-01,4.5609671e-01 -1,O16,nuclide_density,scatter,7.9113862e+00,3.6811434e+01 +1,O16,nuclide_density,total,4.2608989e+01,2.6322158e+00 +1,O16,nuclide_density,absorption,-5.9877963e-01,4.2139216e-01 +1,O16,nuclide_density,scatter,4.3207769e+01,2.5312922e+00 +1,O16,nuclide_density,fission,-9.2838585e-01,4.3505041e-01 +1,O16,nuclide_density,nu-fission,-2.2834786e+00,1.0634300e+00 +1,O16,nuclide_density,total,-1.1195412e+00,3.3033730e-01 +1,O16,nuclide_density,absorption,-1.0650267e+00,3.2780477e-01 +1,O16,nuclide_density,scatter,-5.4514540e-02,2.4911965e-02 +1,O16,nuclide_density,fission,-8.6787386e-01,4.4270048e-01 +1,O16,nuclide_density,nu-fission,-2.1159252e+00,1.0787495e+00 +1,O16,nuclide_density,total,-3.1004750e+01,8.0776339e+00 +1,O16,nuclide_density,absorption,-5.0354237e-01,2.6144390e-01 +1,O16,nuclide_density,scatter,-3.0501208e+01,7.8176703e+00 1,O16,nuclide_density,fission,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,total,0.0000000e+00,0.0000000e+00 @@ -69,19 +69,19 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. 1,O16,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,fission,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 -1,U235,nuclide_density,total,-2.8654443e+02,3.3721470e+02 -1,U235,nuclide_density,absorption,2.0329180e+02,1.0522263e+02 -1,U235,nuclide_density,scatter,-4.8983623e+02,2.3237977e+02 -1,U235,nuclide_density,fission,2.6089045e+02,7.2578344e+01 -1,U235,nuclide_density,nu-fission,6.3692044e+02,1.7710877e+02 -1,U235,nuclide_density,total,4.5611633e+02,9.1682367e+01 -1,U235,nuclide_density,absorption,3.3831545e+02,8.5035501e+01 -1,U235,nuclide_density,scatter,1.1780088e+02,7.4128809e+00 -1,U235,nuclide_density,fission,2.6094461e+02,7.2102445e+01 -1,U235,nuclide_density,nu-fission,6.3705705e+02,1.7578950e+02 -1,U235,nuclide_density,total,-4.1342174e+03,1.4666097e+03 -1,U235,nuclide_density,absorption,-1.1329170e+02,3.5066579e+01 -1,U235,nuclide_density,scatter,-4.0209257e+03,1.4320401e+03 +1,U235,nuclide_density,total,-5.3578869e+02,3.4044374e+02 +1,U235,nuclide_density,absorption,2.0769087e+02,1.0873543e+02 +1,U235,nuclide_density,scatter,-7.4347956e+02,2.5966153e+02 +1,U235,nuclide_density,fission,2.8982867e+02,8.5348425e+01 +1,U235,nuclide_density,nu-fission,7.0772332e+02,2.0847449e+02 +1,U235,nuclide_density,total,4.8356107e+02,1.0276621e+02 +1,U235,nuclide_density,absorption,3.6683548e+02,9.6924085e+01 +1,U235,nuclide_density,scatter,1.1672558e+02,6.1773010e+00 +1,U235,nuclide_density,fission,2.8941699e+02,8.4475937e+01 +1,U235,nuclide_density,nu-fission,7.0639136e+02,2.0594285e+02 +1,U235,nuclide_density,total,-4.6777522e+03,1.5037171e+03 +1,U235,nuclide_density,absorption,-1.1585081e+02,3.8299177e+01 +1,U235,nuclide_density,scatter,-4.5619014e+03,1.4660078e+03 1,U235,nuclide_density,fission,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,total,0.0000000e+00,0.0000000e+00 @@ -89,19 +89,19 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. 1,U235,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,fission,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,temperature,total,5.3733744e-05,1.1785516e-04 -1,,temperature,absorption,-1.3987780e-05,1.9819801e-05 -1,,temperature,scatter,6.7721524e-05,9.9934995e-05 -1,,temperature,fission,-1.4882696e-05,1.6930666e-05 -1,,temperature,nu-fission,-3.6272065e-05,4.1250892e-05 -1,,temperature,total,-1.8119796e-05,2.2651409e-05 -1,,temperature,absorption,-1.7632076e-05,2.1825006e-05 -1,,temperature,scatter,-4.8771972e-07,1.4270133e-06 -1,,temperature,fission,-1.4890811e-05,1.6935899e-05 -1,,temperature,nu-fission,-3.6292215e-05,4.1263951e-05 -1,,temperature,total,-2.0776498e-04,2.9286552e-04 -1,,temperature,absorption,-3.9068381e-06,3.4912438e-06 -1,,temperature,scatter,-2.0385814e-04,2.8941307e-04 +1,,temperature,total,8.2134941e-05,1.3941434e-05 +1,,temperature,absorption,4.1502002e-05,3.5967068e-05 +1,,temperature,scatter,4.0632939e-05,2.6595574e-05 +1,,temperature,fission,3.1768469e-06,2.1582455e-05 +1,,temperature,nu-fission,7.7368345e-06,5.2593375e-05 +1,,temperature,total,1.0834099e-06,2.6707333e-05 +1,,temperature,absorption,1.6240165e-06,2.6844372e-05 +1,,temperature,scatter,-5.4060665e-07,2.5905412e-07 +1,,temperature,fission,3.1674458e-06,2.1588836e-05 +1,,temperature,nu-fission,7.7134913e-06,5.2609321e-05 +1,,temperature,total,9.5175179e-05,1.0549922e-04 +1,,temperature,absorption,4.3553888e-06,2.9261613e-06 +1,,temperature,scatter,9.0819790e-05,1.0362538e-04 1,,temperature,fission,0.0000000e+00,0.0000000e+00 1,,temperature,nu-fission,0.0000000e+00,0.0000000e+00 1,,temperature,total,0.0000000e+00,0.0000000e+00 @@ -109,68 +109,68 @@ d_material,d_nuclide,d_variable,score,mean,std. dev. 1,,temperature,scatter,0.0000000e+00,0.0000000e+00 1,,temperature,fission,0.0000000e+00,0.0000000e+00 1,,temperature,nu-fission,0.0000000e+00,0.0000000e+00 -3,,density,absorption,-4.5579543e-01,5.5532252e-02 -3,,density,absorption,-1.3526251e-02,1.3917291e-01 -1,,density,absorption,3.8695654e-02,1.5823093e-02 -1,,density,absorption,-1.8171150e-02,1.2999773e-03 -1,O16,nuclide_density,absorption,2.0992238e+00,2.7230754e+00 -1,O16,nuclide_density,absorption,-6.8956953e-01,3.3064989e-01 -1,U235,nuclide_density,absorption,2.5000417e+02,7.3334295e+01 -1,U235,nuclide_density,absorption,-1.0832917e+02,1.1517513e+01 -1,,temperature,absorption,1.1819459e-05,4.2090670e-05 -1,,temperature,absorption,-7.2302974e-06,1.5200299e-05 +3,,density,absorption,-5.4897740e-01,8.6529144e-02 +3,,density,absorption,1.3410763e-01,5.6235628e-02 +1,,density,absorption,2.9551566e-02,1.5215007e-02 +1,,density,absorption,-8.6382033e-03,5.5181454e-03 +1,O16,nuclide_density,absorption,2.7111116e-01,9.6922067e-01 +1,O16,nuclide_density,absorption,-7.3785997e-01,7.7252792e-01 +1,U235,nuclide_density,absorption,2.7361252e+02,1.6168134e+02 +1,U235,nuclide_density,absorption,-9.6885408e+01,1.9390948e+01 +1,,temperature,absorption,1.0054736e-05,4.2876538e-05 +1,,temperature,absorption,-1.8280609e-06,1.0133065e-05 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 -3,,density,scatter,-7.6858714e-01,3.2467801e-01 +3,,density,scatter,-5.4273849e-01,1.8081153e-01 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 -3,,density,scatter,3.2513857e-04,3.2513857e-04 -3,,density,nu-fission,-6.4963717e-01,1.8008086e-01 -3,,density,scatter,-2.6911548e+00,2.6336008e-01 -3,,density,nu-fission,-6.3014524e-01,1.8056453e-01 -3,,density,scatter,-3.4247012e-02,2.2649385e-02 +3,,density,scatter,1.3451827e-02,7.2870304e-03 +3,,density,nu-fission,-8.4200508e-01,3.4267126e-01 +3,,density,scatter,-3.1963455e+00,5.0369564e-01 +3,,density,nu-fission,-8.2934702e-01,3.4526131e-01 +3,,density,scatter,-7.0221960e-02,6.8067882e-02 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 -3,,density,scatter,1.0254549e+01,1.1054242e+01 +3,,density,scatter,1.1368387e+00,1.2091778e+00 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 3,,density,scatter,0.0000000e+00,0.0000000e+00 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 -3,,density,scatter,2.5022850e-01,2.1207285e+00 +3,,density,scatter,-1.5916491e+00,2.3551913e+00 3,,density,nu-fission,0.0000000e+00,0.0000000e+00 3,,density,scatter,0.0000000e+00,0.0000000e+00 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,density,scatter,8.1153611e-03,3.1226564e-02 +1,,density,scatter,-1.8655633e-03,2.4061808e-02 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,density,scatter,2.3728497e-04,9.7166041e-04 -1,,density,nu-fission,2.6248459e-02,3.9328080e-02 -1,,density,scatter,4.2447769e-01,1.2580873e-02 -1,,density,nu-fission,1.9600074e-02,3.8118776e-02 -1,,density,scatter,8.0978391e-03,2.6585488e-03 +1,,density,scatter,-1.7672807e-04,7.4702879e-04 +1,,density,nu-fission,4.4506944e-03,3.1478180e-02 +1,,density,scatter,3.7553200e-01,2.3420342e-02 +1,,density,nu-fission,-1.3567324e-03,3.0610901e-02 +1,,density,scatter,6.9330560e-03,4.6649873e-03 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,density,scatter,-3.8358302e-01,2.1525401e-01 +1,,density,scatter,-5.1560927e-01,1.4846253e-01 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 1,,density,scatter,0.0000000e+00,0.0000000e+00 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 -1,,density,scatter,-1.1924803e-01,9.1254221e-02 +1,,density,scatter,-1.0427977e-01,6.6396271e-02 1,,density,nu-fission,0.0000000e+00,0.0000000e+00 1,,density,scatter,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 -1,O16,nuclide_density,scatter,-1.6577061e-01,1.0793192e-01 -1,O16,nuclide_density,nu-fission,2.4995074e+00,5.7946039e+00 -1,O16,nuclide_density,scatter,5.5800956e-01,5.7675606e-01 +1,O16,nuclide_density,scatter,4.6587151e-02,9.0232672e-02 +1,O16,nuclide_density,nu-fission,-2.1162226e+00,2.4773842e+00 +1,O16,nuclide_density,scatter,6.6533325e-01,2.4693113e-01 1,O16,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,O16,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 -1,U235,nuclide_density,scatter,5.8641633e+00,2.9488422e+00 -1,U235,nuclide_density,nu-fission,6.7444160e+02,1.1308014e+02 -1,U235,nuclide_density,scatter,1.1592472e+02,2.8886339e+01 +1,U235,nuclide_density,scatter,2.8979849e+01,2.0235325e+01 +1,U235,nuclide_density,nu-fission,8.1210341e+02,2.9252040e+02 +1,U235,nuclide_density,scatter,1.0307302e+02,4.4919960e+01 1,U235,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,nu-fission,0.0000000e+00,0.0000000e+00 1,U235,nuclide_density,scatter,0.0000000e+00,0.0000000e+00 1,,temperature,nu-fission,0.0000000e+00,0.0000000e+00 -1,,temperature,scatter,-7.7511866e-07,6.4761261e-07 -1,,temperature,nu-fission,-9.5466386e-05,3.1033330e-05 -1,,temperature,scatter,-2.7127084e-06,2.0699253e-07 +1,,temperature,scatter,-3.3782154e-06,3.8240314e-06 +1,,temperature,nu-fission,-6.8920903e-05,4.4384761e-05 +1,,temperature,scatter,1.6325729e-07,2.3270228e-06 1,,temperature,nu-fission,0.0000000e+00,0.0000000e+00 1,,temperature,scatter,0.0000000e+00,0.0000000e+00 1,,temperature,nu-fission,0.0000000e+00,0.0000000e+00 diff --git a/tests/regression_tests/distribmat/results_true.dat b/tests/regression_tests/distribmat/results_true.dat index af7b27fe72..166fd4662d 100644 --- a/tests/regression_tests/distribmat/results_true.dat +++ b/tests/regression_tests/distribmat/results_true.dat @@ -1,5 +1,5 @@ k-combined: -1.257344E+00 6.246360E-04 +1.246391E+00 1.414798E-02 Cell ID = 11 Name = diff --git a/tests/regression_tests/distribmat/test.py b/tests/regression_tests/distribmat/test.py index 02f7e773e5..dd09eec36c 100644 --- a/tests/regression_tests/distribmat/test.py +++ b/tests/regression_tests/distribmat/test.py @@ -73,7 +73,7 @@ class DistribmatTestHarness(PyAPITestHarness): # Plots #################### - plot1 = openmc.Plot(plot_id=1) + plot1 = openmc.SlicePlot(plot_id=1) plot1.basis = 'xy' plot1.color_by = 'cell' plot1.filename = 'cellplot' @@ -81,7 +81,7 @@ class DistribmatTestHarness(PyAPITestHarness): plot1.width = (7, 7) plot1.pixels = (400, 400) - plot2 = openmc.Plot(plot_id=2) + plot2 = openmc.SlicePlot(plot_id=2) plot2.basis = 'xy' plot2.color_by = 'material' plot2.filename = 'matplot' diff --git a/tests/regression_tests/eigenvalue_genperbatch/results_true.dat b/tests/regression_tests/eigenvalue_genperbatch/results_true.dat index 3f7ea801a1..d171c5e87f 100644 --- a/tests/regression_tests/eigenvalue_genperbatch/results_true.dat +++ b/tests/regression_tests/eigenvalue_genperbatch/results_true.dat @@ -1,5 +1,5 @@ k-combined: -3.037481E-01 1.247474E-04 +2.975937E-01 1.293390E-03 tally 1: -3.211129E+01 -2.578396E+02 +3.173222E+01 +2.517683E+02 diff --git a/tests/regression_tests/eigenvalue_no_inactive/results_true.dat b/tests/regression_tests/eigenvalue_no_inactive/results_true.dat index 2b10216081..3ba7485a96 100644 --- a/tests/regression_tests/eigenvalue_no_inactive/results_true.dat +++ b/tests/regression_tests/eigenvalue_no_inactive/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.998284E-01 7.587782E-03 +3.072780E-01 6.882841E-03 diff --git a/tests/regression_tests/electron_heating/__init__.py b/tests/regression_tests/electron_heating/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/electron_heating/inputs_true.dat b/tests/regression_tests/electron_heating/inputs_true.dat new file mode 100644 index 0000000000..ec8e5a8376 --- /dev/null +++ b/tests/regression_tests/electron_heating/inputs_true.dat @@ -0,0 +1,32 @@ + + + + + + + + + + + + + + + fixed source + 10000 + 1 + + + 10000000.0 1.0 + + + + 1000.0 + + + + + heating + + + diff --git a/tests/regression_tests/electron_heating/results_true.dat b/tests/regression_tests/electron_heating/results_true.dat new file mode 100644 index 0000000000..4f54ceaa4d --- /dev/null +++ b/tests/regression_tests/electron_heating/results_true.dat @@ -0,0 +1,3 @@ +tally 1: +1.000000E+07 +1.000000E+14 diff --git a/tests/regression_tests/electron_heating/test.py b/tests/regression_tests/electron_heating/test.py new file mode 100644 index 0000000000..e7a58560c4 --- /dev/null +++ b/tests/regression_tests/electron_heating/test.py @@ -0,0 +1,40 @@ +import pytest +import openmc + +from tests.testing_harness import PyAPITestHarness + + +@pytest.fixture +def water_model(): + # Define materals and geometry + water = openmc.Material() + water.add_nuclide("H1", 2.0) + water.add_nuclide("O16", 1.0) + water.set_density("g/cc", 1.0) + sphere = openmc.Sphere(r=1.0, boundary_type="reflective") + sph = openmc.Cell(fill=water, region=-sphere) + geometry = openmc.Geometry([sph]) + source = openmc.IndependentSource( + energy=openmc.stats.delta_function(10.0e6), + particle="electron" + ) + + # Define settings + settings = openmc.Settings() + settings.particles = 10000 + settings.batches = 1 + settings.cutoff = {"energy_photon": 1000.0} + settings.run_mode = "fixed source" + settings.source = source + + # Define tallies + tally = openmc.Tally() + tally.scores = ["heating"] + tallies = openmc.Tallies([tally]) + + return openmc.Model(geometry=geometry, settings=settings, tallies=tallies) + + +def test_electron_heating_calc(water_model): + harness = PyAPITestHarness("statepoint.1.h5", water_model) + harness.main() diff --git a/tests/regression_tests/energy_grid/results_true.dat b/tests/regression_tests/energy_grid/results_true.dat index deab1e28be..3a042d882b 100644 --- a/tests/regression_tests/energy_grid/results_true.dat +++ b/tests/regression_tests/energy_grid/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.152586E-01 1.458068E-03 +3.218009E-01 4.687417E-03 diff --git a/tests/regression_tests/energy_laws/results_true.dat b/tests/regression_tests/energy_laws/results_true.dat index 534a299b56..7802786838 100644 --- a/tests/regression_tests/energy_laws/results_true.dat +++ b/tests/regression_tests/energy_laws/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.444000E+00 1.044626E-02 +2.458770E+00 9.422203E-03 diff --git a/tests/regression_tests/entropy/results_true.dat b/tests/regression_tests/entropy/results_true.dat index 1c8b2908bc..92d7f091df 100644 --- a/tests/regression_tests/entropy/results_true.dat +++ b/tests/regression_tests/entropy/results_true.dat @@ -1,13 +1,13 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 entropy: 7.688862E+00 -8.237960E+00 -8.314772E+00 -8.285254E+00 -8.271486E+00 -8.291355E+00 -8.253349E+00 -8.336726E+00 -8.284741E+00 -8.328102E+00 +8.226316E+00 +8.308355E+00 +8.243413E+00 +8.369345E+00 +8.304865E+00 +8.230689E+00 +8.338304E+00 +8.270630E+00 +8.386598E+00 diff --git a/tests/regression_tests/filter_cellfrom/results_true.dat b/tests/regression_tests/filter_cellfrom/results_true.dat index 5dd43e1f33..408a4965b1 100644 --- a/tests/regression_tests/filter_cellfrom/results_true.dat +++ b/tests/regression_tests/filter_cellfrom/results_true.dat @@ -1,53 +1,53 @@ k-combined: -9.640806E-02 2.655206E-03 +9.035025E-02 2.654309E-03 tally 1: -6.025999E+00 -3.635317E+00 +5.994069E+00 +3.594398E+00 tally 2: -4.523606E-04 -2.051522E-08 +4.559707E-04 +2.080739E-08 tally 3: -6.026452E+00 -3.635862E+00 +5.994525E+00 +3.594945E+00 tally 4: 0.000000E+00 0.000000E+00 tally 5: -1.530903E+00 -2.357048E-01 +1.473892E+00 +2.187509E-01 tally 6: -4.992646E-05 -2.600391E-10 +5.223875E-05 +2.992861E-10 tally 7: -1.530953E+00 -2.357201E-01 +1.473945E+00 +2.187663E-01 tally 8: -1.889115E+01 -3.574727E+01 +1.885798E+01 +3.558423E+01 tally 9: -7.556902E+00 -5.717680E+00 +7.467961E+00 +5.580255E+00 tally 10: -5.022871E-04 -2.531352E-08 +5.082094E-04 +2.584432E-08 tally 11: -7.557405E+00 -5.718440E+00 +7.468470E+00 +5.581014E+00 tally 12: -1.889115E+01 -3.574727E+01 +1.885798E+01 +3.558423E+01 tally 13: 0.000000E+00 0.000000E+00 tally 14: -2.663407E-04 -7.161725E-09 +2.739543E-04 +7.600983E-09 tally 15: -2.663407E-04 -7.161725E-09 +2.739543E-04 +7.600983E-09 tally 16: -8.025710E+01 -6.459305E+02 +7.881296E+01 +6.221087E+02 tally 17: -1.067059E+02 -1.140939E+03 +1.051397E+02 +1.106292E+03 diff --git a/tests/regression_tests/filter_cellinstance/results_true.dat b/tests/regression_tests/filter_cellinstance/results_true.dat index 079b7d3d25..1529865954 100644 --- a/tests/regression_tests/filter_cellinstance/results_true.dat +++ b/tests/regression_tests/filter_cellinstance/results_true.dat @@ -1,84 +1,84 @@ k-combined: -1.050139E+00 1.886614E-02 +1.097679E+00 8.074294E-03 tally 1: -9.724996E-02 -2.784804E-03 -1.146976E-01 -3.173782E-03 -1.698297E-01 -6.569993E-03 -1.158802E-01 -2.959280E-03 -2.533354E-01 -1.539905E-02 -1.908717E-01 -8.360058E-03 -1.738899E-01 -6.713494E-03 -3.172247E-01 -2.124184E-02 -1.363012E-01 -4.653519E-03 -1.698720E-01 -6.753819E-03 -9.934671E-02 -2.371660E-03 -6.038075E-02 -1.204656E-03 -1.038793E+01 -2.590382E+01 -2.841397E+01 -1.865709E+02 -2.786916E+01 -1.923869E+02 -1.085149E+01 -2.907194E+01 -1.038793E+01 -2.590382E+01 -2.841397E+01 -1.865709E+02 -2.786916E+01 -1.923869E+02 -1.085149E+01 -2.907194E+01 +7.125168E-02 +1.412152E-03 +1.254059E-01 +4.145686E-03 +1.609454E-01 +6.174116E-03 +1.444278E-01 +4.523981E-03 +3.363588E-01 +2.342988E-02 +1.751677E-01 +7.108034E-03 +1.384074E-01 +3.949804E-03 +2.856450E-01 +1.824185E-02 +9.680810E-02 +2.256338E-03 +1.691663E-01 +6.456530E-03 +1.160968E-01 +3.233815E-03 +7.334131E-02 +1.456688E-03 +1.168548E+01 +3.210924E+01 +2.860162E+01 +1.876786E+02 +2.857267E+01 +1.996553E+02 +1.050245E+01 +2.569953E+01 +1.168548E+01 +3.210924E+01 +2.860162E+01 +1.876786E+02 +2.857267E+01 +1.996553E+02 +1.050245E+01 +2.569953E+01 tally 2: -1.085149E+01 -2.907194E+01 -2.786916E+01 -1.923869E+02 -2.841397E+01 -1.865709E+02 -1.038793E+01 -2.590382E+01 -1.085149E+01 -2.907194E+01 -2.786916E+01 -1.923869E+02 -2.841397E+01 -1.865709E+02 -1.038793E+01 -2.590382E+01 -6.038075E-02 -1.204656E-03 -9.934671E-02 -2.371660E-03 -1.698720E-01 -6.753819E-03 -1.363012E-01 -4.653519E-03 -3.172247E-01 -2.124184E-02 -1.738899E-01 -6.713494E-03 -1.908717E-01 -8.360058E-03 -2.533354E-01 -1.539905E-02 -1.158802E-01 -2.959280E-03 -1.698297E-01 -6.569993E-03 -1.146976E-01 -3.173782E-03 -9.724996E-02 -2.784804E-03 +1.050245E+01 +2.569953E+01 +2.857267E+01 +1.996553E+02 +2.860162E+01 +1.876786E+02 +1.168548E+01 +3.210924E+01 +1.050245E+01 +2.569953E+01 +2.857267E+01 +1.996553E+02 +2.860162E+01 +1.876786E+02 +1.168548E+01 +3.210924E+01 +7.334131E-02 +1.456688E-03 +1.160968E-01 +3.233815E-03 +1.691663E-01 +6.456530E-03 +9.680810E-02 +2.256338E-03 +2.856450E-01 +1.824185E-02 +1.384074E-01 +3.949804E-03 +1.751677E-01 +7.108034E-03 +3.363588E-01 +2.342988E-02 +1.444278E-01 +4.523981E-03 +1.609454E-01 +6.174116E-03 +1.254059E-01 +4.145686E-03 +7.125168E-02 +1.412152E-03 diff --git a/tests/regression_tests/filter_distribcell/case-3/results_true.dat b/tests/regression_tests/filter_distribcell/case-3/results_true.dat index f30e858f06..77f2a2a873 100644 --- a/tests/regression_tests/filter_distribcell/case-3/results_true.dat +++ b/tests/regression_tests/filter_distribcell/case-3/results_true.dat @@ -1 +1 @@ -1d09084dc41305687d53d1e800fb3d0ac3949aa4e1cb0bfbb327d0ec1ad4b74fc97ee73da84b910529296b858aab9b8a5d0924d17ca2cc373625e1a9e197aa94 \ No newline at end of file +93c1efbc586874a715982d26609e9e79232de25a0b73093a00938d658440644f0ee6bb823902a6ef1b7a2a855e67b2da0a0e767ef550f9ffa4dea723e35af6f5 \ No newline at end of file diff --git a/tests/regression_tests/filter_distribcell/case-4/results_true.dat b/tests/regression_tests/filter_distribcell/case-4/results_true.dat index 228456c58b..ed84838ee4 100644 --- a/tests/regression_tests/filter_distribcell/case-4/results_true.dat +++ b/tests/regression_tests/filter_distribcell/case-4/results_true.dat @@ -1,12 +1,12 @@ k-combined: -1.068596E-01 INF +1.069692E-01 INF tally 1: 1.812612E-02 3.285561E-04 2.870442E-02 8.239436E-04 -1.807689E-02 -3.267740E-04 +1.824058E-02 +3.327188E-04 2.660796E-02 7.079835E-04 1.961572E-02 diff --git a/tests/regression_tests/filter_energyfun/results_true.dat b/tests/regression_tests/filter_energyfun/results_true.dat index 0aadac82e9..d64de58a69 100644 --- a/tests/regression_tests/filter_energyfun/results_true.dat +++ b/tests/regression_tests/filter_energyfun/results_true.dat @@ -1,10 +1,10 @@ energyfunction nuclide score mean std. dev. -0 448ee8dfd19c4f Am241 ((n,gamma) / (n,gamma)) 1.74e-01 6.83e-03 +0 448ee8dfd19c4f Am241 ((n,gamma) / (n,gamma)) 1.74e-01 5.44e-03 energyfunction nuclide score mean std. dev. -0 37e006ae6b2e74 Am241 (n,gamma) 8.16e-02 2.24e-03 +0 37e006ae6b2e74 Am241 (n,gamma) 8.35e-02 1.83e-03 energyfunction nuclide score mean std. dev. -0 b4e2ac84068d2d Am241 (n,gamma) 8.19e-02 2.25e-03 +0 b4e2ac84068d2d Am241 (n,gamma) 8.39e-02 1.84e-03 energyfunction nuclide score mean std. dev. -0 dacf88242512ea Am241 (n,gamma) 7.95e-02 2.19e-03 +0 dacf88242512ea Am241 (n,gamma) 8.14e-02 1.78e-03 energyfunction nuclide score mean std. dev. -0 fe168c70d9e078 Am241 (n,gamma) 1.06e-01 2.96e-03 +0 fe168c70d9e078 Am241 (n,gamma) 1.09e-01 2.41e-03 diff --git a/tests/regression_tests/filter_mesh/results_true.dat b/tests/regression_tests/filter_mesh/results_true.dat index a91eadb356..34e99c17e2 100644 --- a/tests/regression_tests/filter_mesh/results_true.dat +++ b/tests/regression_tests/filter_mesh/results_true.dat @@ -1 +1 @@ -bd55ee25094f9ad04fda4439f58ef0fed718632c88b9fde411a484dc624dedcd45dee643e14d8b107d8b92757737b8bb3d9a667de5482457d6d8346afffdf657 \ No newline at end of file +e07ed2bc8893c69721abf61b123336f1f6128a3bee6ec63b84d1f549f31707a74a6ce885091ccc0eac6b7f16f7cab39ede4784584c08825829e108de878ea5fb \ No newline at end of file diff --git a/tests/regression_tests/filter_musurface/results_true.dat b/tests/regression_tests/filter_musurface/results_true.dat index 39c9f2b925..4cdd7dbf50 100644 --- a/tests/regression_tests/filter_musurface/results_true.dat +++ b/tests/regression_tests/filter_musurface/results_true.dat @@ -1,11 +1,11 @@ k-combined: -1.157005E-01 7.587090E-03 +1.202075E-01 1.113188E-02 tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -8.770000E-01 -1.608710E-01 -3.909000E+00 -3.063035E+00 +9.230000E-01 +1.791510E-01 +3.869000E+00 +3.002523E+00 diff --git a/tests/regression_tests/filter_translations/results_true.dat b/tests/regression_tests/filter_translations/results_true.dat index d257d71a69..a63586d2dd 100644 --- a/tests/regression_tests/filter_translations/results_true.dat +++ b/tests/regression_tests/filter_translations/results_true.dat @@ -1,342 +1,342 @@ k-combined: -2.298294E-01 3.256961E-01 +7.729082E-01 3.775399E-02 tally 1: -4.880089E-02 -4.894233E-04 -8.221192E-02 -1.373712E-03 -5.205261E-02 -5.584673E-04 -1.272758E-01 -3.371623E-03 -3.599375E-01 -2.655645E-02 -1.377572E-01 -3.835778E-03 -1.646205E-01 -5.916595E-03 -3.806765E-01 -2.947576E-02 -1.470573E-01 -4.360385E-03 -5.568294E-02 -6.368003E-04 -6.775790E-02 -9.447074E-04 -5.580909E-02 -6.303584E-04 -6.674847E-02 -9.080853E-04 -9.747628E-02 -1.934325E-03 -6.824062E-02 -9.908844E-04 -1.891692E-01 -7.211874E-03 -5.976566E-01 -7.206211E-02 -1.805640E-01 -6.599680E-03 -2.114692E-01 -9.202185E-03 -6.514433E-01 -8.523087E-02 -1.905740E-01 -7.287607E-03 -7.633486E-02 -1.216488E-03 -1.117747E-01 -2.538705E-03 -7.438042E-02 -1.127109E-03 -7.356007E-02 -1.090617E-03 -1.161258E-01 -2.734941E-03 -6.745417E-02 -9.371031E-04 -2.153323E-01 -9.293477E-03 -9.414362E-01 -2.261845E-01 -2.016933E-01 -8.270477E-03 -2.370758E-01 -1.150628E-02 -9.973982E-01 -2.489516E-01 -2.152505E-01 -9.424546E-03 -7.502684E-02 -1.208304E-03 -1.244515E-01 -3.168682E-03 -7.515812E-02 -1.151397E-03 -6.355178E-02 -8.423316E-04 -1.040915E-01 -2.224064E-03 -6.902234E-02 -9.843766E-04 -1.978591E-01 -7.894161E-03 -5.162186E-01 -5.357742E-02 -1.897326E-01 -7.231935E-03 -1.827950E-01 -6.839560E-03 -5.780661E-01 -6.799910E-02 -1.881215E-01 -7.093746E-03 -6.083700E-02 -7.861240E-04 -9.978991E-02 -2.022733E-03 -6.004653E-02 -7.428556E-04 -4.951220E-02 -4.952385E-04 -7.401227E-02 -1.124154E-03 -5.151090E-02 -5.339359E-04 -1.356118E-01 -3.711749E-03 -3.400140E-01 -2.367518E-02 -1.385305E-01 -4.060592E-03 -1.438711E-01 -4.191824E-03 -3.276170E-01 -2.210924E-02 -1.279501E-01 -3.435254E-03 -4.852204E-02 -4.919417E-04 -7.229090E-02 -1.062894E-03 -4.344414E-02 -3.825354E-04 +5.296804E-02 +5.661701E-04 +8.356446E-02 +1.412139E-03 +5.041335E-02 +5.143568E-04 +1.299348E-01 +3.467618E-03 +3.929702E-01 +3.147038E-02 +1.379707E-01 +3.888484E-03 +1.405034E-01 +4.473799E-03 +3.785796E-01 +2.940585E-02 +1.422010E-01 +4.113723E-03 +5.647073E-02 +6.735251E-04 +7.911154E-02 +1.329137E-03 +5.160755E-02 +5.361448E-04 +6.669424E-02 +9.090832E-04 +1.008621E-01 +2.134534E-03 +6.808932E-02 +9.355993E-04 +1.873006E-01 +7.135961E-03 +6.221575E-01 +7.819842E-02 +1.856653E-01 +6.954762E-03 +2.014929E-01 +8.327845E-03 +5.853251E-01 +6.945708E-02 +1.709645E-01 +5.917124E-03 +7.214913E-02 +1.058962E-03 +1.027720E-01 +2.138475E-03 +6.099853E-02 +7.493941E-04 +6.892071E-02 +9.630680E-04 +1.035459E-01 +2.173883E-03 +6.973870E-02 +9.904237E-04 +2.125703E-01 +9.112659E-03 +9.012205E-01 +2.163546E-01 +2.066426E-01 +8.617414E-03 +2.258950E-01 +1.039607E-02 +9.476792E-01 +2.350708E-01 +2.225585E-01 +1.017898E-02 +7.111503E-02 +1.036847E-03 +1.117012E-01 +2.530040E-03 +6.870474E-02 +9.551035E-04 +5.738897E-02 +6.699030E-04 +9.522335E-02 +1.835769E-03 +6.570917E-02 +8.656870E-04 +1.945592E-01 +7.593336E-03 +5.514753E-01 +6.122981E-02 +2.144202E-01 +9.421739E-03 +1.971631E-01 +7.944046E-03 +6.088996E-01 +7.442954E-02 +1.965447E-01 +7.765628E-03 +7.005494E-02 +1.012891E-03 +1.010633E-01 +2.084095E-03 +6.145926E-02 +7.694351E-04 +4.999479E-02 +5.129164E-04 +7.238243E-02 +1.062921E-03 +4.902309E-02 +4.852193E-04 +1.324655E-01 +3.642431E-03 +3.305312E-01 +2.265726E-02 +1.332993E-01 +3.728385E-03 +1.547469E-01 +4.894837E-03 +3.625944E-01 +2.747313E-02 +1.435761E-01 +4.334405E-03 +5.789603E-02 +7.065383E-04 +7.589559E-02 +1.205386E-03 +5.210018E-02 +5.790843E-04 tally 2: -2.379877E-01 -1.141258E-02 -2.376600E-01 -1.137350E-02 -6.546514E-01 -8.852321E-02 -5.823862E-01 -6.810779E-02 -2.692631E-01 -1.479426E-02 -2.360469E-01 -1.124950E-02 -3.534788E-01 -2.528363E-02 -3.247931E-01 -2.160130E-02 -1.181513E+00 -2.959140E-01 -1.078874E+00 -2.467321E-01 -3.743375E-01 -2.859905E-02 -3.468123E-01 -2.427809E-02 -3.203903E-01 -2.109786E-02 -3.315547E-01 -2.216053E-02 -1.039077E+00 -2.294722E-01 -1.091786E+00 -2.572834E-01 -3.615960E-01 -2.678347E-02 -3.323317E-01 -2.226424E-02 -2.519726E-01 -1.279098E-02 -2.332385E-01 -1.101251E-02 -5.587247E-01 -6.293355E-02 -5.426859E-01 -6.010041E-02 -2.332981E-01 -1.097940E-02 -2.239951E-01 -1.043440E-02 +2.572693E-01 +1.338921E-02 +2.567576E-01 +1.333558E-02 +6.127899E-01 +7.781914E-02 +6.163075E-01 +7.600273E-02 +2.566545E-01 +1.372553E-02 +2.509744E-01 +1.286275E-02 +3.366720E-01 +2.282560E-02 +3.216175E-01 +2.103222E-02 +1.118187E+00 +2.697988E-01 +1.050003E+00 +2.391098E-01 +3.407360E-01 +2.332214E-02 +3.150094E-01 +2.006040E-02 +3.130223E-01 +2.001074E-02 +3.238651E-01 +2.101351E-02 +1.061186E+00 +2.372828E-01 +1.099461E+00 +2.597134E-01 +3.445524E-01 +2.400393E-02 +3.429055E-01 +2.372392E-02 +2.299776E-01 +1.064851E-02 +2.208901E-01 +9.829109E-03 +6.015657E-01 +7.399276E-02 +5.851229E-01 +7.165716E-02 +2.583609E-01 +1.364046E-02 +2.456380E-01 +1.257735E-02 tally 3: -4.880089E-02 -4.894233E-04 -8.221192E-02 -1.373712E-03 -5.205261E-02 -5.584673E-04 -1.272758E-01 -3.371623E-03 -3.599375E-01 -2.655645E-02 -1.377572E-01 -3.835778E-03 -1.646205E-01 -5.916595E-03 -3.806765E-01 -2.947576E-02 -1.470573E-01 -4.360385E-03 -5.568294E-02 -6.368003E-04 -6.775790E-02 -9.447074E-04 -5.580909E-02 -6.303584E-04 -6.674847E-02 -9.080853E-04 -9.747628E-02 -1.934325E-03 -6.824062E-02 -9.908844E-04 -1.891692E-01 -7.211874E-03 -5.976566E-01 -7.206211E-02 -1.805640E-01 -6.599680E-03 -2.114692E-01 -9.202185E-03 -6.514433E-01 -8.523087E-02 -1.905740E-01 -7.287607E-03 -7.633486E-02 -1.216488E-03 -1.117747E-01 -2.538705E-03 -7.438042E-02 -1.127109E-03 -7.356007E-02 -1.090617E-03 -1.161258E-01 -2.734941E-03 -6.745417E-02 -9.371031E-04 -2.153323E-01 -9.293477E-03 -9.414362E-01 -2.261845E-01 -2.016933E-01 -8.270477E-03 -2.370758E-01 -1.150628E-02 -9.973982E-01 -2.489516E-01 -2.152505E-01 -9.424546E-03 -7.502684E-02 -1.208304E-03 -1.244515E-01 -3.168682E-03 -7.515812E-02 -1.151397E-03 -6.355178E-02 -8.423316E-04 -1.040915E-01 -2.224064E-03 -6.902234E-02 -9.843766E-04 -1.978591E-01 -7.894161E-03 -5.162186E-01 -5.357742E-02 -1.897326E-01 -7.231935E-03 -1.827950E-01 -6.839560E-03 -5.780661E-01 -6.799910E-02 -1.881215E-01 -7.093746E-03 -6.083700E-02 -7.861240E-04 -9.978991E-02 -2.022733E-03 -6.004653E-02 -7.428556E-04 -4.951220E-02 -4.952385E-04 -7.401227E-02 -1.124154E-03 -5.151090E-02 -5.339359E-04 -1.356118E-01 -3.711749E-03 -3.400140E-01 -2.367518E-02 -1.385305E-01 -4.060592E-03 -1.438711E-01 -4.191824E-03 -3.276170E-01 -2.210924E-02 -1.279501E-01 -3.435254E-03 -4.852204E-02 -4.919417E-04 -7.229090E-02 -1.062894E-03 -4.344414E-02 -3.825354E-04 +5.296804E-02 +5.661701E-04 +8.356446E-02 +1.412139E-03 +5.041335E-02 +5.143568E-04 +1.299348E-01 +3.467618E-03 +3.929702E-01 +3.147038E-02 +1.379707E-01 +3.888484E-03 +1.405034E-01 +4.473799E-03 +3.785796E-01 +2.940585E-02 +1.422010E-01 +4.113723E-03 +5.647073E-02 +6.735251E-04 +7.911154E-02 +1.329137E-03 +5.160755E-02 +5.361448E-04 +6.669424E-02 +9.090832E-04 +1.008621E-01 +2.134534E-03 +6.808932E-02 +9.355993E-04 +1.873006E-01 +7.135961E-03 +6.221575E-01 +7.819842E-02 +1.856653E-01 +6.954762E-03 +2.014929E-01 +8.327845E-03 +5.853251E-01 +6.945708E-02 +1.709645E-01 +5.917124E-03 +7.214913E-02 +1.058962E-03 +1.027720E-01 +2.138475E-03 +6.099853E-02 +7.493941E-04 +6.892071E-02 +9.630680E-04 +1.035459E-01 +2.173883E-03 +6.973870E-02 +9.904237E-04 +2.125703E-01 +9.112659E-03 +9.012205E-01 +2.163546E-01 +2.066426E-01 +8.617414E-03 +2.258950E-01 +1.039607E-02 +9.476792E-01 +2.350708E-01 +2.225585E-01 +1.017898E-02 +7.111503E-02 +1.036847E-03 +1.117012E-01 +2.530040E-03 +6.870474E-02 +9.551035E-04 +5.738897E-02 +6.699030E-04 +9.522335E-02 +1.835769E-03 +6.570917E-02 +8.656870E-04 +1.945592E-01 +7.593336E-03 +5.514753E-01 +6.122981E-02 +2.144202E-01 +9.421739E-03 +1.971631E-01 +7.944046E-03 +6.088996E-01 +7.442954E-02 +1.965447E-01 +7.765628E-03 +7.005494E-02 +1.012891E-03 +1.010633E-01 +2.084095E-03 +6.145926E-02 +7.694351E-04 +4.999479E-02 +5.129164E-04 +7.238243E-02 +1.062921E-03 +4.902309E-02 +4.852193E-04 +1.324655E-01 +3.642431E-03 +3.305312E-01 +2.265726E-02 +1.332993E-01 +3.728385E-03 +1.547469E-01 +4.894837E-03 +3.625944E-01 +2.747313E-02 +1.435761E-01 +4.334405E-03 +5.789603E-02 +7.065383E-04 +7.589559E-02 +1.205386E-03 +5.210018E-02 +5.790843E-04 tally 4: -2.379877E-01 -1.141258E-02 -2.376600E-01 -1.137350E-02 -6.546514E-01 -8.852321E-02 -5.823862E-01 -6.810779E-02 -2.692631E-01 -1.479426E-02 -2.360469E-01 -1.124950E-02 -3.534788E-01 -2.528363E-02 -3.247931E-01 -2.160130E-02 -1.181513E+00 -2.959140E-01 -1.078874E+00 -2.467321E-01 -3.743375E-01 -2.859905E-02 -3.468123E-01 -2.427809E-02 -3.203903E-01 -2.109786E-02 -3.315547E-01 -2.216053E-02 -1.039077E+00 -2.294722E-01 -1.091786E+00 -2.572834E-01 -3.615960E-01 -2.678347E-02 -3.323317E-01 -2.226424E-02 -2.519726E-01 -1.279098E-02 -2.332385E-01 -1.101251E-02 -5.587247E-01 -6.293355E-02 -5.426859E-01 -6.010041E-02 -2.332981E-01 -1.097940E-02 -2.239951E-01 -1.043440E-02 +2.572693E-01 +1.338921E-02 +2.567576E-01 +1.333558E-02 +6.127899E-01 +7.781914E-02 +6.163075E-01 +7.600273E-02 +2.566545E-01 +1.372553E-02 +2.509744E-01 +1.286275E-02 +3.366720E-01 +2.282560E-02 +3.216175E-01 +2.103222E-02 +1.118187E+00 +2.697988E-01 +1.050003E+00 +2.391098E-01 +3.407360E-01 +2.332214E-02 +3.150094E-01 +2.006040E-02 +3.130223E-01 +2.001074E-02 +3.238651E-01 +2.101351E-02 +1.061186E+00 +2.372828E-01 +1.099461E+00 +2.597134E-01 +3.445524E-01 +2.400393E-02 +3.429055E-01 +2.372392E-02 +2.299776E-01 +1.064851E-02 +2.208901E-01 +9.829109E-03 +6.015657E-01 +7.399276E-02 +5.851229E-01 +7.165716E-02 +2.583609E-01 +1.364046E-02 +2.456380E-01 +1.257735E-02 diff --git a/tests/regression_tests/ifp/groupwise/__init__.py b/tests/regression_tests/ifp/groupwise/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/ifp/groupwise/inputs_true.dat b/tests/regression_tests/ifp/groupwise/inputs_true.dat new file mode 100644 index 0000000000..6d7e20717b --- /dev/null +++ b/tests/regression_tests/ifp/groupwise/inputs_true.dat @@ -0,0 +1,43 @@ + + + + + + + + + + + + + + eigenvalue + 1000 + 20 + 5 + + + -10.0 -10.0 -10.0 10.0 10.0 10.0 + + + true + + + 5 + + + + 1 2 3 4 5 6 + + + ifp-time-numerator + + + 1 + ifp-beta-numerator + + + ifp-denominator + + + diff --git a/tests/regression_tests/ifp/groupwise/results_true.dat b/tests/regression_tests/ifp/groupwise/results_true.dat new file mode 100644 index 0000000000..ea66a8de3c --- /dev/null +++ b/tests/regression_tests/ifp/groupwise/results_true.dat @@ -0,0 +1,21 @@ +k-combined: +1.006559E+00 5.389391E-03 +tally 1: +9.109384E-08 +5.667165E-16 +tally 2: +3.000000E-03 +9.000000E-06 +0.000000E+00 +0.000000E+00 +2.100000E-02 +1.370000E-04 +2.800000E-02 +2.220000E-04 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +tally 3: +1.489000E+01 +1.480036E+01 diff --git a/tests/regression_tests/ifp/groupwise/test.py b/tests/regression_tests/ifp/groupwise/test.py new file mode 100644 index 0000000000..a1a0ebefb8 --- /dev/null +++ b/tests/regression_tests/ifp/groupwise/test.py @@ -0,0 +1,40 @@ +"""Test the Iterated Fission Probability (IFP) method to compute adjoint-weighted +kinetics parameters using dedicated tallies.""" + +import openmc +import pytest + +from tests.testing_harness import PyAPITestHarness + +@pytest.fixture() +def ifp_model(): + # Material + material = openmc.Material(name="core") + material.add_nuclide("U235", 1.0) + material.set_density('g/cm3', 16.0) + + # Geometry + radius = 10.0 + sphere = openmc.Sphere(r=radius, boundary_type="vacuum") + cell = openmc.Cell(region=-sphere, fill=material) + geometry = openmc.Geometry([cell]) + + # Settings + settings = openmc.Settings() + settings.particles = 1000 + settings.batches = 20 + settings.inactive = 5 + settings.ifp_n_generation = 5 + + model = openmc.Model(settings=settings, geometry=geometry) + + space = openmc.stats.Box(*cell.bounding_box) + model.settings.source = openmc.IndependentSource( + space=space, constraints={'fissionable': True}) + model.add_kinetics_parameters_tallies(num_groups=6) + return model + + +def test_iterated_fission_probability(ifp_model): + harness = PyAPITestHarness("statepoint.20.h5", model=ifp_model) + harness.main() diff --git a/tests/regression_tests/ifp/results_true.dat b/tests/regression_tests/ifp/results_true.dat deleted file mode 100644 index a74e2bd78b..0000000000 --- a/tests/regression_tests/ifp/results_true.dat +++ /dev/null @@ -1,9 +0,0 @@ -k-combined: -1.007452E+00 5.705278E-03 -tally 1: -8.996235E-08 -5.461421E-16 -4.800000E-02 -4.680000E-04 -1.512000E+01 -1.526063E+01 diff --git a/tests/regression_tests/ifp/total/__init__.py b/tests/regression_tests/ifp/total/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/ifp/inputs_true.dat b/tests/regression_tests/ifp/total/inputs_true.dat similarity index 100% rename from tests/regression_tests/ifp/inputs_true.dat rename to tests/regression_tests/ifp/total/inputs_true.dat diff --git a/tests/regression_tests/ifp/total/results_true.dat b/tests/regression_tests/ifp/total/results_true.dat new file mode 100644 index 0000000000..466ca1f015 --- /dev/null +++ b/tests/regression_tests/ifp/total/results_true.dat @@ -0,0 +1,9 @@ +k-combined: +1.006559E+00 5.389391E-03 +tally 1: +9.109384E-08 +5.667165E-16 +5.200000E-02 +5.420000E-04 +1.489000E+01 +1.480036E+01 diff --git a/tests/regression_tests/ifp/test.py b/tests/regression_tests/ifp/total/test.py similarity index 99% rename from tests/regression_tests/ifp/test.py rename to tests/regression_tests/ifp/total/test.py index 6969a54c49..18b89cfc0b 100644 --- a/tests/regression_tests/ifp/test.py +++ b/tests/regression_tests/ifp/total/test.py @@ -6,7 +6,6 @@ import pytest from tests.testing_harness import PyAPITestHarness - @pytest.fixture() def ifp_model(): model = openmc.Model() diff --git a/tests/regression_tests/infinite_cell/results_true.dat b/tests/regression_tests/infinite_cell/results_true.dat index 2c4ce082d5..4cdbcaf887 100644 --- a/tests/regression_tests/infinite_cell/results_true.dat +++ b/tests/regression_tests/infinite_cell/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.589951E-02 8.489144E-04 +9.603664E-02 1.050772E-03 diff --git a/tests/regression_tests/iso_in_lab/results_true.dat b/tests/regression_tests/iso_in_lab/results_true.dat index aaef226234..0378ec86dc 100644 --- a/tests/regression_tests/iso_in_lab/results_true.dat +++ b/tests/regression_tests/iso_in_lab/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.015537E-01 1.086850E-01 +9.365837E-01 5.366122E-02 diff --git a/tests/regression_tests/lattice/results_true.dat b/tests/regression_tests/lattice/results_true.dat index f3e937b36e..dca84bd6a5 100644 --- a/tests/regression_tests/lattice/results_true.dat +++ b/tests/regression_tests/lattice/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.610829E-01 2.522714E-02 +9.182679E-01 5.270201E-02 diff --git a/tests/regression_tests/lattice_distribmat/False/results_true.dat b/tests/regression_tests/lattice_distribmat/False/results_true.dat index 45a9ddb0a6..9ebbb43b83 100644 --- a/tests/regression_tests/lattice_distribmat/False/results_true.dat +++ b/tests/regression_tests/lattice_distribmat/False/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.863277E+00 1.289821E-02 +1.848895E+00 1.480242E-02 diff --git a/tests/regression_tests/lattice_distribmat/True/results_true.dat b/tests/regression_tests/lattice_distribmat/True/results_true.dat index 45a9ddb0a6..9ebbb43b83 100644 --- a/tests/regression_tests/lattice_distribmat/True/results_true.dat +++ b/tests/regression_tests/lattice_distribmat/True/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.863277E+00 1.289821E-02 +1.848895E+00 1.480242E-02 diff --git a/tests/regression_tests/lattice_distribrho/__init__.py b/tests/regression_tests/lattice_distribrho/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/lattice_distribrho/inputs_true.dat b/tests/regression_tests/lattice_distribrho/inputs_true.dat new file mode 100644 index 0000000000..5031bea6e2 --- /dev/null +++ b/tests/regression_tests/lattice_distribrho/inputs_true.dat @@ -0,0 +1,40 @@ + + + + + + + + + + + + + + + + + + + + + 1.0 1.0 + 2 2 + -1.0 -1.0 + +1 1 +1 1 + + + + + + + + + eigenvalue + 1000 + 10 + 5 + + diff --git a/tests/regression_tests/lattice_distribrho/results_true.dat b/tests/regression_tests/lattice_distribrho/results_true.dat new file mode 100644 index 0000000000..f7f3da8e65 --- /dev/null +++ b/tests/regression_tests/lattice_distribrho/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +1.900249E+00 8.157834E-03 diff --git a/tests/regression_tests/lattice_distribrho/test.py b/tests/regression_tests/lattice_distribrho/test.py new file mode 100644 index 0000000000..ec94fe96b8 --- /dev/null +++ b/tests/regression_tests/lattice_distribrho/test.py @@ -0,0 +1,51 @@ +import openmc +import pytest + +from tests.testing_harness import PyAPITestHarness + + +@pytest.fixture +def model(): + model = openmc.Model() + + uo2 = openmc.Material(name='UO2') + uo2.set_density('g/cm3', 10.0) + uo2.add_nuclide('U235', 1.0) + uo2.add_nuclide('O16', 2.0) + water = openmc.Material(name='light water') + water.add_nuclide('H1', 2.0) + water.add_nuclide('O16', 1.0) + water.set_density('g/cm3', 1.0) + water.add_s_alpha_beta('c_H_in_H2O') + model.materials.extend([uo2, water]) + + cyl = openmc.ZCylinder(r=0.4) + pin = openmc.model.pin([cyl], [uo2, water]) + d = 1.0 + + lattice = openmc.RectLattice() + lattice.lower_left = (-d, -d) + lattice.pitch = (d, d) + lattice.universes = [[pin, pin], + [pin, pin]] + box = openmc.model.RectangularPrism( + 2.0 * d, 2.0 * d, + origin=(0.0, 0.0), + boundary_type='reflective' + ) + + pin.cells[1].density = [10.0, 20.0, 10.0, 20.0] + + model.geometry = openmc.Geometry([openmc.Cell(fill=lattice, region=-box)]) + model.geometry.merge_surfaces = True + + model.settings.batches = 10 + model.settings.inactive = 5 + model.settings.particles = 1000 + + return model + + +def test_lattice_checkerboard(model): + harness = PyAPITestHarness('statepoint.10.h5', model) + harness.main() diff --git a/tests/regression_tests/lattice_hex/results_true.dat b/tests/regression_tests/lattice_hex/results_true.dat index 789bacc404..46db641ebe 100644 --- a/tests/regression_tests/lattice_hex/results_true.dat +++ b/tests/regression_tests/lattice_hex/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.566607E-01 9.207770E-03 +2.595598E-01 9.089294E-03 diff --git a/tests/regression_tests/lattice_hex_coincident/results_true.dat b/tests/regression_tests/lattice_hex_coincident/results_true.dat index c134e123f9..c798b66e40 100644 --- a/tests/regression_tests/lattice_hex_coincident/results_true.dat +++ b/tests/regression_tests/lattice_hex_coincident/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.917792E+00 4.329425E-02 +1.931086E+00 5.968486E-02 diff --git a/tests/regression_tests/lattice_hex_x/results_true.dat b/tests/regression_tests/lattice_hex_x/results_true.dat index 174dc70cd4..44f947283c 100644 --- a/tests/regression_tests/lattice_hex_x/results_true.dat +++ b/tests/regression_tests/lattice_hex_x/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.367975E+00 2.264887E-02 +1.326294E+00 1.193578E-02 diff --git a/tests/regression_tests/lattice_multiple/results_true.dat b/tests/regression_tests/lattice_multiple/results_true.dat index 7a06551bd8..0866932d2a 100644 --- a/tests/regression_tests/lattice_multiple/results_true.dat +++ b/tests/regression_tests/lattice_multiple/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.859911E+00 8.282311E-03 +1.843982E+00 5.815875E-03 diff --git a/tests/regression_tests/lattice_rotated/results_true.dat b/tests/regression_tests/lattice_rotated/results_true.dat index eeaa268fb1..9a96a92594 100644 --- a/tests/regression_tests/lattice_rotated/results_true.dat +++ b/tests/regression_tests/lattice_rotated/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.426784E-01 6.627506E-03 +4.515246E-01 2.358354E-02 diff --git a/tests/regression_tests/mg_basic/results_true.dat b/tests/regression_tests/mg_basic/results_true.dat index 15a9f21868..16980732db 100644 --- a/tests/regression_tests/mg_basic/results_true.dat +++ b/tests/regression_tests/mg_basic/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.009864E+00 1.107115E-02 +1.004679E+00 1.329350E-02 diff --git a/tests/regression_tests/mg_basic_delayed/results_true.dat b/tests/regression_tests/mg_basic_delayed/results_true.dat index 6f7c79c1b2..f150030b9b 100644 --- a/tests/regression_tests/mg_basic_delayed/results_true.dat +++ b/tests/regression_tests/mg_basic_delayed/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.024610E+00 9.643746E-03 +1.017078E+00 1.181139E-02 diff --git a/tests/regression_tests/mg_convert/results_true.dat b/tests/regression_tests/mg_convert/results_true.dat index ff3d7bb913..f8f748cc7c 100644 --- a/tests/regression_tests/mg_convert/results_true.dat +++ b/tests/regression_tests/mg_convert/results_true.dat @@ -1,24 +1,24 @@ k-combined: -9.984888E-01 1.558301E-03 +9.926427E-01 3.067527E-03 k-combined: -1.001035E+00 7.622447E-04 +9.932868E-01 2.780271E-03 k-combined: -9.984888E-01 1.558301E-03 +9.926427E-01 3.067527E-03 k-combined: -9.991101E-01 2.776191E-03 +1.000000E+00 0.000000E+00 k-combined: -9.965954E-01 5.185046E-03 +9.902969E-01 1.654717E-02 k-combined: -9.987613E-01 4.806845E-04 +9.882796E-01 1.929843E-03 k-combined: -9.991101E-01 2.776191E-03 +1.000000E+00 0.000000E+00 k-combined: -9.965954E-01 5.185315E-03 +9.902953E-01 1.654291E-02 k-combined: -9.987610E-01 4.791528E-04 +9.882814E-01 1.927488E-03 k-combined: -9.944808E-01 4.458524E-03 +9.893153E-01 7.576652E-03 k-combined: -9.984888E-01 1.558301E-03 +9.926427E-01 3.067527E-03 k-combined: -9.984888E-01 1.558301E-03 +9.926427E-01 3.067527E-03 diff --git a/tests/regression_tests/mg_convert/test.py b/tests/regression_tests/mg_convert/test.py index 8099c89a29..0e50f3a744 100755 --- a/tests/regression_tests/mg_convert/test.py +++ b/tests/regression_tests/mg_convert/test.py @@ -1,3 +1,4 @@ +from math import isnan import os import hashlib @@ -142,10 +143,13 @@ class MGXSTestHarness(PyAPITestHarness): openmc.run(openmc_exec=config['exe']) with openmc.StatePoint('statepoint.{}.h5'.format(batches)) as sp: + # Sometimes NaN results are produced; convert these to 0.0 + std_dev = 0.0 if isnan(sp.keff.s) else sp.keff.s + # Write out k-combined. outstr += 'k-combined:\n' form = '{:12.6E} {:12.6E}\n' - outstr += form.format(sp.keff.n, sp.keff.s) + outstr += form.format(sp.keff.n, std_dev) return outstr diff --git a/tests/regression_tests/mg_legendre/results_true.dat b/tests/regression_tests/mg_legendre/results_true.dat index e2989469c8..04d9c9874b 100644 --- a/tests/regression_tests/mg_legendre/results_true.dat +++ b/tests/regression_tests/mg_legendre/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.003646E+00 9.134747E-03 +1.009220E+00 9.571832E-03 diff --git a/tests/regression_tests/mg_max_order/results_true.dat b/tests/regression_tests/mg_max_order/results_true.dat index e2989469c8..04d9c9874b 100644 --- a/tests/regression_tests/mg_max_order/results_true.dat +++ b/tests/regression_tests/mg_max_order/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.003646E+00 9.134747E-03 +1.009220E+00 9.571832E-03 diff --git a/tests/regression_tests/mg_survival_biasing/results_true.dat b/tests/regression_tests/mg_survival_biasing/results_true.dat index cddbdaceb3..4b26978ada 100644 --- a/tests/regression_tests/mg_survival_biasing/results_true.dat +++ b/tests/regression_tests/mg_survival_biasing/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.878738E-01 8.326224E-03 +9.889968E-01 9.144186E-03 diff --git a/tests/regression_tests/mg_tallies/results_true.dat b/tests/regression_tests/mg_tallies/results_true.dat index 7484dd2485..07fe22ce50 100644 --- a/tests/regression_tests/mg_tallies/results_true.dat +++ b/tests/regression_tests/mg_tallies/results_true.dat @@ -1,1324 +1,1324 @@ k-combined: -1.003646E+00 9.134747E-03 +1.012390E+00 9.679132E-03 tally 1: -5.220000E-01 -5.995400E-02 -1.400000E-02 -4.000000E-05 -6.718865E-03 -9.371695E-06 -1.106435E-02 -3.119729E-05 -1.216992E-07 -3.699412E-15 -1.106435E-02 -3.119729E-05 +1.342000E+00 +4.291640E-01 +7.000000E-02 +1.158000E-03 +2.919844E-02 +1.953371E-04 +5.372246E-02 +6.734832E-04 +2.939310E-07 +2.375686E-14 +5.372246E-02 +6.734832E-04 0.000000E+00 0.000000E+00 -1.343773E+06 -3.748678E+11 -5.220000E-01 -5.995400E-02 +5.839688E+06 +7.813485E+12 +1.342000E+00 +4.291640E-01 0.000000E+00 0.000000E+00 -1.520872E+00 -5.121226E-01 -2.564000E+00 -1.338762E+00 -1.160000E-01 -2.738000E-03 -4.593685E-02 -4.275719E-04 -1.360763E-01 -3.951569E-03 -8.079937E-07 -1.577355E-13 -1.350645E-01 -3.872739E-03 -1.011813E-03 -1.023765E-06 -9.187371E+06 -1.710288E+13 -2.564000E+00 -1.338762E+00 -8.595248E-04 -7.387829E-07 -7.412367E+00 -1.121746E+01 -2.184000E+00 -9.895940E-01 -1.080000E-01 -2.394000E-03 -4.782785E-02 -4.787428E-04 -1.140806E-01 -2.886440E-03 -6.242229E-07 -9.307161E-14 -1.130687E-01 -2.811706E-03 -1.011813E-03 -1.023765E-06 -9.565570E+06 -1.914971E+13 -2.184000E+00 -9.895940E-01 -3.312574E-05 -1.097314E-09 -6.331465E+00 -8.328826E+00 -5.970000E-01 -8.325100E-02 -3.500000E-02 -3.150000E-04 -1.514871E-02 -5.131352E-05 -3.795718E-02 -3.631435E-04 -2.299730E-07 -1.295603E-14 -3.795718E-02 -3.631435E-04 +3.915206E+00 +3.646810E+00 +2.701000E+00 +1.486587E+00 +1.340000E-01 +3.598000E-03 +5.583136E-02 +6.266530E-04 +1.267275E-01 +3.349463E-03 +7.209619E-07 +1.153253E-13 +1.267275E-01 +3.349463E-03 0.000000E+00 0.000000E+00 -3.029741E+06 -2.052541E+12 -5.970000E-01 -8.325100E-02 +1.116627E+07 +2.506612E+13 +2.701000E+00 +1.486587E+00 0.000000E+00 0.000000E+00 -1.714353E+00 -6.970480E-01 -1.852000E+00 -7.973360E-01 -7.900000E-02 -1.689000E-03 -2.755187E-02 -2.091740E-04 -5.453423E-02 -7.484037E-04 -2.368001E-07 -1.753710E-14 -5.453423E-02 -7.484037E-04 +7.844332E+00 +1.252301E+01 +2.791000E+00 +1.658877E+00 +1.240000E-01 +3.282000E-03 +5.173865E-02 +5.560435E-04 +1.292971E-01 +3.436301E-03 +6.920456E-07 +9.917496E-14 +1.263311E-01 +3.290664E-03 +2.965960E-03 +4.837204E-06 +1.034773E+07 +2.224174E+13 +2.791000E+00 +1.658877E+00 +7.133747E-04 +3.640977E-07 +8.120311E+00 +1.408288E+01 +3.169000E+00 +2.031747E+00 +1.620000E-01 +5.364000E-03 +6.707115E-02 +9.171975E-04 +1.648345E-01 +5.547084E-03 +1.008876E-06 +2.201766E-13 +1.638199E-01 +5.463700E-03 +1.014608E-03 +1.029429E-06 +1.341423E+07 +3.668790E+13 +3.169000E+00 +2.031747E+00 +8.618993E-04 +7.428703E-07 +9.158565E+00 +1.699756E+01 +3.660000E+00 +2.796494E+00 +1.580000E-01 +5.158000E-03 +6.719242E-02 +9.422093E-04 +1.591500E-01 +5.615224E-03 +8.020080E-07 +1.480166E-13 +1.581743E-01 +5.540021E-03 +9.756761E-04 +9.519438E-07 +1.343848E+07 +3.768837E+13 +3.660000E+00 +2.796494E+00 +2.954152E-04 +8.727014E-08 +1.067773E+01 +2.376726E+01 +2.527000E+00 +1.452369E+00 +1.140000E-01 +2.834000E-03 +4.984389E-02 +5.325247E-04 +1.111356E-01 +2.793586E-03 +7.289084E-07 +1.302125E-13 +1.111356E-01 +2.793586E-03 0.000000E+00 0.000000E+00 -5.510374E+06 -8.366961E+12 -1.852000E+00 -7.973360E-01 +9.968777E+06 +2.130099E+13 +2.527000E+00 +1.452369E+00 0.000000E+00 0.000000E+00 -5.449659E+00 -6.908544E+00 -4.177000E+00 -3.780409E+00 -1.760000E-01 -6.584000E-03 -7.049310E-02 -1.047700E-03 -2.082153E-01 -9.154274E-03 -1.090026E-06 -2.590031E-13 -2.082153E-01 -9.154274E-03 +7.323996E+00 +1.221424E+01 +3.204000E+00 +2.092834E+00 +1.500000E-01 +4.600000E-03 +6.029165E-02 +7.387235E-04 +1.410668E-01 +4.414885E-03 +8.384625E-07 +1.602532E-13 +1.400911E-01 +4.332066E-03 +9.756761E-04 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-2.765806E+00 -1.490000E-01 -4.587000E-03 -5.894825E-02 -7.367371E-04 -1.434581E-01 -4.305327E-03 -7.603618E-07 -1.250071E-13 -1.414758E-01 -4.212618E-03 -1.982273E-03 -1.965559E-06 -1.178965E+07 -2.946948E+13 -3.630000E+00 -2.765806E+00 -4.160428E-04 -1.012741E-07 -1.059988E+01 -2.359174E+01 +3.698633E-01 +4.679347E-02 tally 2: -5.033991E-01 -5.701830E-02 -2.304219E-02 -1.162005E-04 -9.376617E-03 -1.933443E-05 -2.344154E-02 -1.208402E-04 -1.277674E-07 -3.888071E-15 -2.329292E-02 -1.193128E-04 -1.486195E-04 -4.857250E-09 -1.875323E+06 -7.733771E+11 -5.220000E-01 -5.995400E-02 -6.963583E-05 -1.066362E-09 -1.463809E+00 -4.840945E-01 -2.621546E+00 -1.396717E+00 -1.276380E-01 -3.311549E-03 -5.565805E-02 -6.598224E-04 -1.391451E-01 -4.123890E-03 -8.331879E-07 -1.660597E-13 -1.382629E-01 -4.071765E-03 -8.821806E-04 -1.657624E-07 -1.113161E+07 -2.639289E+13 -2.581000E+00 -1.357455E+00 -4.133468E-04 -3.639153E-08 -7.576783E+00 -1.169599E+01 -2.230626E+00 -1.033217E+00 -1.065165E-01 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-5.020635E-05 -5.047241E-10 -5.009785E+00 -5.021429E+00 -3.196471E-02 -2.044235E-04 -4.033399E+08 -3.254855E+16 -1.092010E+02 -2.386227E+03 -1.497710E-02 -4.487918E-05 +1.098420E+02 +2.414277E+03 +5.008447E+00 +5.018748E+00 +2.028674E+00 +8.234818E-01 +5.071684E+00 +5.146761E+00 +5.050718E-05 +5.107669E-10 +5.039530E+00 +5.081707E+00 +3.215450E-02 +2.068774E-04 +4.057347E+08 +3.293927E+16 +1.098420E+02 +2.414277E+03 +1.506603E-02 +4.541792E-05 tally 15: -1.097121E+02 -2.408636E+03 -5.009145E+00 -5.019563E+00 -2.032191E+00 -8.264420E-01 -5.080477E+00 -5.165263E+00 -2.756641E-05 -1.523527E-10 -5.048267E+00 -5.099975E+00 -3.221025E-02 -2.076211E-04 -4.064382E+08 -3.305768E+16 -1.093810E+02 -2.394075E+03 -1.509215E-02 -4.558119E-05 +1.103689E+02 +2.437562E+03 +5.035611E+00 +5.073005E+00 +2.041209E+00 +8.337913E-01 +5.103022E+00 +5.211196E+00 +2.765405E-05 +1.532759E-10 +5.070669E+00 +5.145327E+00 +3.235318E-02 +2.094674E-04 +4.082417E+08 +3.335165E+16 +1.098580E+02 +2.414983E+03 +1.515912E-02 +4.598653E-05 tally 16: -1.042260E+02 -2.173864E+03 -1.042260E+02 -2.173864E+03 -5.000649E+00 -5.012321E+00 +1.048490E+02 +2.199887E+03 +1.048490E+02 +2.199887E+03 +5.037812E+00 +5.086734E+00 tally 17: -6.507000E+00 -8.478423E+00 -1.444000E+00 -4.172780E-01 -1.146407E+00 -2.630079E-01 -2.867025E+00 -1.647980E+00 -2.707153E-05 -1.467503E-10 -2.848880E+00 -1.627146E+00 -1.814469E-02 -6.685238E-05 -2.292814E+08 -1.052031E+16 -6.507000E+00 -8.478423E+00 -9.467712E-03 -2.396878E-05 -5.063000E+00 -5.136983E+00 -5.063000E+00 -5.136983E+00 -1.026940E+02 -2.110535E+03 +6.546000E+00 +8.579894E+00 +1.462000E+00 +4.278220E-01 +1.160697E+00 +2.696537E-01 +2.879845E+00 +1.663297E+00 +2.723379E-05 +1.485067E-10 +2.862628E+00 +1.643479E+00 +1.721726E-02 +6.055382E-05 +2.321395E+08 +1.078615E+16 +6.546000E+00 +8.579894E+00 +6.709978E-03 +1.387848E-05 +5.084000E+00 +5.178800E+00 +5.084000E+00 +5.178800E+00 +1.032960E+02 +2.135240E+03 3.531000E+00 -2.493861E+00 +2.493943E+00 8.630652E-01 -1.489924E-01 -2.133624E+00 -9.150435E-01 -2.183901E-07 -9.544829E-15 -2.115593E+00 -8.991467E-01 -1.803087E-02 -8.677353E-05 +1.489973E-01 +2.157967E+00 +9.345420E-01 +2.196703E-07 +9.656558E-15 +2.139877E+00 +9.185178E-01 +1.808977E-02 +8.744581E-05 1.726130E+08 -5.959695E+15 -1.026940E+02 -2.110535E+03 -3.872081E-03 -5.919692E-06 -9.916300E+01 -1.968002E+03 -9.916300E+01 -1.968002E+03 +5.959891E+15 +1.032960E+02 +2.135240E+03 +3.886968E-03 +5.976458E-06 +9.976500E+01 +1.991860E+03 +9.976500E+01 +1.991860E+03 tally 18: -6.507000E+00 -8.478423E+00 -1.455344E+00 -4.241161E-01 -1.155413E+00 -2.673178E-01 -2.888532E+00 -1.670737E+00 -4.955615E-05 -4.917547E-10 -2.870219E+00 -1.649619E+00 -1.831331E-02 -6.715634E-05 -2.310826E+08 -1.069271E+16 -6.507000E+00 -8.478423E+00 -8.580723E-03 -1.474352E-05 -1.026940E+02 -2.110535E+03 -3.523724E+00 -2.484884E+00 -8.612868E-01 -1.484560E-01 -2.153217E+00 -9.278503E-01 -6.502027E-07 -8.460574E-14 -2.139566E+00 -9.161225E-01 -1.365140E-02 -3.729555E-05 -1.722574E+08 -5.938242E+15 -1.026940E+02 -2.110535E+03 -6.396382E-03 -8.187874E-06 +6.546000E+00 +8.579894E+00 +1.464067E+00 +4.291919E-01 +1.162338E+00 +2.705171E-01 +2.905845E+00 +1.690732E+00 +4.985316E-05 +4.976401E-10 +2.887422E+00 +1.669362E+00 +1.842307E-02 +6.796008E-05 +2.324676E+08 +1.082069E+16 +6.546000E+00 +8.579894E+00 +8.632151E-03 +1.491997E-05 +1.032960E+02 +2.135240E+03 +3.544380E+00 +2.513971E+00 +8.663357E-01 +1.501938E-01 +2.165839E+00 +9.387115E-01 +6.540142E-07 +8.559612E-14 +2.152108E+00 +9.268463E-01 +1.373143E-02 +3.773212E-05 +1.732671E+08 +6.007753E+15 +1.032960E+02 +2.135240E+03 +6.433878E-03 +8.283719E-06 tally 19: -6.573230E+00 -8.663027E+00 -1.470157E+00 -4.333505E-01 -1.167173E+00 -2.731383E-01 -2.917933E+00 -1.707114E+00 -2.734707E-05 -1.499456E-10 -2.899433E+00 -1.685536E+00 -1.849971E-02 -6.861856E-05 -2.334346E+08 -1.092553E+16 -6.518000E+00 -8.507644E+00 -8.668060E-03 -1.506454E-05 -1.031389E+02 -2.128993E+03 -3.538988E+00 -2.506616E+00 -8.650177E-01 -1.497544E-01 -2.162544E+00 -9.359650E-01 -2.193361E-07 -9.628305E-15 -2.148834E+00 -9.241346E-01 -1.371054E-02 -3.762172E-05 -1.730035E+08 -5.990176E+15 -1.028630E+02 -2.117467E+03 -6.424090E-03 -8.259483E-06 +6.593971E+00 +8.715030E+00 +1.474796E+00 +4.359519E-01 +1.170856E+00 +2.747779E-01 +2.927140E+00 +1.717362E+00 +2.743336E-05 +1.508457E-10 +2.908582E+00 +1.695655E+00 +1.855808E-02 +6.903047E-05 +2.341712E+08 +1.099112E+16 +6.547000E+00 +8.582573E+00 +8.695410E-03 +1.515497E-05 +1.037750E+02 +2.155274E+03 +3.560815E+00 +2.537559E+00 +8.703528E-01 +1.516031E-01 +2.175882E+00 +9.475192E-01 +2.206889E-07 +9.747163E-15 +2.162087E+00 +9.355427E-01 +1.379510E-02 +3.808615E-05 +1.740706E+08 +6.064123E+15 +1.033110E+02 +2.135863E+03 +6.463712E-03 +8.361443E-06 tally 20: -5.063000E+00 -5.136983E+00 -5.063000E+00 -5.136983E+00 +5.084000E+00 +5.178800E+00 +5.084000E+00 +5.178800E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -2.867025E+00 -1.647980E+00 -1.445000E+00 -4.178610E-01 -1.445000E+00 -4.178610E-01 +2.879845E+00 +1.663297E+00 +1.463000E+00 +4.284330E-01 +1.463000E+00 +4.284330E-01 0.000000E+00 0.000000E+00 -9.771800E+01 -1.911083E+03 -9.771800E+01 -1.911083E+03 -2.133624E+00 -9.150435E-01 +9.830200E+01 +1.933884E+03 +9.830200E+01 +1.933884E+03 +2.157967E+00 +9.345420E-01 diff --git a/tests/regression_tests/mg_temperature/results_true.dat b/tests/regression_tests/mg_temperature/results_true.dat index 19364e1d96..6de4c6bb13 100644 --- a/tests/regression_tests/mg_temperature/results_true.dat +++ b/tests/regression_tests/mg_temperature/results_true.dat @@ -1,40 +1,40 @@ micro, method: nearest, t: 300.0, k-combined: -1.439563E+00 4.526076E-04 +1.439913E+00 4.285638E-04 kanalyt 1.440410E+00 micro, method: nearest, t: 600.0, k-combined: -1.409389E+00 4.684481E-04 +1.410750E+00 4.829834E-04 kanalyt 1.410164E+00 micro, method: nearest, t: 900.0, k-combined: -1.407593E+00 4.410387E-04 +1.408232E+00 4.946310E-04 kanalyt 1.407830E+00 micro, method: interpolation, t: 520.0, k-combined: -1.418259E+00 4.242856E-04 +1.418877E+00 4.651822E-04 kanalyt 1.418514E+00 micro, method: interpolation, t: 600.0, k-combined: -1.409389E+00 4.684481E-04 +1.410750E+00 4.829834E-04 kanalyt 1.410164E+00 macro, method: nearest, t: 300.0, k-combined: -1.439563E+00 4.526076E-04 +1.439913E+00 4.285638E-04 kanalyt 1.440410E+00 macro, method: nearest, t: 600.0, k-combined: -1.409389E+00 4.684481E-04 +1.410750E+00 4.829834E-04 kanalyt 1.410164E+00 macro, method: nearest, t: 900.0, k-combined: -1.407593E+00 4.410387E-04 +1.408232E+00 4.946310E-04 kanalyt 1.407830E+00 macro, method: interpolation, t: 520.0, k-combined: -1.418259E+00 4.242856E-04 +1.418877E+00 4.651822E-04 kanalyt 1.418514E+00 macro, method: interpolation, t: 600, k-combined: -1.409389E+00 4.684481E-04 +1.410750E+00 4.829834E-04 kanalyt 1.410164E+00 diff --git a/tests/regression_tests/mg_temperature_multi/results_true.dat b/tests/regression_tests/mg_temperature_multi/results_true.dat index 80c2f56225..3e2f990c8e 100644 --- a/tests/regression_tests/mg_temperature_multi/results_true.dat +++ b/tests/regression_tests/mg_temperature_multi/results_true.dat @@ -1,8 +1,8 @@ k-combined: -1.337115E+00 7.221249E-03 +1.309371E+00 6.765039E-03 tally 1: -2.549066E+01 -1.299987E+02 +2.532303E+01 +1.282689E+02 tally 2: -9.276778E+01 -1.721791E+03 +9.336894E+01 +1.743765E+03 diff --git a/tests/regression_tests/mgxs_library_ce_to_mg/results_true.dat b/tests/regression_tests/mgxs_library_ce_to_mg/results_true.dat index d956595345..7ce1063146 100644 --- a/tests/regression_tests/mgxs_library_ce_to_mg/results_true.dat +++ b/tests/regression_tests/mgxs_library_ce_to_mg/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.158563E+00 3.354681E-02 +1.152065E+00 2.768158E-02 diff --git a/tests/regression_tests/mgxs_library_ce_to_mg/test.py b/tests/regression_tests/mgxs_library_ce_to_mg/test.py index 48a715997a..075167f588 100644 --- a/tests/regression_tests/mgxs_library_ce_to_mg/test.py +++ b/tests/regression_tests/mgxs_library_ce_to_mg/test.py @@ -28,7 +28,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Initialize a tallies file - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _run_openmc(self): # Initial run diff --git a/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/results_true.dat b/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/results_true.dat index a4e9dafcc0..50c8328c88 100644 --- a/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/results_true.dat +++ b/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/results_true.dat @@ -1,2 +1,2 @@ k-combined: -6.025533E-01 1.157401E-02 +4.139942E-01 1.181308E-02 diff --git a/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/test.py b/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/test.py index a77ad24296..489105f8f5 100644 --- a/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/test.py +++ b/tests/regression_tests/mgxs_library_ce_to_mg_nuclides/test.py @@ -28,7 +28,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Initialize a tallies file - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _run_openmc(self): # Initial run diff --git a/tests/regression_tests/mgxs_library_condense/results_true.dat b/tests/regression_tests/mgxs_library_condense/results_true.dat index ae5bff6e35..98b30932c3 100644 --- a/tests/regression_tests/mgxs_library_condense/results_true.dat +++ b/tests/regression_tests/mgxs_library_condense/results_true.dat @@ -1,362 +1,362 @@ mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.699306 0.028642 -2 1 2 1 1 total 0.687913 0.025966 -1 2 1 1 1 total 0.716035 0.018945 -3 2 2 1 1 total 0.702630 0.028574 +0 1 1 1 1 total 0.702881 0.026175 +2 1 2 1 1 total 0.706921 0.029169 +1 2 1 1 1 total 0.707809 0.024766 +3 2 2 1 1 total 0.717967 0.024008 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.443642 0.030984 -2 1 2 1 1 total 0.429968 0.028072 -1 2 1 1 1 total 0.461535 0.021345 -3 2 2 1 1 total 0.439454 0.031232 +0 1 1 1 1 total 0.431023 0.028803 +2 1 2 1 1 total 0.451864 0.030748 +1 2 1 1 1 total 0.456990 0.026359 +3 2 2 1 1 total 0.450621 0.026744 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.443642 0.030984 -2 1 2 1 1 total 0.429968 0.028072 -1 2 1 1 1 total 0.461535 0.021345 -3 2 2 1 1 total 0.439454 0.031232 +0 1 1 1 1 total 0.431023 0.028803 +2 1 2 1 1 total 0.451864 0.030748 +1 2 1 1 1 total 0.456990 0.026359 +3 2 2 1 1 total 0.450621 0.026744 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.021895 0.001041 -2 1 2 1 1 total 0.021903 0.001108 -1 2 1 1 1 total 0.024895 0.001401 -3 2 2 1 1 total 0.022105 0.001198 +0 1 1 1 1 total 0.022398 0.001401 +2 1 2 1 1 total 0.022325 0.001371 +1 2 1 1 1 total 0.022942 0.000990 +3 2 2 1 1 total 0.022705 0.001322 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.021883 0.001040 -2 1 2 1 1 total 0.021879 0.001108 -1 2 1 1 1 total 0.024875 0.001401 -3 2 2 1 1 total 0.022071 0.001197 +0 1 1 1 1 total 0.022394 0.001401 +2 1 2 1 1 total 0.022321 0.001371 +1 2 1 1 1 total 0.022935 0.000990 +3 2 2 1 1 total 0.022699 0.001322 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.011219 0.000958 -2 1 2 1 1 total 0.011437 0.001013 -1 2 1 1 1 total 0.012947 0.001437 -3 2 2 1 1 total 0.011756 0.001144 +0 1 1 1 1 total 0.011562 0.001544 +2 1 2 1 1 total 0.011852 0.001418 +1 2 1 1 1 total 0.012168 0.000958 +3 2 2 1 1 total 0.011986 0.001418 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.010676 0.000481 -2 1 2 1 1 total 0.010466 0.000446 -1 2 1 1 1 total 0.011948 0.000517 -3 2 2 1 1 total 0.010350 0.000547 +0 1 1 1 1 total 0.010836 0.000803 +2 1 2 1 1 total 0.010473 0.000591 +1 2 1 1 1 total 0.010774 0.000415 +3 2 2 1 1 total 0.010719 0.000688 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.026218 0.001180 -2 1 2 1 1 total 0.025724 0.001093 -1 2 1 1 1 total 0.029326 0.001262 -3 2 2 1 1 total 0.025451 0.001338 +0 1 1 1 1 total 0.026602 0.001957 +2 1 2 1 1 total 0.025695 0.001442 +1 2 1 1 1 total 0.026454 0.001015 +3 2 2 1 1 total 0.026310 0.001678 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 2.067337e+06 93152.452502 -2 1 2 1 1 total 2.026907e+06 86377.585629 -1 2 1 1 1 total 2.313358e+06 99980.823985 -3 2 2 1 1 total 2.004370e+06 105820.022073 +0 1 1 1 1 total 2.098256e+06 155243.612264 +2 1 2 1 1 total 2.027699e+06 114334.400924 +1 2 1 1 1 total 2.086255e+06 80325.567787 +3 2 2 1 1 total 2.075596e+06 133128.805680 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.677411 0.027731 -2 1 2 1 1 total 0.666009 0.025155 -1 2 1 1 1 total 0.691140 0.018119 -3 2 2 1 1 total 0.680525 0.027587 +0 1 1 1 1 total 0.680483 0.025407 +2 1 2 1 1 total 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total 0.0 0.000000 +5 1 1 1 6 1 total 0.0 0.000000 +12 1 2 1 1 1 total 0.0 0.000000 +13 1 2 1 2 1 total 0.0 0.000000 +14 1 2 1 3 1 total 0.0 0.000000 +15 1 2 1 4 1 total 1.0 0.869026 +16 1 2 1 5 1 total 0.0 0.000000 +17 1 2 1 6 1 total 0.0 0.000000 +6 2 1 1 1 1 total 0.0 0.000000 +7 2 1 1 2 1 total 0.0 0.000000 +8 2 1 1 3 1 total 0.0 0.000000 +9 2 1 1 4 1 total 1.0 1.414214 +10 2 1 1 5 1 total 0.0 0.000000 +11 2 1 1 6 1 total 0.0 0.000000 +18 2 2 1 1 1 total 0.0 0.000000 +19 2 2 1 2 1 total 0.0 0.000000 +20 2 2 1 3 1 total 0.0 0.000000 +21 2 2 1 4 1 total 1.0 1.414214 +22 2 2 1 5 1 total 0.0 0.000000 +23 2 2 1 6 1 total 0.0 0.000000 mesh 1 delayedgroup group in nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.000227 0.000011 -1 1 1 1 2 1 total 0.001212 0.000058 -2 1 1 1 3 1 total 0.001180 0.000057 -3 1 1 1 4 1 total 0.002734 0.000131 -4 1 1 1 5 1 total 0.001215 0.000059 -5 1 1 1 6 1 total 0.000506 0.000024 -12 1 2 1 1 1 total 0.000227 0.000010 -13 1 2 1 2 1 total 0.001213 0.000052 -14 1 2 1 3 1 total 0.001182 0.000051 -15 1 2 1 4 1 total 0.002744 0.000120 -16 1 2 1 5 1 total 0.001223 0.000056 -17 1 2 1 6 1 total 0.000509 0.000023 -6 2 1 1 1 1 total 0.000227 0.000013 -7 2 1 1 2 1 total 0.001207 0.000067 -8 2 1 1 3 1 total 0.001173 0.000065 -9 2 1 1 4 1 total 0.002710 0.000150 -10 2 1 1 5 1 total 0.001195 0.000066 -11 2 1 1 6 1 total 0.000498 0.000027 -18 2 2 1 1 1 total 0.000227 0.000014 -19 2 2 1 2 1 total 0.001212 0.000073 -20 2 2 1 3 1 total 0.001180 0.000071 -21 2 2 1 4 1 total 0.002740 0.000163 -22 2 2 1 5 1 total 0.001221 0.000073 -23 2 2 1 6 1 total 0.000508 0.000030 +0 1 1 1 1 1 total 0.000227 0.000023 +1 1 1 1 2 1 total 0.001210 0.000119 +2 1 1 1 3 1 total 0.001176 0.000114 +3 1 1 1 4 1 total 0.002722 0.000261 +4 1 1 1 5 1 total 0.001204 0.000112 +5 1 1 1 6 1 total 0.000501 0.000047 +12 1 2 1 1 1 total 0.000227 0.000017 +13 1 2 1 2 1 total 0.001208 0.000087 +14 1 2 1 3 1 total 0.001174 0.000084 +15 1 2 1 4 1 total 0.002710 0.000192 +16 1 2 1 5 1 total 0.001194 0.000082 +17 1 2 1 6 1 total 0.000497 0.000034 +6 2 1 1 1 1 total 0.000227 0.000010 +7 2 1 1 2 1 total 0.001210 0.000053 +8 2 1 1 3 1 total 0.001177 0.000052 +9 2 1 1 4 1 total 0.002726 0.000119 +10 2 1 1 5 1 total 0.001208 0.000053 +11 2 1 1 6 1 total 0.000503 0.000022 +18 2 2 1 1 1 total 0.000227 0.000019 +19 2 2 1 2 1 total 0.001211 0.000102 +20 2 2 1 3 1 total 0.001178 0.000098 +21 2 2 1 4 1 total 0.002726 0.000223 +22 2 2 1 5 1 total 0.001207 0.000096 +23 2 2 1 6 1 total 0.000503 0.000040 mesh 1 delayedgroup nuclide mean std. dev. x y z -0 1 1 1 1 total 0.013354 0.000674 -1 1 1 1 2 total 0.032612 0.001720 -2 1 1 1 3 total 0.121057 0.006579 -3 1 1 1 4 total 0.305656 0.017398 -4 1 1 1 5 total 0.861000 0.053768 -5 1 1 1 6 total 2.891889 0.179407 -12 1 2 1 1 total 0.013354 0.000497 -13 1 2 1 2 total 0.032605 0.001150 -14 1 2 1 3 total 0.121071 0.004175 -15 1 2 1 4 total 0.305792 0.010484 -16 1 2 1 5 total 0.861500 0.032627 -17 1 2 1 6 total 2.893589 0.108347 -6 2 1 1 1 total 0.013352 0.000663 -7 2 1 1 2 total 0.032625 0.001570 -8 2 1 1 3 total 0.121029 0.005721 -9 2 1 1 4 total 0.305375 0.014144 -10 2 1 1 5 total 0.859955 0.039608 -11 2 1 1 6 total 2.888337 0.132844 -18 2 2 1 1 total 0.013354 0.000892 -19 2 2 1 2 total 0.032606 0.002209 -20 2 2 1 3 total 0.121069 0.008302 -21 2 2 1 4 total 0.305776 0.021416 -22 2 2 1 5 total 0.861442 0.063571 -23 2 2 1 6 total 2.893392 0.212640 - mesh 1 delayedgroup group in group out nuclide mean std. dev. - x y z -0 1 1 1 1 1 1 total 0.0 0.0 -1 1 1 1 2 1 1 total 0.0 0.0 -2 1 1 1 3 1 1 total 0.0 0.0 -3 1 1 1 4 1 1 total 0.0 0.0 -4 1 1 1 5 1 1 total 0.0 0.0 -5 1 1 1 6 1 1 total 0.0 0.0 -12 1 2 1 1 1 1 total 0.0 0.0 -13 1 2 1 2 1 1 total 0.0 0.0 -14 1 2 1 3 1 1 total 0.0 0.0 -15 1 2 1 4 1 1 total 0.0 0.0 -16 1 2 1 5 1 1 total 0.0 0.0 -17 1 2 1 6 1 1 total 0.0 0.0 -6 2 1 1 1 1 1 total 0.0 0.0 -7 2 1 1 2 1 1 total 0.0 0.0 -8 2 1 1 3 1 1 total 0.0 0.0 -9 2 1 1 4 1 1 total 0.0 0.0 -10 2 1 1 5 1 1 total 0.0 0.0 -11 2 1 1 6 1 1 total 0.0 0.0 -18 2 2 1 1 1 1 total 0.0 0.0 -19 2 2 1 2 1 1 total 0.0 0.0 -20 2 2 1 3 1 1 total 0.0 0.0 -21 2 2 1 4 1 1 total 0.0 0.0 -22 2 2 1 5 1 1 total 0.0 0.0 -23 2 2 1 6 1 1 total 0.0 0.0 +0 1 1 1 1 total 0.013353 0.001345 +1 1 1 1 2 total 0.032619 0.003120 +2 1 1 1 3 total 0.121042 0.011142 +3 1 1 1 4 total 0.305503 0.026418 +4 1 1 1 5 total 0.860433 0.064665 +5 1 1 1 6 total 2.889963 0.219527 +12 1 2 1 1 total 0.013352 0.001049 +13 1 2 1 2 total 0.032626 0.002465 +14 1 2 1 3 total 0.121027 0.008891 +15 1 2 1 4 total 0.305351 0.021426 +16 1 2 1 5 total 0.859866 0.054490 +17 1 2 1 6 total 2.888034 0.184436 +6 2 1 1 1 total 0.013353 0.000612 +7 2 1 1 2 total 0.032616 0.001412 +8 2 1 1 3 total 0.121047 0.005039 +9 2 1 1 4 total 0.305559 0.012002 +10 2 1 1 5 total 0.860640 0.030707 +11 2 1 1 6 total 2.890664 0.103692 +18 2 2 1 1 total 0.013353 0.001132 +19 2 2 1 2 total 0.032617 0.002633 +20 2 2 1 3 total 0.121046 0.009426 +21 2 2 1 4 total 0.305545 0.022417 +22 2 2 1 5 total 0.860588 0.055030 +23 2 2 1 6 total 2.890489 0.186821 + mesh 1 delayedgroup group in group out nuclide mean std. dev. + x y z +0 1 1 1 1 1 1 total 0.000000 0.000000 +1 1 1 1 2 1 1 total 0.000000 0.000000 +2 1 1 1 3 1 1 total 0.000000 0.000000 +3 1 1 1 4 1 1 total 0.000219 0.000219 +4 1 1 1 5 1 1 total 0.000000 0.000000 +5 1 1 1 6 1 1 total 0.000000 0.000000 +12 1 2 1 1 1 1 total 0.000000 0.000000 +13 1 2 1 2 1 1 total 0.000000 0.000000 +14 1 2 1 3 1 1 total 0.000000 0.000000 +15 1 2 1 4 1 1 total 0.000467 0.000287 +16 1 2 1 5 1 1 total 0.000000 0.000000 +17 1 2 1 6 1 1 total 0.000000 0.000000 +6 2 1 1 1 1 1 total 0.000000 0.000000 +7 2 1 1 2 1 1 total 0.000000 0.000000 +8 2 1 1 3 1 1 total 0.000000 0.000000 +9 2 1 1 4 1 1 total 0.000211 0.000211 +10 2 1 1 5 1 1 total 0.000000 0.000000 +11 2 1 1 6 1 1 total 0.000000 0.000000 +18 2 2 1 1 1 1 total 0.000000 0.000000 +19 2 2 1 2 1 1 total 0.000000 0.000000 +20 2 2 1 3 1 1 total 0.000000 0.000000 +21 2 2 1 4 1 1 total 0.000219 0.000219 +22 2 2 1 5 1 1 total 0.000000 0.000000 +23 2 2 1 6 1 1 total 0.000000 0.000000 diff --git a/tests/regression_tests/mgxs_library_condense/test.py b/tests/regression_tests/mgxs_library_condense/test.py index a7e60617f0..bbc4c11bfa 100644 --- a/tests/regression_tests/mgxs_library_condense/test.py +++ b/tests/regression_tests/mgxs_library_condense/test.py @@ -36,7 +36,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_correction/results_true.dat b/tests/regression_tests/mgxs_library_correction/results_true.dat index ff4bd97463..b6aaad0441 100644 --- a/tests/regression_tests/mgxs_library_correction/results_true.dat +++ b/tests/regression_tests/mgxs_library_correction/results_true.dat @@ -1,60 +1,60 @@ material group in group out nuclide mean std. dev. -3 1 1 1 total 0.342252 0.023795 -2 1 1 2 total 0.000695 0.000327 +3 1 1 1 total 0.353477 0.019952 +2 1 1 2 total 0.000522 0.000349 1 1 2 1 total 0.000000 0.000000 -0 1 2 2 total 0.388426 0.020840 +0 1 2 2 total 0.414134 0.029955 material group in group out nuclide mean std. dev. -3 1 1 1 total 0.342252 0.023795 -2 1 1 2 total 0.000695 0.000327 +3 1 1 1 total 0.353477 0.019952 +2 1 1 2 total 0.000522 0.000349 1 1 2 1 total 0.000000 0.000000 -0 1 2 2 total 0.388426 0.020840 +0 1 2 2 total 0.414134 0.029955 material group in group out nuclide mean std. dev. -3 1 1 1 total 0.343021 0.031016 -2 1 1 2 total 0.000697 0.000329 +3 1 1 1 total 0.356124 0.026110 +2 1 1 2 total 0.000526 0.000352 1 1 2 1 total 0.000000 0.000000 -0 1 2 2 total 0.376544 0.025156 +0 1 2 2 total 0.413622 0.044755 material group in group out nuclide mean std. dev. -3 1 1 1 total 0.343021 0.039761 -2 1 1 2 total 0.000697 0.000566 +3 1 1 1 total 0.356124 0.033873 +2 1 1 2 total 0.000526 0.000608 1 1 2 1 total 0.000000 0.000000 -0 1 2 2 total 0.376544 0.032140 +0 1 2 2 total 0.413622 0.054899 material group in group out nuclide mean std. dev. -3 2 1 1 total 0.271174 0.022374 +3 2 1 1 total 0.261901 0.016456 2 2 1 2 total 0.000000 0.000000 1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.295401 0.032831 +0 2 2 2 total 0.322376 0.044195 material group in group out nuclide mean std. dev. -3 2 1 1 total 0.271174 0.022374 +3 2 1 1 total 0.261901 0.016456 2 2 1 2 total 0.000000 0.000000 1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.295401 0.032831 +0 2 2 2 total 0.322376 0.044195 material group in group out nuclide mean std. dev. -3 2 1 1 total 0.264654 0.028288 +3 2 1 1 total 0.266612 0.021169 2 2 1 2 total 0.000000 0.000000 1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.295178 0.032530 +0 2 2 2 total 0.321966 0.054140 material group in group out nuclide mean std. dev. -3 2 1 1 total 0.264654 0.036081 +3 2 1 1 total 0.266612 0.025384 2 2 1 2 total 0.000000 0.000000 1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.295178 0.044676 +0 2 2 2 total 0.321966 0.068014 material group in group out nuclide mean std. dev. -3 3 1 1 total 0.257831 0.014436 -2 3 1 2 total 0.030826 0.000973 -1 3 2 1 total 0.000467 0.000467 -0 3 2 2 total 1.443057 0.119909 +3 3 1 1 total 0.259426 0.012116 +2 3 1 2 total 0.031650 0.000613 +1 3 2 1 total 0.000474 0.000475 +0 3 2 2 total 1.416407 0.162435 material group in group out nuclide mean std. dev. -3 3 1 1 total 0.257831 0.014436 -2 3 1 2 total 0.030826 0.000973 -1 3 2 1 total 0.000467 0.000467 -0 3 2 2 total 1.443057 0.119909 +3 3 1 1 total 0.259426 0.012116 +2 3 1 2 total 0.031650 0.000613 +1 3 2 1 total 0.000474 0.000475 +0 3 2 2 total 1.416407 0.162435 material group in group out nuclide mean std. dev. -3 3 1 1 total 0.267025 0.029512 -2 3 1 2 total 0.031268 0.001416 -1 3 2 1 total 0.000466 0.000467 -0 3 2 2 total 1.440250 0.164573 +3 3 1 1 total 0.266083 0.024503 +2 3 1 2 total 0.031973 0.001157 +1 3 2 1 total 0.000477 0.000480 +0 3 2 2 total 1.427932 0.269812 material group in group out nuclide mean std. dev. -3 3 1 1 total 0.267025 0.032860 -2 3 1 2 total 0.031268 0.001768 -1 3 2 1 total 0.000466 0.000808 -0 3 2 2 total 1.440250 0.212183 +3 3 1 1 total 0.266083 0.027910 +2 3 1 2 total 0.031973 0.001391 +1 3 2 1 total 0.000477 0.000827 +0 3 2 2 total 1.427932 0.328026 diff --git a/tests/regression_tests/mgxs_library_correction/test.py b/tests/regression_tests/mgxs_library_correction/test.py index 05eedfef82..64e638e442 100644 --- a/tests/regression_tests/mgxs_library_correction/test.py +++ b/tests/regression_tests/mgxs_library_correction/test.py @@ -29,7 +29,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_distribcell/results_true.dat b/tests/regression_tests/mgxs_library_distribcell/results_true.dat index ef7cb2b96b..127df75c1e 100644 --- a/tests/regression_tests/mgxs_library_distribcell/results_true.dat +++ b/tests/regression_tests/mgxs_library_distribcell/results_true.dat @@ -1,97 +1,97 @@ sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.455527 0.009851 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.459656 0.010039 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.409242 0.011118 - sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.40929 0.011119 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.416327 0.01121 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.066934 0.002424 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.416327 0.01121 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.066764 0.002423 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.070545 0.002486 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.028358 0.002669 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.070348 0.002485 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.038576 0.001526 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.029374 0.002719 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.094817 0.003725 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.041172 0.001562 + sum(distribcell) group in nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.101218 0.003812 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 7.470225e+06 295170.385185 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 7.972654e+06 302079.851251 + sum(distribcell) group in nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.38911 0.00831 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.388593 0.008156 - sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.388874 0.013889 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.394876 0.014019 sum(distribcell) group in group out legendre nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.388711 0.013887 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.046285 0.005155 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.023632 0.003772 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.006997 0.003207 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.394876 0.014019 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.043329 0.004988 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.027490 0.003974 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.016004 0.003232 sum(distribcell) group in group out legendre nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.388874 0.013889 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.046237 0.005156 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.023571 0.003775 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.007058 0.003207 - sum(distribcell) group in group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 1.000418 0.036246 - sum(distribcell) group in group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.092139 0.005956 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.394876 0.014019 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.043329 0.004988 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.027490 0.003974 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.016004 0.003232 sum(distribcell) group in group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 1.0 0.036242 - sum(distribcell) group in group out legendre nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.388593 0.016275 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.046271 0.005251 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.023624 0.003806 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.006995 0.003209 - sum(distribcell) group in group out legendre nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.388755 0.021528 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.046290 0.005515 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.023634 0.003903 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.006998 0.003221 - sum(distribcell) group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 1.0 0.084366 - sum(distribcell) group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 1.0 0.084331 - sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 5.253873e-07 2.168462e-08 - sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.094147 0.003701 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 1.0 0.036306 sum(distribcell) group in group out nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.091593 0.005919 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.097856 0.006191 + sum(distribcell) group in group out nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 1.0 0.036306 + sum(distribcell) group in group out legendre nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.389110 0.016390 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.042696 0.005009 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.027088 0.003964 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.015770 0.003204 + sum(distribcell) group in group out legendre nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P0 total 0.389110 0.021638 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P1 total 0.042696 0.005244 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P2 total 0.027088 0.004084 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 P3 total 0.015770 0.003255 + sum(distribcell) group out nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 1.0 0.082469 + sum(distribcell) group out nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 1.0 0.082587 + sum(distribcell) group in nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 5.626624e-07 2.235532e-08 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.814514 0.022129 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.100506 0.003787 + sum(distribcell) group in group out nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.097658 0.006185 sum(distribcell) group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.814419 0.022125 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.800653 0.021558 + sum(distribcell) group in nuclide mean std. dev. +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.800653 0.021558 sum(distribcell) delayedgroup group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.000021 8.473275e-07 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 0.000115 4.405467e-06 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 0.000112 4.225826e-06 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 0.000259 9.559952e-06 -4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 total 0.000115 4.025369e-06 -5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 total 0.000048 1.682226e-06 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.000023 8.667436e-07 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 0.000122 4.499059e-06 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 0.000119 4.311220e-06 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 0.000275 9.735290e-06 +4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 total 0.000122 4.078954e-06 +5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 total 0.000051 1.705327e-06 sum(distribcell) delayedgroup group out nuclide mean std. dev. 0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.0 0.000000 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 0.0 0.000000 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 1.0 1.000002 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 1.0 1.414214 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 1.0 1.414214 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 0.0 0.000000 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 0.0 0.000000 4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 total 0.0 0.000000 5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 total 0.0 0.000000 sum(distribcell) delayedgroup group in nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.000227 0.000012 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 0.001210 0.000062 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 0.001177 0.000060 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 0.002728 0.000136 -4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 total 0.001211 0.000059 -5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 total 0.000504 0.000025 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 total 0.000227 0.000011 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 total 0.001208 0.000059 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 total 0.001175 0.000056 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 total 0.002721 0.000129 +4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 total 0.001206 0.000055 +5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 total 0.000502 0.000023 sum(distribcell) delayedgroup nuclide mean std. dev. -0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.013353 0.000692 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 total 0.032613 0.001644 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 total 0.121054 0.005983 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 total 0.305630 0.014645 -4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 total 0.860903 0.038693 -5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 total 2.891558 0.130564 +0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 total 0.013353 0.000658 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 total 0.032616 0.001562 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 total 0.121048 0.005678 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 total 0.305568 0.013868 +4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 total 0.860675 0.036434 +5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 total 2.890786 0.122997 sum(distribcell) delayedgroup group in group out nuclide mean std. dev. 0 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 1 1 1 total 0.000000 0.000000 -1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 1 total 0.000000 0.000000 -2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 1 total 0.000362 0.000256 -3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 1 total 0.000185 0.000185 +1 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 2 1 1 total 0.000198 0.000198 +2 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 3 1 1 total 0.000000 0.000000 +3 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 4 1 1 total 0.000000 0.000000 4 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 5 1 1 total 0.000000 0.000000 5 ((0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, ...),) 6 1 1 total 0.000000 0.000000 diff --git a/tests/regression_tests/mgxs_library_distribcell/test.py b/tests/regression_tests/mgxs_library_distribcell/test.py index fd6c8e9386..464b309c00 100644 --- a/tests/regression_tests/mgxs_library_distribcell/test.py +++ b/tests/regression_tests/mgxs_library_distribcell/test.py @@ -36,7 +36,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) self._model.tallies.export_to_xml() def _get_results(self, hash_output=False): diff --git a/tests/regression_tests/mgxs_library_hdf5/results_true.dat b/tests/regression_tests/mgxs_library_hdf5/results_true.dat index b2ef8eae92..14d7371fe6 100644 --- a/tests/regression_tests/mgxs_library_hdf5/results_true.dat +++ b/tests/regression_tests/mgxs_library_hdf5/results_true.dat @@ -1,201 +1,201 @@ domain=1 type=total -[5.52629207e-01 1.46792426e+00] -[2.73983948e-02 9.30468557e-02] +[5.66580451e-01 1.44262943e+00] +[1.96770003e-02 1.46112369e-01] domain=1 type=transport -[3.09650231e-01 1.14528468e+00] -[2.96126059e-02 1.01957125e-01] +[3.14856281e-01 1.05346368e+00] +[2.15203447e-02 1.60562179e-01] domain=1 type=nu-transport -[3.09650231e-01 1.14528468e+00] -[2.96126059e-02 1.01957125e-01] +[3.14856281e-01 1.05346368e+00] +[2.15203447e-02 1.60562179e-01] domain=1 type=absorption -[7.90251362e-03 9.52195503e-02] -[7.77996866e-04 5.32017792e-03] +[8.63921263e-03 9.70718967e-02] +[7.09849180e-04 9.96697703e-03] domain=1 type=reduced absorption -[7.88836875e-03 9.52195503e-02] -[7.77877367e-04 5.32017792e-03] +[8.63459183e-03 9.70718967e-02] +[7.09826160e-04 9.96697703e-03] domain=1 type=capture -[5.66271991e-03 4.03380329e-02] -[7.65494411e-04 4.41129849e-03] +[6.29732743e-03 4.01344183e-02] +[7.03181817e-04 9.43458504e-03] domain=1 type=fission -[2.23979371e-03 5.48815174e-02] -[1.44808204e-04 3.21965557e-03] +[2.34188519e-03 5.69374784e-02] +[1.04006997e-04 6.19904834e-03] domain=1 type=nu-fission -[5.70078167e-03 1.33729794e-01] -[3.71908758e-04 7.84533474e-03] +[5.93985124e-03 1.38739554e-01] +[2.57215008e-04 1.51052211e-02] domain=1 type=kappa-fission -[4.36283087e+05 1.06143820e+07] -[2.81939099e+04 6.22698786e+05] +[4.55876276e+05 1.10120160e+07] +[2.00450394e+04 1.19892945e+06] domain=1 type=scatter -[5.44726693e-01 1.37270471e+00] -[2.67443307e-02 8.86578418e-02] +[5.57941239e-01 1.34555753e+00] +[1.96103602e-02 1.38008873e-01] domain=1 type=nu-scatter -[5.46058885e-01 1.38608802e+00] -[2.72733439e-02 9.59957737e-02] +[5.53883536e-01 1.40126963e+00] +[1.89917740e-02 1.62647765e-01] domain=1 type=scatter matrix -[[[5.25081070e-01 2.42978975e-01 9.65459393e-02 8.62265123e-03] - [2.09778151e-02 5.67750504e-03 -1.86093418e-03 -1.63034937e-03]] +[[[5.35878034e-01 2.51724170e-01 1.01011269e-01 1.03439439e-02] + [1.80055019e-02 5.80562809e-03 -1.57470166e-03 -2.27320020e-03]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.38608802e+00 2.92665071e-01 4.65545679e-02 3.43129413e-03]]] -[[[2.68584158e-02 1.12354079e-02 5.95151250e-03 5.08213314e-03] - [1.69810442e-03 1.03379654e-03 3.35798077e-04 8.28775769e-04]] + [1.40126963e+00 3.55339640e-01 7.06453615e-02 4.04065595e-02]]] +[[[1.86010787e-02 8.71440749e-03 3.01351835e-03 5.22968320e-03] + [1.36795874e-03 6.67372701e-04 3.26122899e-04 8.68935369e-04]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [9.59957737e-02 3.98634629e-02 1.79245433e-02 2.53788407e-02]]] + [1.62647765e-01 6.23420543e-02 9.61788834e-03 8.80966610e-03]]] domain=1 type=nu-scatter matrix -[[[5.25081070e-01 2.42978975e-01 9.65459393e-02 8.62265123e-03] - [2.09778151e-02 5.67750504e-03 -1.86093418e-03 -1.63034937e-03]] +[[[5.35878034e-01 2.51724170e-01 1.01011269e-01 1.03439439e-02] + [1.80055019e-02 5.80562809e-03 -1.57470166e-03 -2.27320020e-03]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.38608802e+00 2.92665071e-01 4.65545679e-02 3.43129413e-03]]] -[[[2.68584158e-02 1.12354079e-02 5.95151250e-03 5.08213314e-03] - [1.69810442e-03 1.03379654e-03 3.35798077e-04 8.28775769e-04]] + [1.40126963e+00 3.55339640e-01 7.06453615e-02 4.04065595e-02]]] +[[[1.86010787e-02 8.71440749e-03 3.01351835e-03 5.22968320e-03] + [1.36795874e-03 6.67372701e-04 3.26122899e-04 8.68935369e-04]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [9.59957737e-02 3.98634629e-02 1.79245433e-02 2.53788407e-02]]] + [1.62647765e-01 6.23420543e-02 9.61788834e-03 8.80966610e-03]]] domain=1 type=multiplicity matrix [[1.00000000e+00 1.00000000e+00] [0.00000000e+00 1.00000000e+00]] -[[4.49973217e-02 9.94834121e-02] - [0.00000000e+00 8.90267353e-02]] +[[3.27047397e-02 1.01015254e-01] + [0.00000000e+00 1.16966513e-01]] domain=1 type=nu-fission matrix -[[6.79725552e-03 0.00000000e+00] - [1.34226308e-01 0.00000000e+00]] -[[1.39232734e-03 0.00000000e+00] - [1.55126210e-02 0.00000000e+00]] +[[7.11392182e-03 0.00000000e+00] + [1.52683850e-01 0.00000000e+00]] +[[1.05605314e-03 0.00000000e+00] + [2.58713491e-02 0.00000000e+00]] domain=1 type=scatter probability matrix -[[9.61583236e-01 3.84167637e-02] +[[9.67492260e-01 3.25077399e-02] [0.00000000e+00 1.00000000e+00]] -[[4.25251594e-02 2.94881301e-03] - [0.00000000e+00 8.90267353e-02]] +[[3.12124830e-02 2.43439942e-03] + [0.00000000e+00 1.16966513e-01]] domain=1 type=consistent scatter matrix -[[[5.23800056e-01 2.42386192e-01 9.63104011e-02 8.60161499e-03] - [2.09266366e-02 5.66365392e-03 -1.85639416e-03 -1.62637189e-03]] +[[[5.39803830e-01 2.53568280e-01 1.01751269e-01 1.04197228e-02] + [1.81374087e-02 5.84815962e-03 -1.58623779e-03 -2.28985347e-03]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.37270471e+00 2.89839256e-01 4.61050623e-02 3.39816342e-03]]] -[[[3.46115177e-02 1.51137129e-02 7.17487890e-03 5.08248710e-03] - [1.90677851e-03 1.05813829e-03 3.43862086e-04 8.29548315e-04]] + [1.34555753e+00 3.41211940e-01 6.78366221e-02 3.88000634e-02]]] +[[[2.57534994e-02 1.20804286e-02 4.50621873e-03 5.27902298e-03] + [1.50041314e-03 6.98980912e-04 3.32589287e-04 8.78503928e-04]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.50979688e-01 4.66032426e-02 1.81833349e-02 2.51354735e-02]]] + [2.09324012e-01 6.95175402e-02 1.16044952e-02 9.36549883e-03]]] domain=1 type=consistent nu-scatter matrix -[[[5.23800056e-01 2.42386192e-01 9.63104011e-02 8.60161499e-03] - [2.09266366e-02 5.66365392e-03 -1.85639416e-03 -1.62637189e-03]] +[[[5.39803830e-01 2.53568280e-01 1.01751269e-01 1.04197228e-02] + [1.81374087e-02 5.84815962e-03 -1.58623779e-03 -2.28985347e-03]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.37270471e+00 2.89839256e-01 4.61050623e-02 3.39816342e-03]]] -[[[4.18746126e-02 1.86381616e-02 8.38211969e-03 5.09720340e-03] - [2.82310416e-03 1.19879975e-03 3.90317811e-04 8.45179676e-04]] + [1.34555753e+00 3.41211940e-01 6.78366221e-02 3.88000634e-02]]] +[[[3.12235732e-02 1.46529414e-02 5.60177820e-03 5.29001047e-03] + [2.36812824e-03 9.15185125e-04 3.69175618e-04 9.08445666e-04]] [[0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00] - [1.94240879e-01 5.32698778e-02 1.86408495e-02 2.51372940e-02]]] + [2.61890501e-01 8.01593794e-02 1.40578233e-02 1.04071518e-02]]] domain=1 type=chi [1.00000000e+00 0.00000000e+00] -[1.03333203e-01 0.00000000e+00] +[1.42429813e-01 0.00000000e+00] domain=1 type=chi-prompt [1.00000000e+00 0.00000000e+00] -[1.03333203e-01 0.00000000e+00] +[1.43958515e-01 0.00000000e+00] domain=1 type=inverse-velocity -[5.72461488e-08 3.00999757e-06] -[2.80644407e-09 1.80993426e-07] +[6.05275939e-08 2.92408191e-06] +[4.98534008e-09 2.95326306e-07] domain=1 type=prompt-nu-fission -[5.64594959e-03 1.32859920e-01] -[3.68364598e-04 7.79430310e-03] +[5.88433433e-03 1.37837093e-01] +[2.56012352e-04 1.50069660e-02] domain=1 type=prompt-nu-fission matrix -[[6.79725552e-03 0.00000000e+00] - [1.34226308e-01 0.00000000e+00]] -[[1.39232734e-03 0.00000000e+00] - [1.55126210e-02 0.00000000e+00]] +[[7.11392182e-03 0.00000000e+00] + [1.51190909e-01 0.00000000e+00]] +[[1.05605314e-03 0.00000000e+00] + [2.57973847e-02 0.00000000e+00]] domain=1 type=current -[[[0.00000000e+00 0.00000000e+00 3.54200000e+00 3.59000000e+00 - 0.00000000e+00 0.00000000e+00 3.73400000e+00 3.69000000e+00] - [0.00000000e+00 0.00000000e+00 7.08000000e-01 6.90000000e-01 - 0.00000000e+00 0.00000000e+00 6.78000000e-01 6.74000000e-01]] +[[[0.00000000e+00 0.00000000e+00 3.71800000e+00 3.58600000e+00 + 0.00000000e+00 0.00000000e+00 3.62200000e+00 3.71800000e+00] + [0.00000000e+00 0.00000000e+00 6.60000000e-01 6.58000000e-01 + 0.00000000e+00 0.00000000e+00 6.62000000e-01 6.70000000e-01]] - [[3.59000000e+00 3.54200000e+00 0.00000000e+00 0.00000000e+00 - 0.00000000e+00 0.00000000e+00 3.65200000e+00 3.73800000e+00] - [6.90000000e-01 7.08000000e-01 0.00000000e+00 0.00000000e+00 - 0.00000000e+00 0.00000000e+00 6.94000000e-01 6.64000000e-01]] + [[3.58600000e+00 3.71800000e+00 0.00000000e+00 0.00000000e+00 + 0.00000000e+00 0.00000000e+00 3.71200000e+00 3.60600000e+00] + [6.58000000e-01 6.60000000e-01 0.00000000e+00 0.00000000e+00 + 0.00000000e+00 0.00000000e+00 7.04000000e-01 6.74000000e-01]] - [[0.00000000e+00 0.00000000e+00 3.76000000e+00 3.66600000e+00 - 3.69000000e+00 3.73400000e+00 0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00 6.68000000e-01 7.22000000e-01 - 6.74000000e-01 6.78000000e-01 0.00000000e+00 0.00000000e+00]] + [[0.00000000e+00 0.00000000e+00 3.48600000e+00 3.60600000e+00 + 3.71800000e+00 3.62200000e+00 0.00000000e+00 0.00000000e+00] + [0.00000000e+00 0.00000000e+00 6.66000000e-01 6.74000000e-01 + 6.70000000e-01 6.62000000e-01 0.00000000e+00 0.00000000e+00]] - [[3.66600000e+00 3.76000000e+00 0.00000000e+00 0.00000000e+00 - 3.73800000e+00 3.65200000e+00 0.00000000e+00 0.00000000e+00] - [7.22000000e-01 6.68000000e-01 0.00000000e+00 0.00000000e+00 - 6.64000000e-01 6.94000000e-01 0.00000000e+00 0.00000000e+00]]] -[[[0.00000000e+00 0.00000000e+00 1.04230514e-01 1.61183126e-01 - 0.00000000e+00 0.00000000e+00 1.50419414e-01 1.00498756e-01] - [0.00000000e+00 0.00000000e+00 2.47790234e-02 3.27108545e-02 - 0.00000000e+00 0.00000000e+00 4.84148737e-02 3.24961536e-02]] + [[3.60600000e+00 3.48600000e+00 0.00000000e+00 0.00000000e+00 + 3.60600000e+00 3.71200000e+00 0.00000000e+00 0.00000000e+00] + [6.74000000e-01 6.66000000e-01 0.00000000e+00 0.00000000e+00 + 6.74000000e-01 7.04000000e-01 0.00000000e+00 0.00000000e+00]]] +[[[0.00000000e+00 0.00000000e+00 9.96192752e-02 8.73269718e-02 + 0.00000000e+00 0.00000000e+00 1.22531629e-01 1.08369737e-01] + [0.00000000e+00 0.00000000e+00 3.96232255e-02 4.06693988e-02 + 0.00000000e+00 0.00000000e+00 4.05462699e-02 4.27784993e-02]] - [[1.61183126e-01 1.04230514e-01 0.00000000e+00 0.00000000e+00 - 0.00000000e+00 0.00000000e+00 1.44201248e-01 1.81229137e-01] - [3.27108545e-02 2.47790234e-02 0.00000000e+00 0.00000000e+00 - 0.00000000e+00 0.00000000e+00 3.41467422e-02 2.20454077e-02]] + [[8.73269718e-02 9.96192752e-02 0.00000000e+00 0.00000000e+00 + 0.00000000e+00 0.00000000e+00 7.09506871e-02 5.27825729e-02] + [4.06693988e-02 3.96232255e-02 0.00000000e+00 0.00000000e+00 + 0.00000000e+00 0.00000000e+00 6.11228272e-02 5.88727441e-02]] - [[0.00000000e+00 0.00000000e+00 1.39355660e-01 9.70875893e-02 - 1.00498756e-01 1.50419414e-01 0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00 1.56204994e-02 3.27719392e-02 - 3.24961536e-02 4.84148737e-02 0.00000000e+00 0.00000000e+00]] + [[0.00000000e+00 0.00000000e+00 1.00279609e-01 1.31209756e-01 + 1.08369737e-01 1.22531629e-01 0.00000000e+00 0.00000000e+00] + [0.00000000e+00 0.00000000e+00 6.05475020e-02 4.87442304e-02 + 4.27784993e-02 4.05462699e-02 0.00000000e+00 0.00000000e+00]] - [[9.70875893e-02 1.39355660e-01 0.00000000e+00 0.00000000e+00 - 1.81229137e-01 1.44201248e-01 0.00000000e+00 0.00000000e+00] - [3.27719392e-02 1.56204994e-02 0.00000000e+00 0.00000000e+00 - 2.20454077e-02 3.41467422e-02 0.00000000e+00 0.00000000e+00]]] + [[1.31209756e-01 1.00279609e-01 0.00000000e+00 0.00000000e+00 + 5.27825729e-02 7.09506871e-02 0.00000000e+00 0.00000000e+00] + [4.87442304e-02 6.05475020e-02 0.00000000e+00 0.00000000e+00 + 5.88727441e-02 6.11228272e-02 0.00000000e+00 0.00000000e+00]]] domain=1 type=diffusion-coefficient -[1.07648340e+00 2.91048451e-01] -[1.02946730e-01 2.59101197e-02] +[1.05868408e+00 3.16416542e-01] +[7.23607812e-02 4.82261806e-02] domain=1 type=nu-diffusion-coefficient -[1.07648340e+00 2.91048451e-01] -[1.02946730e-01 2.59101197e-02] +[1.05868408e+00 3.16416542e-01] +[7.23607812e-02 4.82261806e-02] domain=1 type=delayed-nu-fission -[[1.27862358e-06 3.04521075e-05] - [7.84219053e-06 1.57184471e-04] - [8.19703020e-06 1.50062017e-04] - [2.11585246e-05 3.36451683e-04] - [1.15983232e-05 1.37940708e-04] - [4.75823112e-06 5.77828684e-05]] -[[8.24665595e-08 1.78649023e-06] - [5.11270396e-07 9.22131636e-06] - [5.43215007e-07 8.80347339e-06] - [1.44919046e-06 1.97381285e-05] - [8.56858673e-07 8.09236929e-06] - [3.49663884e-07 3.38986452e-06]] +[[1.33370452e-06 3.15928985e-05] + [8.06563789e-06 1.63072885e-04] + [8.37555675e-06 1.55683610e-04] + [2.14225848e-05 3.49055766e-04] + [1.15633419e-05 1.43108212e-04] + [4.74849054e-06 5.99475175e-05]] +[[5.58190638e-08 3.43966581e-06] + [2.80924725e-07 1.77545031e-05] + [2.81900859e-07 1.69499982e-05] + [7.44207592e-07 3.80033227e-05] + [4.95821820e-07 1.55808550e-05] + [2.00315983e-07 6.52676436e-06]] domain=1 type=chi-delayed [[0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00] + [1.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00]] [[0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00] + [1.41421356e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00]] domain=1 type=beta -[[2.24289169e-04 2.27713711e-04] - [1.37563425e-03 1.17538857e-03] - [1.43787829e-03 1.12212853e-03] - [3.71151288e-03 2.51590669e-03] - [2.03451453e-03 1.03148823e-03] - [8.34662928e-04 4.32086724e-04]] -[[1.75760869e-05 1.28957660e-05] - [1.08591736e-04 6.65640010e-05] - [1.14785004e-04 6.35478047e-05] - [3.03169937e-04 1.42479528e-04] - [1.75476030e-04 5.84147049e-05] - [7.17094876e-05 2.44697107e-05]] +[[2.24535003e-04 2.27713710e-04] + [1.35788550e-03 1.17538857e-03] + [1.41006170e-03 1.12212852e-03] + [3.60658609e-03 2.51590665e-03] + [1.94673931e-03 1.03148820e-03] + [7.99429201e-04 4.32086711e-04]] +[[1.15072629e-05 2.77827007e-05] + [6.20475481e-05 1.43405806e-04] + [6.31808205e-05 1.36907698e-04] + [1.64551758e-04 3.06958585e-04] + [1.01406915e-04 1.25848924e-04] + [4.11875799e-05 5.27176635e-05]] domain=1 type=decay-rate -[1.33535692e-02 3.26115957e-02 1.21057117e-01 3.05655911e-01 - 8.60999995e-01 2.89188863e+00] -[6.74373067e-04 1.71978136e-03 6.57917554e-03 1.73982053e-02 - 5.37683207e-02 1.79407115e-01] +[1.33525569e-02 3.26187089e-02 1.21041926e-01 3.05503129e-01 + 8.60433350e-01 2.88996258e+00] +[1.34484408e-03 3.11955840e-03 1.11418058e-02 2.64184722e-02 + 6.46651447e-02 2.19526509e-01] domain=1 type=delayed-nu-fission matrix [[[0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00]] @@ -207,7 +207,7 @@ domain=1 type=delayed-nu-fission matrix [0.00000000e+00 0.00000000e+00]] [[0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00]] + [1.49294023e-03 0.00000000e+00]] [[0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00]] @@ -224,7 +224,7 @@ domain=1 type=delayed-nu-fission matrix [0.00000000e+00 0.00000000e+00]] [[0.00000000e+00 0.00000000e+00] - [0.00000000e+00 0.00000000e+00]] + [1.49788268e-03 0.00000000e+00]] [[0.00000000e+00 0.00000000e+00] [0.00000000e+00 0.00000000e+00]] diff --git a/tests/regression_tests/mgxs_library_hdf5/test.py b/tests/regression_tests/mgxs_library_hdf5/test.py index 06625c25f9..4fb4bf0936 100644 --- a/tests/regression_tests/mgxs_library_hdf5/test.py +++ b/tests/regression_tests/mgxs_library_hdf5/test.py @@ -40,7 +40,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_histogram/results_true.dat b/tests/regression_tests/mgxs_library_histogram/results_true.dat index 2fa94cef58..f927d057ee 100644 --- a/tests/regression_tests/mgxs_library_histogram/results_true.dat +++ b/tests/regression_tests/mgxs_library_histogram/results_true.dat @@ -1,18 +1,18 @@ material group in group out mu bin nuclide mean std. dev. -33 1 1 1 1 total 0.032861 0.003703 -34 1 1 1 2 total 0.026428 0.003637 -35 1 1 1 3 total 0.029210 0.001648 -36 1 1 1 4 total 0.032513 0.004770 -37 1 1 1 5 total 0.030949 0.003129 -38 1 1 1 6 total 0.027124 0.004029 -39 1 1 1 7 total 0.030079 0.002186 -40 1 1 1 8 total 0.037034 0.002198 -41 1 1 1 9 total 0.038251 0.003825 -42 1 1 1 10 total 0.039294 0.003626 -43 1 1 1 11 total 0.062593 0.005934 -22 1 1 2 1 total 0.000000 0.000000 -23 1 1 2 2 total 0.000174 0.000174 -24 1 1 2 3 total 0.000348 0.000213 +33 1 1 1 1 total 0.029945 0.003043 +34 1 1 1 2 total 0.028378 0.003793 +35 1 1 1 3 total 0.033079 0.002866 +36 1 1 1 4 total 0.030119 0.002259 +37 1 1 1 5 total 0.033601 0.003739 +38 1 1 1 6 total 0.035516 0.001929 +39 1 1 1 7 total 0.032382 0.001744 +40 1 1 1 8 total 0.031860 0.002565 +41 1 1 1 9 total 0.038302 0.004757 +42 1 1 1 10 total 0.041784 0.003047 +43 1 1 1 11 total 0.057453 0.003686 +22 1 1 2 1 total 0.000174 0.000174 +23 1 1 2 2 total 0.000000 0.000000 +24 1 1 2 3 total 0.000174 0.000174 25 1 1 2 4 total 0.000174 0.000174 26 1 1 2 5 total 0.000000 0.000000 27 1 1 2 6 total 0.000000 0.000000 @@ -32,32 +32,32 @@ 19 1 2 1 9 total 0.000000 0.000000 20 1 2 1 10 total 0.000000 0.000000 21 1 2 1 11 total 0.000000 0.000000 -0 1 2 2 1 total 0.032383 0.006826 -1 1 2 2 2 total 0.037146 0.001158 -2 1 2 2 3 total 0.036193 0.004463 -3 1 2 2 4 total 0.036193 0.007028 -4 1 2 2 5 total 0.038098 0.006769 -5 1 2 2 6 total 0.024764 0.004638 -6 1 2 2 7 total 0.034288 0.008049 -7 1 2 2 8 total 0.040003 0.007350 -8 1 2 2 9 total 0.032383 0.003211 -9 1 2 2 10 total 0.050480 0.005824 -10 1 2 2 11 total 0.045718 0.013291 +0 1 2 2 1 total 0.037212 0.004892 +1 1 2 2 2 total 0.039224 0.003682 +2 1 2 2 3 total 0.044253 0.005869 +3 1 2 2 4 total 0.043247 0.004970 +4 1 2 2 5 total 0.025144 0.006632 +5 1 2 2 6 total 0.037212 0.009199 +6 1 2 2 7 total 0.035201 0.008964 +7 1 2 2 8 total 0.041235 0.009733 +8 1 2 2 9 total 0.032184 0.002384 +9 1 2 2 10 total 0.026149 0.006714 +10 1 2 2 11 total 0.035201 0.008073 material group in group out mu bin nuclide mean std. dev. -33 1 1 1 1 total 0.032861 0.003703 -34 1 1 1 2 total 0.026428 0.003637 -35 1 1 1 3 total 0.029210 0.001648 -36 1 1 1 4 total 0.032513 0.004770 -37 1 1 1 5 total 0.030949 0.003129 -38 1 1 1 6 total 0.027124 0.004029 -39 1 1 1 7 total 0.030079 0.002186 -40 1 1 1 8 total 0.037034 0.002198 -41 1 1 1 9 total 0.038251 0.003825 -42 1 1 1 10 total 0.039294 0.003626 -43 1 1 1 11 total 0.062593 0.005934 -22 1 1 2 1 total 0.000000 0.000000 -23 1 1 2 2 total 0.000174 0.000174 -24 1 1 2 3 total 0.000348 0.000213 +33 1 1 1 1 total 0.029945 0.003043 +34 1 1 1 2 total 0.028378 0.003793 +35 1 1 1 3 total 0.033079 0.002866 +36 1 1 1 4 total 0.030119 0.002259 +37 1 1 1 5 total 0.033601 0.003739 +38 1 1 1 6 total 0.035516 0.001929 +39 1 1 1 7 total 0.032382 0.001744 +40 1 1 1 8 total 0.031860 0.002565 +41 1 1 1 9 total 0.038302 0.004757 +42 1 1 1 10 total 0.041784 0.003047 +43 1 1 1 11 total 0.057453 0.003686 +22 1 1 2 1 total 0.000174 0.000174 +23 1 1 2 2 total 0.000000 0.000000 +24 1 1 2 3 total 0.000174 0.000174 25 1 1 2 4 total 0.000174 0.000174 26 1 1 2 5 total 0.000000 0.000000 27 1 1 2 6 total 0.000000 0.000000 @@ -77,33 +77,33 @@ 19 1 2 1 9 total 0.000000 0.000000 20 1 2 1 10 total 0.000000 0.000000 21 1 2 1 11 total 0.000000 0.000000 -0 1 2 2 1 total 0.032383 0.006826 -1 1 2 2 2 total 0.037146 0.001158 -2 1 2 2 3 total 0.036193 0.004463 -3 1 2 2 4 total 0.036193 0.007028 -4 1 2 2 5 total 0.038098 0.006769 -5 1 2 2 6 total 0.024764 0.004638 -6 1 2 2 7 total 0.034288 0.008049 -7 1 2 2 8 total 0.040003 0.007350 -8 1 2 2 9 total 0.032383 0.003211 -9 1 2 2 10 total 0.050480 0.005824 -10 1 2 2 11 total 0.045718 0.013291 +0 1 2 2 1 total 0.037212 0.004892 +1 1 2 2 2 total 0.039224 0.003682 +2 1 2 2 3 total 0.044253 0.005869 +3 1 2 2 4 total 0.043247 0.004970 +4 1 2 2 5 total 0.025144 0.006632 +5 1 2 2 6 total 0.037212 0.009199 +6 1 2 2 7 total 0.035201 0.008964 +7 1 2 2 8 total 0.041235 0.009733 +8 1 2 2 9 total 0.032184 0.002384 +9 1 2 2 10 total 0.026149 0.006714 +10 1 2 2 11 total 0.035201 0.008073 material group in group out mu bin nuclide mean std. dev. -33 1 1 1 1 total 0.032927 0.003848 -34 1 1 1 2 total 0.026481 0.003736 -35 1 1 1 3 total 0.029268 0.001884 -36 1 1 1 4 total 0.032578 0.004885 -37 1 1 1 5 total 0.031010 0.003280 -38 1 1 1 6 total 0.027177 0.004124 -39 1 1 1 7 total 0.030139 0.002382 -40 1 1 1 8 total 0.037108 0.002485 -41 1 1 1 9 total 0.038327 0.004013 -42 1 1 1 10 total 0.039372 0.003833 -43 1 1 1 11 total 0.062717 0.006256 -22 1 1 2 1 total 0.000000 0.000000 -23 1 1 2 2 total 0.000174 0.000174 -24 1 1 2 3 total 0.000348 0.000214 -25 1 1 2 4 total 0.000174 0.000174 +33 1 1 1 1 total 0.030147 0.003165 +34 1 1 1 2 total 0.028570 0.003893 +35 1 1 1 3 total 0.033302 0.003016 +36 1 1 1 4 total 0.030322 0.002411 +37 1 1 1 5 total 0.033828 0.003868 +38 1 1 1 6 total 0.035756 0.002159 +39 1 1 1 7 total 0.032601 0.001955 +40 1 1 1 8 total 0.032075 0.002718 +41 1 1 1 9 total 0.038560 0.004896 +42 1 1 1 10 total 0.042066 0.003262 +43 1 1 1 11 total 0.057840 0.004013 +22 1 1 2 1 total 0.000175 0.000175 +23 1 1 2 2 total 0.000000 0.000000 +24 1 1 2 3 total 0.000175 0.000175 +25 1 1 2 4 total 0.000175 0.000175 26 1 1 2 5 total 0.000000 0.000000 27 1 1 2 6 total 0.000000 0.000000 28 1 1 2 7 total 0.000000 0.000000 @@ -122,33 +122,33 @@ 19 1 2 1 9 total 0.000000 0.000000 20 1 2 1 10 total 0.000000 0.000000 21 1 2 1 11 total 0.000000 0.000000 -0 1 2 2 1 total 0.031440 0.006860 -1 1 2 2 2 total 0.036063 0.002322 -2 1 2 2 3 total 0.035138 0.004763 -3 1 2 2 4 total 0.035138 0.007105 -4 1 2 2 5 total 0.036988 0.006894 -5 1 2 2 6 total 0.024042 0.004702 -6 1 2 2 7 total 0.033289 0.008036 -7 1 2 2 8 total 0.038837 0.007464 -8 1 2 2 9 total 0.031440 0.003585 -9 1 2 2 10 total 0.049009 0.006292 -10 1 2 2 11 total 0.044385 0.013144 +0 1 2 2 1 total 0.037164 0.005797 +1 1 2 2 2 total 0.039173 0.004933 +2 1 2 2 3 total 0.044195 0.006937 +3 1 2 2 4 total 0.043191 0.006147 +4 1 2 2 5 total 0.025111 0.006951 +5 1 2 2 6 total 0.037164 0.009702 +6 1 2 2 7 total 0.035155 0.009426 +7 1 2 2 8 total 0.041182 0.010317 +8 1 2 2 9 total 0.032142 0.003598 +9 1 2 2 10 total 0.026115 0.007055 +10 1 2 2 11 total 0.035155 0.008586 material group in group out mu bin nuclide mean std. dev. -33 1 1 1 1 total 0.032927 0.004236 -34 1 1 1 2 total 0.026481 0.003998 -35 1 1 1 3 total 0.029268 0.002455 -36 1 1 1 4 total 0.032578 0.005190 -37 1 1 1 5 total 0.031010 0.003679 -38 1 1 1 6 total 0.027177 0.004376 -39 1 1 1 7 total 0.030139 0.002881 -40 1 1 1 8 total 0.037108 0.003187 -41 1 1 1 9 total 0.038327 0.004511 -42 1 1 1 10 total 0.039372 0.004379 -43 1 1 1 11 total 0.062717 0.007108 -22 1 1 2 1 total 0.000000 0.000000 -23 1 1 2 2 total 0.000174 0.000209 -24 1 1 2 3 total 0.000348 0.000315 -25 1 1 2 4 total 0.000174 0.000209 +33 1 1 1 1 total 0.030147 0.003454 +34 1 1 1 2 total 0.028570 0.004107 +35 1 1 1 3 total 0.033302 0.003381 +36 1 1 1 4 total 0.030322 0.002783 +37 1 1 1 5 total 0.033828 0.004168 +38 1 1 1 6 total 0.035756 0.002711 +39 1 1 1 7 total 0.032601 0.002461 +40 1 1 1 8 total 0.032075 0.003090 +41 1 1 1 9 total 0.038560 0.005205 +42 1 1 1 10 total 0.042066 0.003790 +43 1 1 1 11 total 0.057840 0.004811 +22 1 1 2 1 total 0.000175 0.000234 +23 1 1 2 2 total 0.000000 0.000000 +24 1 1 2 3 total 0.000175 0.000234 +25 1 1 2 4 total 0.000175 0.000234 26 1 1 2 5 total 0.000000 0.000000 27 1 1 2 6 total 0.000000 0.000000 28 1 1 2 7 total 0.000000 0.000000 @@ -167,29 +167,29 @@ 19 1 2 1 9 total 0.000000 0.000000 20 1 2 1 10 total 0.000000 0.000000 21 1 2 1 11 total 0.000000 0.000000 -0 1 2 2 1 total 0.031440 0.007170 -1 1 2 2 2 total 0.036063 0.003334 -2 1 2 2 3 total 0.035138 0.005303 -3 1 2 2 4 total 0.035138 0.007478 -4 1 2 2 5 total 0.036988 0.007318 -5 1 2 2 6 total 0.024042 0.004965 -6 1 2 2 7 total 0.033289 0.008334 -7 1 2 2 8 total 0.038837 0.007896 -8 1 2 2 9 total 0.031440 0.004148 -9 1 2 2 10 total 0.049009 0.007083 -10 1 2 2 11 total 0.044385 0.013469 +0 1 2 2 1 total 0.037164 0.006511 +1 1 2 2 2 total 0.039173 0.005840 +2 1 2 2 3 total 0.044195 0.007782 +3 1 2 2 4 total 0.043191 0.007047 +4 1 2 2 5 total 0.025111 0.007234 +5 1 2 2 6 total 0.037164 0.010146 +6 1 2 2 7 total 0.035155 0.009835 +7 1 2 2 8 total 0.041182 0.010828 +8 1 2 2 9 total 0.032142 0.004419 +9 1 2 2 10 total 0.026115 0.007356 +10 1 2 2 11 total 0.035155 0.009032 material group in group out mu bin nuclide mean std. dev. -33 2 1 1 1 total 0.026798 0.002892 -34 2 1 1 2 total 0.021339 0.003475 -35 2 1 1 3 total 0.021835 0.003963 -36 2 1 1 4 total 0.018361 0.006133 -37 2 1 1 5 total 0.023820 0.003932 -38 2 1 1 6 total 0.025805 0.003808 -39 2 1 1 7 total 0.026798 0.002299 -40 2 1 1 8 total 0.029279 0.003939 -41 2 1 1 9 total 0.034738 0.004323 -42 2 1 1 10 total 0.032753 0.006086 -43 2 1 1 11 total 0.057069 0.003798 +33 2 1 1 1 total 0.025373 0.004281 +34 2 1 1 2 total 0.023909 0.004395 +35 2 1 1 3 total 0.019518 0.003911 +36 2 1 1 4 total 0.019518 0.003424 +37 2 1 1 5 total 0.020006 0.002901 +38 2 1 1 6 total 0.024885 0.005801 +39 2 1 1 7 total 0.019030 0.002566 +40 2 1 1 8 total 0.030741 0.001410 +41 2 1 1 9 total 0.034156 0.002902 +42 2 1 1 10 total 0.042939 0.004498 +43 2 1 1 11 total 0.054650 0.003865 22 2 1 2 1 total 0.000000 0.000000 23 2 1 2 2 total 0.000000 0.000000 24 2 1 2 3 total 0.000000 0.000000 @@ -212,29 +212,29 @@ 19 2 2 1 9 total 0.000000 0.000000 20 2 2 1 10 total 0.000000 0.000000 21 2 2 1 11 total 0.000000 0.000000 -0 2 2 2 1 total 0.032254 0.009449 -1 2 2 2 2 total 0.018815 0.005569 -2 2 2 2 3 total 0.032254 0.009449 -3 2 2 2 4 total 0.024191 0.006844 -4 2 2 2 5 total 0.013439 0.008563 -5 2 2 2 6 total 0.024191 0.005365 -6 2 2 2 7 total 0.043005 0.010420 -7 2 2 2 8 total 0.032254 0.012710 -8 2 2 2 9 total 0.034942 0.007365 -9 2 2 2 10 total 0.021503 0.007051 -10 2 2 2 11 total 0.018815 0.008193 +0 2 2 2 1 total 0.026892 0.012233 +1 2 2 2 2 total 0.034959 0.007449 +2 2 2 2 3 total 0.040337 0.009144 +3 2 2 2 4 total 0.021513 0.003750 +4 2 2 2 5 total 0.018824 0.005602 +5 2 2 2 6 total 0.026892 0.004806 +6 2 2 2 7 total 0.037648 0.012716 +7 2 2 2 8 total 0.026892 0.009768 +8 2 2 2 9 total 0.024202 0.005420 +9 2 2 2 10 total 0.018824 0.010183 +10 2 2 2 11 total 0.018824 0.007033 material group in group out mu bin nuclide mean std. dev. -33 2 1 1 1 total 0.026798 0.002892 -34 2 1 1 2 total 0.021339 0.003475 -35 2 1 1 3 total 0.021835 0.003963 -36 2 1 1 4 total 0.018361 0.006133 -37 2 1 1 5 total 0.023820 0.003932 -38 2 1 1 6 total 0.025805 0.003808 -39 2 1 1 7 total 0.026798 0.002299 -40 2 1 1 8 total 0.029279 0.003939 -41 2 1 1 9 total 0.034738 0.004323 -42 2 1 1 10 total 0.032753 0.006086 -43 2 1 1 11 total 0.057069 0.003798 +33 2 1 1 1 total 0.025373 0.004281 +34 2 1 1 2 total 0.023909 0.004395 +35 2 1 1 3 total 0.019518 0.003911 +36 2 1 1 4 total 0.019518 0.003424 +37 2 1 1 5 total 0.020006 0.002901 +38 2 1 1 6 total 0.024885 0.005801 +39 2 1 1 7 total 0.019030 0.002566 +40 2 1 1 8 total 0.030741 0.001410 +41 2 1 1 9 total 0.034156 0.002902 +42 2 1 1 10 total 0.042939 0.004498 +43 2 1 1 11 total 0.054650 0.003865 22 2 1 2 1 total 0.000000 0.000000 23 2 1 2 2 total 0.000000 0.000000 24 2 1 2 3 total 0.000000 0.000000 @@ -257,29 +257,29 @@ 19 2 2 1 9 total 0.000000 0.000000 20 2 2 1 10 total 0.000000 0.000000 21 2 2 1 11 total 0.000000 0.000000 -0 2 2 2 1 total 0.032254 0.009449 -1 2 2 2 2 total 0.018815 0.005569 -2 2 2 2 3 total 0.032254 0.009449 -3 2 2 2 4 total 0.024191 0.006844 -4 2 2 2 5 total 0.013439 0.008563 -5 2 2 2 6 total 0.024191 0.005365 -6 2 2 2 7 total 0.043005 0.010420 -7 2 2 2 8 total 0.032254 0.012710 -8 2 2 2 9 total 0.034942 0.007365 -9 2 2 2 10 total 0.021503 0.007051 -10 2 2 2 11 total 0.018815 0.008193 +0 2 2 2 1 total 0.026892 0.012233 +1 2 2 2 2 total 0.034959 0.007449 +2 2 2 2 3 total 0.040337 0.009144 +3 2 2 2 4 total 0.021513 0.003750 +4 2 2 2 5 total 0.018824 0.005602 +5 2 2 2 6 total 0.026892 0.004806 +6 2 2 2 7 total 0.037648 0.012716 +7 2 2 2 8 total 0.026892 0.009768 +8 2 2 2 9 total 0.024202 0.005420 +9 2 2 2 10 total 0.018824 0.010183 +10 2 2 2 11 total 0.018824 0.007033 material group in group out mu bin nuclide mean std. dev. -33 2 1 1 1 total 0.026249 0.003012 -34 2 1 1 2 total 0.020902 0.003500 -35 2 1 1 3 total 0.021388 0.003971 -36 2 1 1 4 total 0.017986 0.006048 -37 2 1 1 5 total 0.023333 0.003958 -38 2 1 1 6 total 0.025277 0.003858 -39 2 1 1 7 total 0.026249 0.002473 -40 2 1 1 8 total 0.028680 0.004017 -41 2 1 1 9 total 0.034027 0.004437 -42 2 1 1 10 total 0.032082 0.006091 -43 2 1 1 11 total 0.055901 0.004311 +33 2 1 1 1 total 0.025753 0.004484 +34 2 1 1 2 total 0.024267 0.004581 +35 2 1 1 3 total 0.019810 0.004060 +36 2 1 1 4 total 0.019810 0.003579 +37 2 1 1 5 total 0.020305 0.003071 +38 2 1 1 6 total 0.025258 0.005987 +39 2 1 1 7 total 0.019315 0.002734 +40 2 1 1 8 total 0.031201 0.001961 +41 2 1 1 9 total 0.034668 0.003301 +42 2 1 1 10 total 0.043582 0.004935 +43 2 1 1 11 total 0.055468 0.004591 22 2 1 2 1 total 0.000000 0.000000 23 2 1 2 2 total 0.000000 0.000000 24 2 1 2 3 total 0.000000 0.000000 @@ -302,29 +302,29 @@ 19 2 2 1 9 total 0.000000 0.000000 20 2 2 1 10 total 0.000000 0.000000 21 2 2 1 11 total 0.000000 0.000000 -0 2 2 2 1 total 0.032230 0.009604 -1 2 2 2 2 total 0.018801 0.005658 -2 2 2 2 3 total 0.032230 0.009604 -3 2 2 2 4 total 0.024172 0.006964 -4 2 2 2 5 total 0.013429 0.008588 -5 2 2 2 6 total 0.024172 0.005520 -6 2 2 2 7 total 0.042973 0.010671 -7 2 2 2 8 total 0.032230 0.012821 -8 2 2 2 9 total 0.034915 0.007601 -9 2 2 2 10 total 0.021486 0.007142 -10 2 2 2 11 total 0.018801 0.008251 +0 2 2 2 1 total 0.026854 0.012543 +1 2 2 2 2 total 0.034911 0.008307 +2 2 2 2 3 total 0.040281 0.010079 +3 2 2 2 4 total 0.021483 0.004382 +4 2 2 2 5 total 0.018798 0.005938 +5 2 2 2 6 total 0.026854 0.005579 +6 2 2 2 7 total 0.037596 0.013308 +7 2 2 2 8 total 0.026854 0.010161 +8 2 2 2 9 total 0.024169 0.005987 +9 2 2 2 10 total 0.018798 0.010362 +10 2 2 2 11 total 0.018798 0.007300 material group in group out mu bin nuclide mean std. dev. -33 2 1 1 1 total 0.026249 0.003460 -34 2 1 1 2 total 0.020902 0.003754 -35 2 1 1 3 total 0.021388 0.004206 -36 2 1 1 4 total 0.017986 0.006160 -37 2 1 1 5 total 0.023333 0.004238 -38 2 1 1 6 total 0.025277 0.004192 -39 2 1 1 7 total 0.026249 0.003003 -40 2 1 1 8 total 0.028680 0.004427 -41 2 1 1 9 total 0.034027 0.004956 -42 2 1 1 10 total 0.032082 0.006437 -43 2 1 1 11 total 0.055901 0.005636 +33 2 1 1 1 total 0.025753 0.004661 +34 2 1 1 2 total 0.024267 0.004736 +35 2 1 1 3 total 0.019810 0.004177 +36 2 1 1 4 total 0.019810 0.003711 +37 2 1 1 5 total 0.020305 0.003231 +38 2 1 1 6 total 0.025258 0.006117 +39 2 1 1 7 total 0.019315 0.002897 +40 2 1 1 8 total 0.031201 0.002497 +41 2 1 1 9 total 0.034668 0.003721 +42 2 1 1 10 total 0.043582 0.005386 +43 2 1 1 11 total 0.055468 0.005350 22 2 1 2 1 total 0.000000 0.000000 23 2 1 2 2 total 0.000000 0.000000 24 2 1 2 3 total 0.000000 0.000000 @@ -347,40 +347,40 @@ 19 2 2 1 9 total 0.000000 0.000000 20 2 2 1 10 total 0.000000 0.000000 21 2 2 1 11 total 0.000000 0.000000 -0 2 2 2 1 total 0.032230 0.010330 -1 2 2 2 2 total 0.018801 0.006077 -2 2 2 2 3 total 0.032230 0.010330 -3 2 2 2 4 total 0.024172 0.007526 -4 2 2 2 5 total 0.013429 0.008733 -5 2 2 2 6 total 0.024172 0.006213 -6 2 2 2 7 total 0.042973 0.011815 -7 2 2 2 8 total 0.032230 0.013373 -8 2 2 2 9 total 0.034915 0.008646 -9 2 2 2 10 total 0.021486 0.007579 -10 2 2 2 11 total 0.018801 0.008544 +0 2 2 2 1 total 0.026854 0.013054 +1 2 2 2 2 total 0.034911 0.009546 +2 2 2 2 3 total 0.040281 0.011446 +3 2 2 2 4 total 0.021483 0.005251 +4 2 2 2 5 total 0.018798 0.006456 +5 2 2 2 6 total 0.026854 0.006649 +6 2 2 2 7 total 0.037596 0.014239 +7 2 2 2 8 total 0.026854 0.010785 +8 2 2 2 9 total 0.024169 0.006815 +9 2 2 2 10 total 0.018798 0.010667 +10 2 2 2 11 total 0.018798 0.007727 material group in group out mu bin nuclide mean std. dev. -33 3 1 1 1 total 0.007006 0.000692 -34 3 1 1 2 total 0.006819 0.000431 -35 3 1 1 3 total 0.005511 0.000591 -36 3 1 1 4 total 0.006165 0.000470 -37 3 1 1 5 total 0.007660 0.000919 -38 3 1 1 6 total 0.012237 0.000938 -39 3 1 1 7 total 0.040914 0.002235 -40 3 1 1 8 total 0.074356 0.001968 -41 3 1 1 9 total 0.121622 0.004662 -42 3 1 1 10 total 0.158707 0.004147 -43 3 1 1 11 total 0.200742 0.007791 -22 3 1 2 1 total 0.000187 0.000187 -23 3 1 2 2 total 0.001028 0.000096 -24 3 1 2 3 total 0.000841 0.000176 -25 3 1 2 4 total 0.000841 0.000310 -26 3 1 2 5 total 0.001308 0.000274 -27 3 1 2 6 total 0.003736 0.000538 -28 3 1 2 7 total 0.003830 0.000703 -29 3 1 2 8 total 0.006259 0.000452 -30 3 1 2 9 total 0.005231 0.000510 -31 3 1 2 10 total 0.005044 0.000440 -32 3 1 2 11 total 0.002522 0.000194 +33 3 1 1 1 total 0.007681 0.001043 +34 3 1 1 2 total 0.005645 0.000710 +35 3 1 1 3 total 0.007403 0.000552 +36 3 1 1 4 total 0.007866 0.000512 +37 3 1 1 5 total 0.007589 0.000524 +38 3 1 1 6 total 0.011198 0.001548 +39 3 1 1 7 total 0.039701 0.002533 +40 3 1 1 8 total 0.075978 0.001897 +41 3 1 1 9 total 0.112532 0.003677 +42 3 1 1 10 total 0.166670 0.005003 +43 3 1 1 11 total 0.210443 0.005656 +22 3 1 2 1 total 0.000463 0.000207 +23 3 1 2 2 total 0.000555 0.000227 +24 3 1 2 3 total 0.000740 0.000429 +25 3 1 2 4 total 0.001111 0.000236 +26 3 1 2 5 total 0.002128 0.000631 +27 3 1 2 6 total 0.003146 0.000645 +28 3 1 2 7 total 0.004905 0.000561 +29 3 1 2 8 total 0.005738 0.000742 +30 3 1 2 9 total 0.005090 0.000672 +31 3 1 2 10 total 0.005367 0.000561 +32 3 1 2 11 total 0.002406 0.000593 11 3 2 1 1 total 0.000000 0.000000 12 3 2 1 2 total 0.000000 0.000000 13 3 2 1 3 total 0.000000 0.000000 @@ -390,42 +390,42 @@ 17 3 2 1 7 total 0.000000 0.000000 18 3 2 1 8 total 0.000000 0.000000 19 3 2 1 9 total 0.000000 0.000000 -20 3 2 1 10 total 0.000467 0.000467 -21 3 2 1 11 total 0.000000 0.000000 -0 3 2 2 1 total 0.084030 0.007630 -1 3 2 2 2 total 0.099902 0.010027 -2 3 2 2 3 total 0.112040 0.010928 -3 3 2 2 4 total 0.117642 0.008523 -4 3 2 2 5 total 0.139116 0.009002 -5 3 2 2 6 total 0.161057 0.013537 -6 3 2 2 7 total 0.180664 0.010135 -7 3 2 2 8 total 0.219411 0.014717 -8 3 2 2 9 total 0.239485 0.027005 -9 3 2 2 10 total 0.281033 0.021376 -10 3 2 2 11 total 0.369731 0.027200 +20 3 2 1 10 total 0.000000 0.000000 +21 3 2 1 11 total 0.000474 0.000475 +0 3 2 2 1 total 0.074402 0.007811 +1 3 2 2 2 total 0.103783 0.009042 +2 3 2 2 3 total 0.106153 0.012691 +3 3 2 2 4 total 0.115631 0.011475 +4 3 2 2 5 total 0.128900 0.014096 +5 3 2 2 6 total 0.169655 0.021010 +6 3 2 2 7 total 0.175816 0.016086 +7 3 2 2 8 total 0.217519 0.029631 +8 3 2 2 9 total 0.247374 0.021476 +9 3 2 2 10 total 0.299977 0.031756 +10 3 2 2 11 total 0.351157 0.027654 material group in group out mu bin nuclide mean std. dev. -33 3 1 1 1 total 0.007006 0.000692 -34 3 1 1 2 total 0.006819 0.000431 -35 3 1 1 3 total 0.005511 0.000591 -36 3 1 1 4 total 0.006165 0.000470 -37 3 1 1 5 total 0.007660 0.000919 -38 3 1 1 6 total 0.012237 0.000938 -39 3 1 1 7 total 0.040914 0.002235 -40 3 1 1 8 total 0.074356 0.001968 -41 3 1 1 9 total 0.121622 0.004662 -42 3 1 1 10 total 0.158707 0.004147 -43 3 1 1 11 total 0.200742 0.007791 -22 3 1 2 1 total 0.000187 0.000187 -23 3 1 2 2 total 0.001028 0.000096 -24 3 1 2 3 total 0.000841 0.000176 -25 3 1 2 4 total 0.000841 0.000310 -26 3 1 2 5 total 0.001308 0.000274 -27 3 1 2 6 total 0.003736 0.000538 -28 3 1 2 7 total 0.003830 0.000703 -29 3 1 2 8 total 0.006259 0.000452 -30 3 1 2 9 total 0.005231 0.000510 -31 3 1 2 10 total 0.005044 0.000440 -32 3 1 2 11 total 0.002522 0.000194 +33 3 1 1 1 total 0.007681 0.001043 +34 3 1 1 2 total 0.005645 0.000710 +35 3 1 1 3 total 0.007403 0.000552 +36 3 1 1 4 total 0.007866 0.000512 +37 3 1 1 5 total 0.007589 0.000524 +38 3 1 1 6 total 0.011198 0.001548 +39 3 1 1 7 total 0.039701 0.002533 +40 3 1 1 8 total 0.075978 0.001897 +41 3 1 1 9 total 0.112532 0.003677 +42 3 1 1 10 total 0.166670 0.005003 +43 3 1 1 11 total 0.210443 0.005656 +22 3 1 2 1 total 0.000463 0.000207 +23 3 1 2 2 total 0.000555 0.000227 +24 3 1 2 3 total 0.000740 0.000429 +25 3 1 2 4 total 0.001111 0.000236 +26 3 1 2 5 total 0.002128 0.000631 +27 3 1 2 6 total 0.003146 0.000645 +28 3 1 2 7 total 0.004905 0.000561 +29 3 1 2 8 total 0.005738 0.000742 +30 3 1 2 9 total 0.005090 0.000672 +31 3 1 2 10 total 0.005367 0.000561 +32 3 1 2 11 total 0.002406 0.000593 11 3 2 1 1 total 0.000000 0.000000 12 3 2 1 2 total 0.000000 0.000000 13 3 2 1 3 total 0.000000 0.000000 @@ -435,42 +435,42 @@ 17 3 2 1 7 total 0.000000 0.000000 18 3 2 1 8 total 0.000000 0.000000 19 3 2 1 9 total 0.000000 0.000000 -20 3 2 1 10 total 0.000467 0.000467 -21 3 2 1 11 total 0.000000 0.000000 -0 3 2 2 1 total 0.084030 0.007630 -1 3 2 2 2 total 0.099902 0.010027 -2 3 2 2 3 total 0.112040 0.010928 -3 3 2 2 4 total 0.117642 0.008523 -4 3 2 2 5 total 0.139116 0.009002 -5 3 2 2 6 total 0.161057 0.013537 -6 3 2 2 7 total 0.180664 0.010135 -7 3 2 2 8 total 0.219411 0.014717 -8 3 2 2 9 total 0.239485 0.027005 -9 3 2 2 10 total 0.281033 0.021376 -10 3 2 2 11 total 0.369731 0.027200 +20 3 2 1 10 total 0.000000 0.000000 +21 3 2 1 11 total 0.000474 0.000475 +0 3 2 2 1 total 0.074402 0.007811 +1 3 2 2 2 total 0.103783 0.009042 +2 3 2 2 3 total 0.106153 0.012691 +3 3 2 2 4 total 0.115631 0.011475 +4 3 2 2 5 total 0.128900 0.014096 +5 3 2 2 6 total 0.169655 0.021010 +6 3 2 2 7 total 0.175816 0.016086 +7 3 2 2 8 total 0.217519 0.029631 +8 3 2 2 9 total 0.247374 0.021476 +9 3 2 2 10 total 0.299977 0.031756 +10 3 2 2 11 total 0.351157 0.027654 material group in group out mu bin nuclide mean std. dev. -33 3 1 1 1 total 0.007106 0.000737 -34 3 1 1 2 total 0.006917 0.000488 -35 3 1 1 3 total 0.005590 0.000624 -36 3 1 1 4 total 0.006254 0.000516 -37 3 1 1 5 total 0.007770 0.000964 -38 3 1 1 6 total 0.012412 0.001029 -39 3 1 1 7 total 0.041501 0.002618 -40 3 1 1 8 total 0.075421 0.003106 -41 3 1 1 9 total 0.123365 0.006125 -42 3 1 1 10 total 0.160981 0.006595 -43 3 1 1 11 total 0.203618 0.010185 -22 3 1 2 1 total 0.000190 0.000190 -23 3 1 2 2 total 0.001042 0.000103 -24 3 1 2 3 total 0.000853 0.000180 -25 3 1 2 4 total 0.000853 0.000316 -26 3 1 2 5 total 0.001327 0.000281 -27 3 1 2 6 total 0.003790 0.000559 -28 3 1 2 7 total 0.003885 0.000724 -29 3 1 2 8 total 0.006348 0.000500 -30 3 1 2 9 total 0.005306 0.000544 -31 3 1 2 10 total 0.005117 0.000475 -32 3 1 2 11 total 0.002558 0.000213 +33 3 1 1 1 total 0.007759 0.001080 +34 3 1 1 2 total 0.005703 0.000738 +35 3 1 1 3 total 0.007479 0.000602 +36 3 1 1 4 total 0.007946 0.000571 +37 3 1 1 5 total 0.007666 0.000578 +38 3 1 1 6 total 0.011312 0.001601 +39 3 1 1 7 total 0.040106 0.002833 +40 3 1 1 8 total 0.076753 0.003016 +41 3 1 1 9 total 0.113680 0.005068 +42 3 1 1 10 total 0.168370 0.007185 +43 3 1 1 11 total 0.212589 0.008616 +22 3 1 2 1 total 0.000467 0.000210 +23 3 1 2 2 total 0.000561 0.000230 +24 3 1 2 3 total 0.000748 0.000434 +25 3 1 2 4 total 0.001122 0.000241 +26 3 1 2 5 total 0.002150 0.000641 +27 3 1 2 6 total 0.003179 0.000659 +28 3 1 2 7 total 0.004955 0.000586 +29 3 1 2 8 total 0.005796 0.000770 +30 3 1 2 9 total 0.005142 0.000697 +31 3 1 2 10 total 0.005422 0.000590 +32 3 1 2 11 total 0.002431 0.000604 11 3 2 1 1 total 0.000000 0.000000 12 3 2 1 2 total 0.000000 0.000000 13 3 2 1 3 total 0.000000 0.000000 @@ -480,42 +480,42 @@ 17 3 2 1 7 total 0.000000 0.000000 18 3 2 1 8 total 0.000000 0.000000 19 3 2 1 9 total 0.000000 0.000000 -20 3 2 1 10 total 0.000466 0.000467 -21 3 2 1 11 total 0.000000 0.000000 -0 3 2 2 1 total 0.083912 0.007782 -1 3 2 2 2 total 0.099762 0.010188 -2 3 2 2 3 total 0.111883 0.011115 -3 3 2 2 4 total 0.117477 0.008794 -4 3 2 2 5 total 0.138921 0.009363 -5 3 2 2 6 total 0.160831 0.013853 -6 3 2 2 7 total 0.180411 0.010676 -7 3 2 2 8 total 0.219104 0.015265 -8 3 2 2 9 total 0.239149 0.027341 -9 3 2 2 10 total 0.280639 0.021991 -10 3 2 2 11 total 0.369213 0.028038 +20 3 2 1 10 total 0.000000 0.000000 +21 3 2 1 11 total 0.000477 0.000479 +0 3 2 2 1 total 0.074833 0.009685 +1 3 2 2 2 total 0.104384 0.012046 +2 3 2 2 3 total 0.106768 0.015107 +3 3 2 2 4 total 0.116300 0.014515 +4 3 2 2 5 total 0.129646 0.017242 +5 3 2 2 6 total 0.170637 0.024765 +6 3 2 2 7 total 0.176834 0.020997 +7 3 2 2 8 total 0.218778 0.034093 +8 3 2 2 9 total 0.248807 0.028656 +9 3 2 2 10 total 0.301714 0.039263 +10 3 2 2 11 total 0.353191 0.038577 material group in group out mu bin nuclide mean std. dev. -33 3 1 1 1 total 0.007106 0.000751 -34 3 1 1 2 total 0.006917 0.000509 -35 3 1 1 3 total 0.005590 0.000635 -36 3 1 1 4 total 0.006254 0.000532 -37 3 1 1 5 total 0.007770 0.000977 -38 3 1 1 6 total 0.012412 0.001060 -39 3 1 1 7 total 0.041501 0.002755 -40 3 1 1 8 total 0.075421 0.003475 -41 3 1 1 9 total 0.123365 0.006634 -42 3 1 1 10 total 0.160981 0.007387 -43 3 1 1 11 total 0.203618 0.011019 -22 3 1 2 1 total 0.000190 0.000190 -23 3 1 2 2 total 0.001042 0.000114 -24 3 1 2 3 total 0.000853 0.000185 -25 3 1 2 4 total 0.000853 0.000319 -26 3 1 2 5 total 0.001327 0.000288 -27 3 1 2 6 total 0.003790 0.000588 -28 3 1 2 7 total 0.003885 0.000748 -29 3 1 2 8 total 0.006348 0.000587 -30 3 1 2 9 total 0.005306 0.000601 -31 3 1 2 10 total 0.005117 0.000535 -32 3 1 2 11 total 0.002558 0.000246 +33 3 1 1 1 total 0.007759 0.001091 +34 3 1 1 2 total 0.005703 0.000746 +35 3 1 1 3 total 0.007479 0.000619 +36 3 1 1 4 total 0.007946 0.000592 +37 3 1 1 5 total 0.007666 0.000598 +38 3 1 1 6 total 0.011312 0.001616 +39 3 1 1 7 total 0.040106 0.002941 +40 3 1 1 8 total 0.076753 0.003373 +41 3 1 1 9 total 0.113680 0.005540 +42 3 1 1 10 total 0.168370 0.007913 +43 3 1 1 11 total 0.212589 0.009578 +22 3 1 2 1 total 0.000467 0.000211 +23 3 1 2 2 total 0.000561 0.000232 +24 3 1 2 3 total 0.000748 0.000436 +25 3 1 2 4 total 0.001122 0.000250 +26 3 1 2 5 total 0.002150 0.000653 +27 3 1 2 6 total 0.003179 0.000684 +28 3 1 2 7 total 0.004955 0.000654 +29 3 1 2 8 total 0.005796 0.000841 +30 3 1 2 9 total 0.005142 0.000759 +31 3 1 2 10 total 0.005422 0.000670 +32 3 1 2 11 total 0.002431 0.000620 11 3 2 1 1 total 0.000000 0.000000 12 3 2 1 2 total 0.000000 0.000000 13 3 2 1 3 total 0.000000 0.000000 @@ -525,16 +525,16 @@ 17 3 2 1 7 total 0.000000 0.000000 18 3 2 1 8 total 0.000000 0.000000 19 3 2 1 9 total 0.000000 0.000000 -20 3 2 1 10 total 0.000466 0.000808 -21 3 2 1 11 total 0.000000 0.000000 -0 3 2 2 1 total 0.083912 0.008936 -1 3 2 2 2 total 0.099762 0.011448 -2 3 2 2 3 total 0.111883 0.012563 -3 3 2 2 4 total 0.117477 0.010731 -4 3 2 2 5 total 0.138921 0.011855 -5 3 2 2 6 total 0.160831 0.016211 -6 3 2 2 7 total 0.180411 0.014254 -7 3 2 2 8 total 0.219104 0.019093 -8 3 2 2 9 total 0.239149 0.030071 -9 3 2 2 10 total 0.280639 0.026447 -10 3 2 2 11 total 0.369213 0.034054 +20 3 2 1 10 total 0.000000 0.000000 +21 3 2 1 11 total 0.000477 0.000827 +0 3 2 2 1 total 0.074833 0.011051 +1 3 2 2 2 total 0.104384 0.014150 +2 3 2 2 3 total 0.106768 0.016908 +3 3 2 2 4 total 0.116300 0.016707 +4 3 2 2 5 total 0.129646 0.019553 +5 3 2 2 6 total 0.170637 0.027579 +6 3 2 2 7 total 0.176834 0.024476 +7 3 2 2 8 total 0.218778 0.037476 +8 3 2 2 9 total 0.248807 0.033680 +9 3 2 2 10 total 0.301714 0.044745 +10 3 2 2 11 total 0.353191 0.046035 diff --git a/tests/regression_tests/mgxs_library_histogram/test.py b/tests/regression_tests/mgxs_library_histogram/test.py index b9905910ab..42fc1957a6 100644 --- a/tests/regression_tests/mgxs_library_histogram/test.py +++ b/tests/regression_tests/mgxs_library_histogram/test.py @@ -30,7 +30,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_mesh/results_true.dat b/tests/regression_tests/mgxs_library_mesh/results_true.dat index b1e8ac003b..16b86870d7 100644 --- a/tests/regression_tests/mgxs_library_mesh/results_true.dat +++ b/tests/regression_tests/mgxs_library_mesh/results_true.dat @@ -1,362 +1,362 @@ mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.102539 0.004894 -2 1 2 1 1 total 0.106476 0.007513 -1 2 1 1 1 total 0.101207 0.004814 -3 2 2 1 1 total 0.101733 0.004445 +0 1 1 1 1 total 0.103374 0.004981 +2 1 2 1 1 total 0.103852 0.004752 +1 2 1 1 1 total 0.103322 0.003613 +3 2 2 1 1 total 0.102889 0.003387 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.073423 0.005232 -2 1 2 1 1 total 0.077906 0.007749 -1 2 1 1 1 total 0.071315 0.005181 -3 2 2 1 1 total 0.071983 0.004856 +0 1 1 1 1 total 0.072760 0.005235 +2 1 2 1 1 total 0.074856 0.004972 +1 2 1 1 1 total 0.074583 0.004000 +3 2 2 1 1 total 0.072925 0.003485 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.073443 0.005235 -2 1 2 1 1 total 0.077909 0.007749 -1 2 1 1 1 total 0.071315 0.005181 -3 2 2 1 1 total 0.071928 0.004865 +0 1 1 1 1 total 0.072768 0.005236 +2 1 2 1 1 total 0.074864 0.004972 +1 2 1 1 1 total 0.074603 0.004002 +3 2 2 1 1 total 0.072881 0.003491 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.013089 0.000762 -2 1 2 1 1 total 0.013802 0.000950 -1 2 1 1 1 total 0.012818 0.000708 -3 2 2 1 1 total 0.012954 0.000699 +0 1 1 1 1 total 0.013309 0.000729 +2 1 2 1 1 total 0.013223 0.000707 +1 2 1 1 1 total 0.013222 0.000596 +3 2 2 1 1 total 0.013282 0.000564 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.013016 0.000761 -2 1 2 1 1 total 0.013715 0.000947 -1 2 1 1 1 total 0.012740 0.000707 -3 2 2 1 1 total 0.012886 0.000698 +0 1 1 1 1 total 0.013241 0.000728 +2 1 2 1 1 total 0.013142 0.000705 +1 2 1 1 1 total 0.013137 0.000596 +3 2 2 1 1 total 0.013221 0.000564 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.001244 0.000926 -2 1 2 1 1 total 0.001345 0.000851 -1 2 1 1 1 total 0.001196 0.000768 -3 2 2 1 1 total 0.001234 0.000843 +0 1 1 1 1 total 0.001281 0.000874 +2 1 2 1 1 total 0.001297 0.000731 +1 2 1 1 1 total 0.001281 0.000744 +3 2 2 1 1 total 0.001288 0.000719 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.011844 0.000690 -2 1 2 1 1 total 0.012457 0.000852 -1 2 1 1 1 total 0.011622 0.000636 -3 2 2 1 1 total 0.011719 0.000633 +0 1 1 1 1 total 0.012029 0.000664 +2 1 2 1 1 total 0.011926 0.000639 +1 2 1 1 1 total 0.011941 0.000545 +3 2 2 1 1 total 0.011994 0.000515 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.030919 0.001784 -2 1 2 1 1 total 0.032495 0.002202 -1 2 1 1 1 total 0.030363 0.001664 -3 2 2 1 1 total 0.030565 0.001671 +0 1 1 1 1 total 0.031361 0.001735 +2 1 2 1 1 total 0.031091 0.001675 +1 2 1 1 1 total 0.031169 0.001418 +3 2 2 1 1 total 0.031255 0.001366 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 2.290786e+06 133521.277651 -2 1 2 1 1 total 2.409292e+06 164752.430241 -1 2 1 1 1 total 2.247742e+06 123005.689035 -3 2 2 1 1 total 2.266603e+06 122428.448367 +0 1 1 1 1 total 2.326447e+06 128504.886535 +2 1 2 1 1 total 2.306518e+06 123638.096130 +1 2 1 1 1 total 2.309435e+06 105395.059055 +3 2 2 1 1 total 2.319667e+06 99692.620001 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.089450 0.004147 -2 1 2 1 1 total 0.092674 0.006571 -1 2 1 1 1 total 0.088389 0.004152 -3 2 2 1 1 total 0.088779 0.003763 +0 1 1 1 1 total 0.090065 0.004262 +2 1 2 1 1 total 0.090629 0.004086 +1 2 1 1 1 total 0.090100 0.003045 +3 2 2 1 1 total 0.089607 0.002828 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.089555 0.004061 -2 1 2 1 1 total 0.092658 0.006216 -1 2 1 1 1 total 0.088293 0.004423 -3 2 2 1 1 total 0.088717 0.004937 +0 1 1 1 1 total 0.090188 0.005151 +2 1 2 1 1 total 0.094339 0.004349 +1 2 1 1 1 total 0.088294 0.003953 +3 2 2 1 1 total 0.089633 0.002592 mesh 1 group in group out legendre nuclide mean std. dev. x y z -0 1 1 1 1 1 P0 total 0.089523 0.004070 -1 1 1 1 1 1 P1 total 0.029116 0.001851 -2 1 1 1 1 1 P2 total 0.016529 0.000827 -3 1 1 1 1 1 P3 total 0.009975 0.000731 -8 1 2 1 1 1 P0 total 0.092626 0.006233 -9 1 2 1 1 1 P1 total 0.028570 0.001899 -10 1 2 1 1 1 P2 total 0.015737 0.001986 -11 1 2 1 1 1 P3 total 0.008492 0.000859 -4 2 1 1 1 1 P0 total 0.088293 0.004423 -5 2 1 1 1 1 P1 total 0.029892 0.001916 -6 2 1 1 1 1 P2 total 0.016736 0.000714 -7 2 1 1 1 1 P3 total 0.009129 0.000509 -12 2 2 1 1 1 P0 total 0.088617 0.004889 -13 2 2 1 1 1 P1 total 0.029750 0.001954 -14 2 2 1 1 1 P2 total 0.016440 0.001320 -15 2 2 1 1 1 P3 total 0.009758 0.000538 +0 1 1 1 1 1 P0 total 0.090122 0.005149 +1 1 1 1 1 1 P1 total 0.030614 0.001612 +2 1 1 1 1 1 P2 total 0.016490 0.000897 +3 1 1 1 1 1 P3 total 0.010163 0.000829 +8 1 2 1 1 1 P0 total 0.094307 0.004337 +9 1 2 1 1 1 P1 total 0.028996 0.001462 +10 1 2 1 1 1 P2 total 0.017486 0.000808 +11 1 2 1 1 1 P3 total 0.009753 0.000742 +4 2 1 1 1 1 P0 total 0.088198 0.003959 +5 2 1 1 1 1 P1 total 0.028739 0.001715 +6 2 1 1 1 1 P2 total 0.015608 0.000680 +7 2 1 1 1 1 P3 total 0.008232 0.000363 +12 2 2 1 1 1 P0 total 0.089536 0.002551 +13 2 2 1 1 1 P1 total 0.029964 0.000821 +14 2 2 1 1 1 P2 total 0.015742 0.001260 +15 2 2 1 1 1 P3 total 0.008944 0.000385 mesh 1 group in group out legendre nuclide mean std. dev. x y z -0 1 1 1 1 1 P0 total 0.089555 0.004061 -1 1 1 1 1 1 P1 total 0.029096 0.001859 -2 1 1 1 1 1 P2 total 0.016532 0.000828 -3 1 1 1 1 1 P3 total 0.009986 0.000734 -8 1 2 1 1 1 P0 total 0.092658 0.006216 -9 1 2 1 1 1 P1 total 0.028567 0.001899 -10 1 2 1 1 1 P2 total 0.015721 0.001995 -11 1 2 1 1 1 P3 total 0.008496 0.000857 -4 2 1 1 1 1 P0 total 0.088293 0.004423 -5 2 1 1 1 1 P1 total 0.029892 0.001916 -6 2 1 1 1 1 P2 total 0.016736 0.000714 -7 2 1 1 1 1 P3 total 0.009129 0.000509 -12 2 2 1 1 1 P0 total 0.088717 0.004937 -13 2 2 1 1 1 P1 total 0.029805 0.001977 -14 2 2 1 1 1 P2 total 0.016448 0.001327 -15 2 2 1 1 1 P3 total 0.009752 0.000534 +0 1 1 1 1 1 P0 total 0.090188 0.005151 +1 1 1 1 1 1 P1 total 0.030606 0.001614 +2 1 1 1 1 1 P2 total 0.016462 0.000898 +3 1 1 1 1 1 P3 total 0.010173 0.000824 +8 1 2 1 1 1 P0 total 0.094339 0.004349 +9 1 2 1 1 1 P1 total 0.028988 0.001462 +10 1 2 1 1 1 P2 total 0.017473 0.000811 +11 1 2 1 1 1 P3 total 0.009763 0.000749 +4 2 1 1 1 1 P0 total 0.088294 0.003953 +5 2 1 1 1 1 P1 total 0.028719 0.001720 +6 2 1 1 1 1 P2 total 0.015571 0.000691 +7 2 1 1 1 1 P3 total 0.008255 0.000361 +12 2 2 1 1 1 P0 total 0.089633 0.002592 +13 2 2 1 1 1 P1 total 0.030008 0.000847 +14 2 2 1 1 1 P2 total 0.015748 0.001284 +15 2 2 1 1 1 P3 total 0.008951 0.000387 mesh 1 group in group out nuclide mean std. dev. x y z -0 1 1 1 1 1 total 1.000362 0.044694 -2 1 2 1 1 1 total 1.000346 0.059372 -1 2 1 1 1 1 total 1.000000 0.055277 -3 2 2 1 1 1 total 1.001132 0.057130 +0 1 1 1 1 1 total 1.000736 0.060260 +2 1 2 1 1 1 total 1.000346 0.042656 +1 2 1 1 1 1 total 1.001091 0.052736 +3 2 2 1 1 1 total 1.001078 0.038212 mesh 1 group in group out nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.031634 0.002236 -2 1 2 1 1 1 total 0.032561 0.002344 -1 2 1 1 1 1 total 0.030820 0.002579 -3 2 2 1 1 1 total 0.029308 0.002507 +0 1 1 1 1 1 total 0.031890 0.002523 +2 1 2 1 1 1 total 0.032714 0.001502 +1 2 1 1 1 1 total 0.030414 0.002369 +3 2 2 1 1 1 total 0.031051 0.001521 mesh 1 group in group out nuclide mean std. dev. x y z -0 1 1 1 1 1 total 1.0 0.044796 -2 1 2 1 1 1 total 1.0 0.059579 -1 2 1 1 1 1 total 1.0 0.055277 -3 2 2 1 1 1 total 1.0 0.056598 +0 1 1 1 1 1 total 1.0 0.060234 +2 1 2 1 1 1 total 1.0 0.042523 +1 2 1 1 1 1 total 1.0 0.052777 +3 2 2 1 1 1 total 1.0 0.037842 mesh 1 group in group out legendre nuclide mean std. dev. x y z -0 1 1 1 1 1 P0 total 0.089450 0.005766 -1 1 1 1 1 1 P1 total 0.029092 0.002277 -2 1 1 1 1 1 P2 total 0.016516 0.001119 -3 1 1 1 1 1 P3 total 0.009967 0.000861 -8 1 2 1 1 1 P0 total 0.092674 0.008583 -9 1 2 1 1 1 P1 total 0.028585 0.002630 -10 1 2 1 1 1 P2 total 0.015745 0.002226 -11 1 2 1 1 1 P3 total 0.008496 0.001015 -4 2 1 1 1 1 P0 total 0.088389 0.006412 -5 2 1 1 1 1 P1 total 0.029924 0.002479 -6 2 1 1 1 1 P2 total 0.016754 0.001133 -7 2 1 1 1 1 P3 total 0.009139 0.000699 -12 2 2 1 1 1 P0 total 0.088779 0.006278 -13 2 2 1 1 1 P1 total 0.029804 0.002360 -14 2 2 1 1 1 P2 total 0.016470 0.001510 -15 2 2 1 1 1 P3 total 0.009776 0.000691 +0 1 1 1 1 1 P0 total 0.090065 0.006899 +1 1 1 1 1 1 P1 total 0.030595 0.002243 +2 1 1 1 1 1 P2 total 0.016480 0.001229 +3 1 1 1 1 1 P3 total 0.010157 0.000977 +8 1 2 1 1 1 P0 total 0.090629 0.005616 +9 1 2 1 1 1 P1 total 0.027865 0.001820 +10 1 2 1 1 1 P2 total 0.016804 0.001044 +11 1 2 1 1 1 P3 total 0.009373 0.000813 +4 2 1 1 1 1 P0 total 0.090100 0.005647 +5 2 1 1 1 1 P1 total 0.029359 0.002172 +6 2 1 1 1 1 P2 total 0.015944 0.000984 +7 2 1 1 1 1 P3 total 0.008410 0.000523 +12 2 2 1 1 1 P0 total 0.089607 0.004415 +13 2 2 1 1 1 P1 total 0.029988 0.001459 +14 2 2 1 1 1 P2 total 0.015755 0.001411 +15 2 2 1 1 1 P3 total 0.008951 0.000528 mesh 1 group in group out legendre nuclide mean std. dev. x y z -0 1 1 1 1 1 P0 total 0.089483 0.007018 -1 1 1 1 1 1 P1 total 0.029103 0.002623 -2 1 1 1 1 1 P2 total 0.016522 0.001341 -3 1 1 1 1 1 P3 total 0.009971 0.000970 -8 1 2 1 1 1 P0 total 0.092706 0.010197 -9 1 2 1 1 1 P1 total 0.028595 0.003131 -10 1 2 1 1 1 P2 total 0.015750 0.002415 -11 1 2 1 1 1 P3 total 0.008499 0.001134 -4 2 1 1 1 1 P0 total 0.088389 0.008061 -5 2 1 1 1 1 P1 total 0.029924 0.002980 -6 2 1 1 1 1 P2 total 0.016754 0.001463 -7 2 1 1 1 1 P3 total 0.009139 0.000863 -12 2 2 1 1 1 P0 total 0.088880 0.008076 -13 2 2 1 1 1 P1 total 0.029838 0.002912 -14 2 2 1 1 1 P2 total 0.016489 0.001781 -15 2 2 1 1 1 P3 total 0.009787 0.000889 +0 1 1 1 1 1 P0 total 0.090131 0.008782 +1 1 1 1 1 1 P1 total 0.030617 0.002905 +2 1 1 1 1 1 P2 total 0.016492 0.001581 +3 1 1 1 1 1 P3 total 0.010164 0.001154 +8 1 2 1 1 1 P0 total 0.090661 0.006820 +9 1 2 1 1 1 P1 total 0.027875 0.002174 +10 1 2 1 1 1 P2 total 0.016810 0.001267 +11 1 2 1 1 1 P3 total 0.009376 0.000906 +4 2 1 1 1 1 P0 total 0.090199 0.007385 +5 2 1 1 1 1 P1 total 0.029391 0.002669 +6 2 1 1 1 1 P2 total 0.015962 0.001295 +7 2 1 1 1 1 P3 total 0.008419 0.000686 +12 2 2 1 1 1 P0 total 0.089704 0.005591 +13 2 2 1 1 1 P1 total 0.030020 0.001856 +14 2 2 1 1 1 P2 total 0.015772 0.001536 +15 2 2 1 1 1 P3 total 0.008961 0.000629 mesh 1 group out nuclide mean std. dev. x y z -0 1 1 1 1 total 1.0 0.088672 -2 1 2 1 1 total 1.0 0.069731 -1 2 1 1 1 total 1.0 0.109718 -3 2 2 1 1 total 1.0 0.108376 +0 1 1 1 1 total 1.0 0.098093 +2 1 2 1 1 total 1.0 0.042346 +1 2 1 1 1 total 1.0 0.104352 +3 2 2 1 1 total 1.0 0.067889 mesh 1 group out nuclide mean std. dev. x y z -0 1 1 1 1 total 1.0 0.091154 -2 1 2 1 1 total 1.0 0.069438 -1 2 1 1 1 total 1.0 0.109233 -3 2 2 1 1 total 1.0 0.108119 +0 1 1 1 1 total 1.0 0.099401 +2 1 2 1 1 total 1.0 0.042085 +1 2 1 1 1 total 1.0 0.104135 +3 2 2 1 1 total 1.0 0.067307 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 8.424136e-10 3.612697e-11 -2 1 2 1 1 total 8.884166e-10 6.324091e-11 -1 2 1 1 1 total 8.415613e-10 4.520088e-11 -3 2 2 1 1 total 8.557929e-10 2.898037e-11 +0 1 1 1 1 total 8.547713e-10 3.477664e-11 +2 1 2 1 1 total 9.057083e-10 4.171858e-11 +1 2 1 1 1 total 8.666731e-10 2.371072e-11 +3 2 2 1 1 total 8.532016e-10 1.638929e-11 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 0.030724 0.001773 -2 1 2 1 1 total 0.032290 0.002188 -1 2 1 1 1 total 0.030172 0.001654 -3 2 2 1 1 total 0.030372 0.001661 +0 1 1 1 1 total 0.031163 0.001724 +2 1 2 1 1 total 0.030895 0.001664 +1 2 1 1 1 total 0.030973 0.001409 +3 2 2 1 1 total 0.031058 0.001358 mesh 1 group in group out nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.031468 0.002273 -2 1 2 1 1 1 total 0.032418 0.002330 -1 2 1 1 1 1 total 0.030706 0.002559 -3 2 2 1 1 1 total 0.029134 0.002487 +0 1 1 1 1 1 total 0.031781 0.002541 +2 1 2 1 1 1 total 0.032490 0.001487 +1 2 1 1 1 1 total 0.030274 0.002354 +3 2 2 1 1 1 total 0.030882 0.001500 mesh 1 group in nuclide mean std. dev. x y surf -3 1 1 x-max in 1 total 0.1884 0.010255 -2 1 1 x-max out 1 total 0.1798 0.009646 +3 1 1 x-max in 1 total 0.1888 0.008218 +2 1 1 x-max out 1 total 0.1828 0.008212 1 1 1 x-min in 1 total 0.0000 0.000000 0 1 1 x-min out 1 total 0.0000 0.000000 -7 1 1 y-max in 1 total 0.1822 0.014739 -6 1 1 y-max out 1 total 0.1806 0.019423 +7 1 1 y-max in 1 total 0.1820 0.012534 +6 1 1 y-max out 1 total 0.1794 0.015302 5 1 1 y-min in 1 total 0.0000 0.000000 4 1 1 y-min out 1 total 0.0000 0.000000 -19 1 2 x-max in 1 total 0.1780 0.012514 -18 1 2 x-max out 1 total 0.1886 0.014979 +19 1 2 x-max in 1 total 0.1870 0.011696 +18 1 2 x-max out 1 total 0.1850 0.012919 17 1 2 x-min in 1 total 0.0000 0.000000 16 1 2 x-min out 1 total 0.0000 0.000000 23 1 2 y-max in 1 total 0.0000 0.000000 22 1 2 y-max out 1 total 0.0000 0.000000 -21 1 2 y-min in 1 total 0.1806 0.019423 -20 1 2 y-min out 1 total 0.1822 0.014739 +21 1 2 y-min in 1 total 0.1794 0.015302 +20 1 2 y-min out 1 total 0.1820 0.012534 11 2 1 x-max in 1 total 0.0000 0.000000 10 2 1 x-max out 1 total 0.0000 0.000000 -9 2 1 x-min in 1 total 0.1798 0.009646 -8 2 1 x-min out 1 total 0.1884 0.010255 -15 2 1 y-max in 1 total 0.1812 0.009583 -14 2 1 y-max out 1 total 0.1858 0.012018 +9 2 1 x-min in 1 total 0.1828 0.008212 +8 2 1 x-min out 1 total 0.1888 0.008218 +15 2 1 y-max in 1 total 0.1850 0.011256 +14 2 1 y-max out 1 total 0.1870 0.009597 13 2 1 y-min in 1 total 0.0000 0.000000 12 2 1 y-min out 1 total 0.0000 0.000000 27 2 2 x-max in 1 total 0.0000 0.000000 26 2 2 x-max out 1 total 0.0000 0.000000 -25 2 2 x-min in 1 total 0.1886 0.014979 -24 2 2 x-min out 1 total 0.1780 0.012514 +25 2 2 x-min in 1 total 0.1850 0.012919 +24 2 2 x-min out 1 total 0.1870 0.011696 31 2 2 y-max in 1 total 0.0000 0.000000 30 2 2 y-max out 1 total 0.0000 0.000000 -29 2 2 y-min in 1 total 0.1858 0.012018 -28 2 2 y-min out 1 total 0.1812 0.009583 +29 2 2 y-min in 1 total 0.1870 0.009597 +28 2 2 y-min out 1 total 0.1850 0.011256 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 4.539911 0.323493 -2 1 2 1 1 total 4.278655 0.425575 -1 2 1 1 1 total 4.674097 0.339600 -3 2 2 1 1 total 4.630700 0.312366 +0 1 1 1 1 total 4.581283 0.329623 +2 1 2 1 1 total 4.452968 0.295762 +1 2 1 1 1 total 4.469295 0.239674 +3 2 2 1 1 total 4.570894 0.218416 mesh 1 group in nuclide mean std. dev. x y z -0 1 1 1 1 total 4.538654 0.323497 -2 1 2 1 1 total 4.278494 0.425550 -1 2 1 1 1 total 4.674097 0.339600 -3 2 2 1 1 total 4.634259 0.313464 +0 1 1 1 1 total 4.580746 0.329583 +2 1 2 1 1 total 4.452519 0.295716 +1 2 1 1 1 total 4.468066 0.239680 +3 2 2 1 1 total 4.573657 0.219069 mesh 1 delayedgroup group in nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.000007 3.997262e-07 -1 1 1 1 2 1 total 0.000035 2.063264e-06 -2 1 1 1 3 1 total 0.000034 1.969771e-06 -3 1 1 1 4 1 total 0.000075 4.416388e-06 -4 1 1 1 5 1 total 0.000031 1.810657e-06 -5 1 1 1 6 1 total 0.000013 7.584779e-07 -12 1 2 1 1 1 total 0.000007 4.931656e-07 -13 1 2 1 2 1 total 0.000037 2.545569e-06 -14 1 2 1 3 1 total 0.000035 2.430221e-06 -15 1 2 1 4 1 total 0.000079 5.448757e-06 -16 1 2 1 5 1 total 0.000032 2.233913e-06 -17 1 2 1 6 1 total 0.000014 9.357785e-07 -6 2 1 1 1 1 total 0.000007 3.618632e-07 -7 2 1 1 2 1 total 0.000035 1.867826e-06 -8 2 1 1 3 1 total 0.000033 1.783189e-06 -9 2 1 1 4 1 total 0.000074 3.998058e-06 -10 2 1 1 5 1 total 0.000030 1.639147e-06 -11 2 1 1 6 1 total 0.000013 6.866331e-07 -18 2 2 1 1 1 total 0.000007 3.603080e-07 -19 2 2 1 2 1 total 0.000035 1.859799e-06 -20 2 2 1 3 1 total 0.000033 1.775526e-06 -21 2 2 1 4 1 total 0.000075 3.980875e-06 -22 2 2 1 5 1 total 0.000031 1.632103e-06 -23 2 2 1 6 1 total 0.000013 6.836821e-07 +0 1 1 1 1 1 total 0.000007 3.812309e-07 +1 1 1 1 2 1 total 0.000036 1.967797e-06 +2 1 1 1 3 1 total 0.000034 1.878630e-06 +3 1 1 1 4 1 total 0.000077 4.212043e-06 +4 1 1 1 5 1 total 0.000031 1.726878e-06 +5 1 1 1 6 1 total 0.000013 7.233832e-07 +12 1 2 1 1 1 total 0.000007 3.663985e-07 +13 1 2 1 2 1 total 0.000035 1.891236e-06 +14 1 2 1 3 1 total 0.000034 1.805539e-06 +15 1 2 1 4 1 total 0.000076 4.048166e-06 +16 1 2 1 5 1 total 0.000031 1.659691e-06 +17 1 2 1 6 1 total 0.000013 6.952388e-07 +6 2 1 1 1 1 total 0.000007 3.123173e-07 +7 2 1 1 2 1 total 0.000035 1.612086e-06 +8 2 1 1 3 1 total 0.000034 1.539037e-06 +9 2 1 1 4 1 total 0.000076 3.450649e-06 +10 2 1 1 5 1 total 0.000031 1.414717e-06 +11 2 1 1 6 1 total 0.000013 5.926201e-07 +18 2 2 1 1 1 total 0.000007 2.946716e-07 +19 2 2 1 2 1 total 0.000036 1.521004e-06 +20 2 2 1 3 1 total 0.000034 1.452083e-06 +21 2 2 1 4 1 total 0.000076 3.255689e-06 +22 2 2 1 5 1 total 0.000031 1.334787e-06 +23 2 2 1 6 1 total 0.000013 5.591374e-07 mesh 1 delayedgroup group out nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.0 0.000000 -1 1 1 1 2 1 total 1.0 0.866877 -2 1 1 1 3 1 total 1.0 0.866877 -3 1 1 1 4 1 total 1.0 1.414214 -4 1 1 1 5 1 total 1.0 1.414214 +0 1 1 1 1 1 total 1.0 1.414214 +1 1 1 1 2 1 total 0.0 0.000000 +2 1 1 1 3 1 total 0.0 0.000000 +3 1 1 1 4 1 total 1.0 0.578922 +4 1 1 1 5 1 total 0.0 0.000000 5 1 1 1 6 1 total 0.0 0.000000 12 1 2 1 1 1 total 0.0 0.000000 -13 1 2 1 2 1 total 0.0 0.000000 -14 1 2 1 3 1 total 0.0 0.000000 -15 1 2 1 4 1 total 1.0 0.579346 -16 1 2 1 5 1 total 1.0 1.414214 +13 1 2 1 2 1 total 1.0 0.578922 +14 1 2 1 3 1 total 1.0 1.414214 +15 1 2 1 4 1 total 1.0 1.414214 +16 1 2 1 5 1 total 1.0 0.875472 17 1 2 1 6 1 total 1.0 1.414214 -6 2 1 1 1 1 total 1.0 1.414214 -7 2 1 1 2 1 total 1.0 1.414214 -8 2 1 1 3 1 total 1.0 0.874781 -9 2 1 1 4 1 total 0.0 0.000000 -10 2 1 1 5 1 total 0.0 0.000000 +6 2 1 1 1 1 total 0.0 0.000000 +7 2 1 1 2 1 total 0.0 0.000000 +8 2 1 1 3 1 total 1.0 1.414214 +9 2 1 1 4 1 total 1.0 0.579392 +10 2 1 1 5 1 total 1.0 1.414214 11 2 1 1 6 1 total 0.0 0.000000 -18 2 2 1 1 1 total 1.0 1.414214 -19 2 2 1 2 1 total 1.0 0.867902 -20 2 2 1 3 1 total 1.0 1.414214 -21 2 2 1 4 1 total 1.0 1.414214 +18 2 2 1 1 1 total 1.0 0.868163 +19 2 2 1 2 1 total 1.0 1.414214 +20 2 2 1 3 1 total 0.0 0.000000 +21 2 2 1 4 1 total 1.0 0.868969 22 2 2 1 5 1 total 1.0 1.414214 23 2 2 1 6 1 total 0.0 0.000000 mesh 1 delayedgroup group in nuclide mean std. dev. x y z -0 1 1 1 1 1 total 0.000221 0.000016 -1 1 1 1 2 1 total 0.001138 0.000084 -2 1 1 1 3 1 total 0.001087 0.000080 -3 1 1 1 4 1 total 0.002437 0.000180 -4 1 1 1 5 1 total 0.000999 0.000074 -5 1 1 1 6 1 total 0.000418 0.000031 -12 1 2 1 1 1 total 0.000221 0.000014 -13 1 2 1 2 1 total 0.001138 0.000073 -14 1 2 1 3 1 total 0.001087 0.000069 -15 1 2 1 4 1 total 0.002436 0.000155 -16 1 2 1 5 1 total 0.000999 0.000064 -17 1 2 1 6 1 total 0.000418 0.000027 -6 2 1 1 1 1 total 0.000220 0.000014 -7 2 1 1 2 1 total 0.001137 0.000070 -8 2 1 1 3 1 total 0.001086 0.000067 -9 2 1 1 4 1 total 0.002435 0.000150 -10 2 1 1 5 1 total 0.000998 0.000062 -11 2 1 1 6 1 total 0.000418 0.000026 -18 2 2 1 1 1 total 0.000221 0.000015 -19 2 2 1 2 1 total 0.001141 0.000078 -20 2 2 1 3 1 total 0.001089 0.000074 -21 2 2 1 4 1 total 0.002442 0.000167 -22 2 2 1 5 1 total 0.001001 0.000068 -23 2 2 1 6 1 total 0.000419 0.000029 +0 1 1 1 1 1 total 0.000221 0.000015 +1 1 1 1 2 1 total 0.001140 0.000079 +2 1 1 1 3 1 total 0.001088 0.000075 +3 1 1 1 4 1 total 0.002440 0.000169 +4 1 1 1 5 1 total 0.001001 0.000069 +5 1 1 1 6 1 total 0.000419 0.000029 +12 1 2 1 1 1 total 0.000221 0.000013 +13 1 2 1 2 1 total 0.001139 0.000066 +14 1 2 1 3 1 total 0.001088 0.000063 +15 1 2 1 4 1 total 0.002439 0.000142 +16 1 2 1 5 1 total 0.001000 0.000058 +17 1 2 1 6 1 total 0.000419 0.000024 +6 2 1 1 1 1 total 0.000220 0.000013 +7 2 1 1 2 1 total 0.001138 0.000067 +8 2 1 1 3 1 total 0.001086 0.000064 +9 2 1 1 4 1 total 0.002435 0.000144 +10 2 1 1 5 1 total 0.000998 0.000059 +11 2 1 1 6 1 total 0.000418 0.000025 +18 2 2 1 1 1 total 0.000221 0.000013 +19 2 2 1 2 1 total 0.001141 0.000066 +20 2 2 1 3 1 total 0.001090 0.000063 +21 2 2 1 4 1 total 0.002443 0.000141 +22 2 2 1 5 1 total 0.001002 0.000058 +23 2 2 1 6 1 total 0.000420 0.000024 mesh 1 delayedgroup nuclide mean std. dev. x y z -0 1 1 1 1 total 0.013336 0.000997 -1 1 1 1 2 total 0.032739 0.002447 -2 1 1 1 3 total 0.120780 0.009028 -3 1 1 1 4 total 0.302780 0.022633 -4 1 1 1 5 total 0.849490 0.063500 -5 1 1 1 6 total 2.853000 0.213262 -12 1 2 1 1 total 0.013336 0.000866 -13 1 2 1 2 total 0.032739 0.002126 -14 1 2 1 3 total 0.120780 0.007843 -15 1 2 1 4 total 0.302780 0.019661 -16 1 2 1 5 total 0.849490 0.055163 -17 1 2 1 6 total 2.853000 0.185263 -6 2 1 1 1 total 0.013336 0.000814 -7 2 1 1 2 total 0.032739 0.001999 -8 2 1 1 3 total 0.120780 0.007373 -9 2 1 1 4 total 0.302780 0.018483 -10 2 1 1 5 total 0.849490 0.051857 -11 2 1 1 6 total 2.853000 0.174163 -18 2 2 1 1 total 0.013336 0.000896 -19 2 2 1 2 total 0.032739 0.002200 -20 2 2 1 3 total 0.120780 0.008117 -21 2 2 1 4 total 0.302780 0.020349 -22 2 2 1 5 total 0.849490 0.057091 -23 2 2 1 6 total 2.853000 0.191738 +0 1 1 1 1 total 0.013336 0.000919 +1 1 1 1 2 total 0.032739 0.002257 +2 1 1 1 3 total 0.120780 0.008325 +3 1 1 1 4 total 0.302780 0.020871 +4 1 1 1 5 total 0.849490 0.058555 +5 1 1 1 6 total 2.853000 0.196656 +12 1 2 1 1 total 0.013336 0.000770 +13 1 2 1 2 total 0.032739 0.001891 +14 1 2 1 3 total 0.120780 0.006977 +15 1 2 1 4 total 0.302780 0.017490 +16 1 2 1 5 total 0.849490 0.049071 +17 1 2 1 6 total 2.853000 0.164804 +6 2 1 1 1 total 0.013336 0.000790 +7 2 1 1 2 total 0.032739 0.001940 +8 2 1 1 3 total 0.120780 0.007157 +9 2 1 1 4 total 0.302780 0.017942 +10 2 1 1 5 total 0.849490 0.050338 +11 2 1 1 6 total 2.853000 0.169061 +18 2 2 1 1 total 0.013336 0.000757 +19 2 2 1 2 total 0.032739 0.001858 +20 2 2 1 3 total 0.120780 0.006855 +21 2 2 1 4 total 0.302780 0.017186 +22 2 2 1 5 total 0.849490 0.048217 +23 2 2 1 6 total 2.853000 0.161935 mesh 1 delayedgroup group in group out nuclide mean std. dev. x y z -0 1 1 1 1 1 1 total 0.000000 0.000000 -1 1 1 1 2 1 1 total 0.000056 0.000034 -2 1 1 1 3 1 1 total 0.000056 0.000034 -3 1 1 1 4 1 1 total 0.000029 0.000029 -4 1 1 1 5 1 1 total 0.000026 0.000026 +0 1 1 1 1 1 1 total 0.000026 0.000026 +1 1 1 1 2 1 1 total 0.000000 0.000000 +2 1 1 1 3 1 1 total 0.000000 0.000000 +3 1 1 1 4 1 1 total 0.000083 0.000034 +4 1 1 1 5 1 1 total 0.000000 0.000000 5 1 1 1 6 1 1 total 0.000000 0.000000 12 1 2 1 1 1 1 total 0.000000 0.000000 -13 1 2 1 2 1 1 total 0.000000 0.000000 -14 1 2 1 3 1 1 total 0.000000 0.000000 -15 1 2 1 4 1 1 total 0.000079 0.000033 -16 1 2 1 5 1 1 total 0.000032 0.000032 -17 1 2 1 6 1 1 total 0.000032 0.000032 -6 2 1 1 1 1 1 total 0.000029 0.000029 -7 2 1 1 2 1 1 total 0.000027 0.000027 -8 2 1 1 3 1 1 total 0.000058 0.000036 -9 2 1 1 4 1 1 total 0.000000 0.000000 -10 2 1 1 5 1 1 total 0.000000 0.000000 +13 1 2 1 2 1 1 total 0.000081 0.000033 +14 1 2 1 3 1 1 total 0.000026 0.000026 +15 1 2 1 4 1 1 total 0.000026 0.000026 +16 1 2 1 5 1 1 total 0.000059 0.000036 +17 1 2 1 6 1 1 total 0.000033 0.000033 +6 2 1 1 1 1 1 total 0.000000 0.000000 +7 2 1 1 2 1 1 total 0.000000 0.000000 +8 2 1 1 3 1 1 total 0.000032 0.000032 +9 2 1 1 4 1 1 total 0.000080 0.000033 +10 2 1 1 5 1 1 total 0.000028 0.000028 11 2 1 1 6 1 1 total 0.000000 0.000000 -18 2 2 1 1 1 1 total 0.000027 0.000027 -19 2 2 1 2 1 1 total 0.000056 0.000035 -20 2 2 1 3 1 1 total 0.000028 0.000028 -21 2 2 1 4 1 1 total 0.000030 0.000030 -22 2 2 1 5 1 1 total 0.000033 0.000033 +18 2 2 1 1 1 1 total 0.000054 0.000033 +19 2 2 1 2 1 1 total 0.000029 0.000029 +20 2 2 1 3 1 1 total 0.000000 0.000000 +21 2 2 1 4 1 1 total 0.000054 0.000033 +22 2 2 1 5 1 1 total 0.000032 0.000032 23 2 2 1 6 1 1 total 0.000000 0.000000 diff --git a/tests/regression_tests/mgxs_library_mesh/test.py b/tests/regression_tests/mgxs_library_mesh/test.py index 89c68a75a3..c1a5980b5d 100644 --- a/tests/regression_tests/mgxs_library_mesh/test.py +++ b/tests/regression_tests/mgxs_library_mesh/test.py @@ -57,7 +57,7 @@ def model(): model.mgxs_lib.build_library() # Add tallies - model.mgxs_lib.add_to_tallies_file(model.tallies, merge=False) + model.mgxs_lib.add_to_tallies(model.tallies, merge=False) return model diff --git a/tests/regression_tests/mgxs_library_no_nuclides/results_true.dat b/tests/regression_tests/mgxs_library_no_nuclides/results_true.dat index c0dba7c0fb..aec8e8bbc1 100644 --- a/tests/regression_tests/mgxs_library_no_nuclides/results_true.dat +++ b/tests/regression_tests/mgxs_library_no_nuclides/results_true.dat @@ -1,227 +1,227 @@ total material group in nuclide mean std. dev. -1 1 1 total 0.413814 0.018434 -0 1 2 total 0.663001 0.012535 +1 1 1 total 0.422772 0.014069 +0 1 2 total 0.661309 0.049458 transport material group in nuclide mean std. dev. -1 1 1 total 0.369730 0.019494 -0 1 2 total 0.643777 0.018246 +1 1 1 total 0.383831 0.015331 +0 1 2 total 0.679181 0.050786 nu-transport material group in nuclide mean std. dev. -1 1 1 total 0.369730 0.019494 -0 1 2 total 0.643777 0.018246 +1 1 1 total 0.383831 0.015331 +0 1 2 total 0.679181 0.050786 absorption material group in nuclide mean std. dev. -1 1 1 total 0.026013 0.001851 -0 1 2 total 0.267233 0.007475 +1 1 1 total 0.027181 0.001539 +0 1 2 total 0.265559 0.020699 reduced absorption material group in nuclide mean std. dev. -1 1 1 total 0.025932 0.001850 -0 1 2 total 0.267233 0.007475 +1 1 1 total 0.027162 0.001538 +0 1 2 total 0.265559 0.020699 capture material group in nuclide mean std. dev. -1 1 1 total 0.018869 0.001758 -0 1 2 total 0.072358 0.008204 +1 1 1 total 0.019717 0.001492 +0 1 2 total 0.072029 0.019378 fission material group in nuclide mean std. dev. -1 1 1 total 0.007144 0.000317 -0 1 2 total 0.194875 0.005528 +1 1 1 total 0.007464 0.000222 +0 1 2 total 0.193530 0.015119 nu-fission material group in nuclide mean std. dev. -1 1 1 total 0.018243 0.000827 -0 1 2 total 0.474851 0.013471 +1 1 1 total 0.018925 0.000543 +0 1 2 total 0.471574 0.036840 kappa-fission material group in nuclide mean std. dev. -1 1 1 total 1.391782e+06 6.192598e+04 -0 1 2 total 3.768981e+07 1.069211e+06 +1 1 1 total 1.453014e+06 4.287190e+04 +0 1 2 total 3.742974e+07 2.924022e+06 scatter material group in nuclide mean std. dev. -1 1 1 total 0.387802 0.017462 -0 1 2 total 0.395768 0.007541 +1 1 1 total 0.395591 0.013417 +0 1 2 total 0.395750 0.029309 nu-scatter material group in nuclide mean std. dev. -1 1 1 total 0.387032 0.024325 -0 1 2 total 0.407651 0.016266 +1 1 1 total 0.392941 0.019689 +0 1 2 total 0.396262 0.027471 scatter matrix material group in group out legendre nuclide mean std. dev. -12 1 1 1 P0 total 0.386336 0.024297 -13 1 1 1 P1 total 0.044084 0.006343 -14 1 1 1 P2 total 0.027336 0.006403 -15 1 1 1 P3 total 0.011672 0.004897 -8 1 1 2 P0 total 0.000695 0.000327 -9 1 1 2 P1 total -0.000359 0.000201 -10 1 1 2 P2 total -0.000047 0.000081 -11 1 1 2 P3 total 0.000239 0.000099 +12 1 1 1 P0 total 0.392419 0.019837 +13 1 1 1 P1 total 0.038941 0.006089 +14 1 1 1 P2 total 0.019512 0.003548 +15 1 1 1 P3 total 0.012951 0.002399 +8 1 1 2 P0 total 0.000522 0.000349 +9 1 1 2 P1 total -0.000301 0.000185 +10 1 1 2 P2 total 0.000045 0.000147 +11 1 1 2 P3 total 0.000069 0.000162 4 1 2 1 P0 total 0.000000 0.000000 5 1 2 1 P1 total 0.000000 0.000000 6 1 2 1 P2 total 0.000000 0.000000 7 1 2 1 P3 total 0.000000 0.000000 -0 1 2 2 P0 total 0.407651 0.016266 -1 1 2 2 P1 total 0.021192 0.013171 -2 1 2 2 P2 total 0.010327 0.017230 -3 1 2 2 P3 total 0.005148 0.013732 +0 1 2 2 P0 total 0.396262 0.027471 +1 1 2 2 P1 total -0.016133 0.010911 +2 1 2 2 P2 total -0.001147 0.010536 +3 1 2 2 P3 total 0.005359 0.008143 nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 1 1 1 P0 total 0.386336 0.024297 -13 1 1 1 P1 total 0.044084 0.006343 -14 1 1 1 P2 total 0.027336 0.006403 -15 1 1 1 P3 total 0.011672 0.004897 -8 1 1 2 P0 total 0.000695 0.000327 -9 1 1 2 P1 total -0.000359 0.000201 -10 1 1 2 P2 total -0.000047 0.000081 -11 1 1 2 P3 total 0.000239 0.000099 +12 1 1 1 P0 total 0.392419 0.019837 +13 1 1 1 P1 total 0.038941 0.006089 +14 1 1 1 P2 total 0.019512 0.003548 +15 1 1 1 P3 total 0.012951 0.002399 +8 1 1 2 P0 total 0.000522 0.000349 +9 1 1 2 P1 total -0.000301 0.000185 +10 1 1 2 P2 total 0.000045 0.000147 +11 1 1 2 P3 total 0.000069 0.000162 4 1 2 1 P0 total 0.000000 0.000000 5 1 2 1 P1 total 0.000000 0.000000 6 1 2 1 P2 total 0.000000 0.000000 7 1 2 1 P3 total 0.000000 0.000000 -0 1 2 2 P0 total 0.407651 0.016266 -1 1 2 2 P1 total 0.021192 0.013171 -2 1 2 2 P2 total 0.010327 0.017230 -3 1 2 2 P3 total 0.005148 0.013732 +0 1 2 2 P0 total 0.396262 0.027471 +1 1 2 2 P1 total -0.016133 0.010911 +2 1 2 2 P2 total -0.001147 0.010536 +3 1 2 2 P3 total 0.005359 0.008143 multiplicity matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 1.0 0.064268 -2 1 1 2 total 1.0 0.661438 +3 1 1 1 total 1.0 0.054620 +2 1 1 2 total 1.0 0.942809 1 1 2 1 total 0.0 0.000000 -0 1 2 2 total 1.0 0.050545 +0 1 2 2 total 1.0 0.080341 nu-fission matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 0.024633 0.002205 +3 1 1 1 total 0.019257 0.001831 2 1 1 2 total 0.000000 0.000000 -1 1 2 1 total 0.435159 0.014743 +1 1 2 1 total 0.459401 0.022054 0 1 2 2 total 0.000000 0.000000 scatter probability matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 0.998203 0.064101 -2 1 1 2 total 0.001797 0.000844 +3 1 1 1 total 0.998671 0.054518 +2 1 1 2 total 0.001329 0.000888 1 1 2 1 total 0.000000 0.000000 -0 1 2 2 total 1.000000 0.050545 +0 1 2 2 total 1.000000 0.080341 consistent scatter matrix material group in group out legendre nuclide mean std. dev. -12 1 1 1 P0 total 0.387105 0.030361 -13 1 1 1 P1 total 0.044172 0.006684 -14 1 1 1 P2 total 0.027391 0.006543 -15 1 1 1 P3 total 0.011695 0.004937 -8 1 1 2 P0 total 0.000697 0.000329 -9 1 1 2 P1 total -0.000360 0.000202 -10 1 1 2 P2 total -0.000047 0.000082 -11 1 1 2 P3 total 0.000239 0.000100 +12 1 1 1 P0 total 0.395065 0.025390 +13 1 1 1 P1 total 0.039204 0.006325 +14 1 1 1 P2 total 0.019644 0.003656 +15 1 1 1 P3 total 0.013039 0.002470 +8 1 1 2 P0 total 0.000526 0.000352 +9 1 1 2 P1 total -0.000303 0.000186 +10 1 1 2 P2 total 0.000045 0.000148 +11 1 1 2 P3 total 0.000069 0.000163 4 1 2 1 P0 total 0.000000 0.000000 5 1 2 1 P1 total 0.000000 0.000000 6 1 2 1 P2 total 0.000000 0.000000 7 1 2 1 P3 total 0.000000 0.000000 -0 1 2 2 P0 total 0.395768 0.021378 -1 1 2 2 P1 total 0.020575 0.012809 -2 1 2 2 P2 total 0.010026 0.016732 -3 1 2 2 P3 total 0.004998 0.013333 +0 1 2 2 P0 total 0.395750 0.043243 +1 1 2 2 P1 total -0.016112 0.010982 +2 1 2 2 P2 total -0.001146 0.010523 +3 1 2 2 P3 total 0.005353 0.008145 consistent nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 1 1 1 P0 total 0.387105 0.039252 -13 1 1 1 P1 total 0.044172 0.007262 -14 1 1 1 P2 total 0.027391 0.006776 -15 1 1 1 P3 total 0.011695 0.004994 -8 1 1 2 P0 total 0.000697 0.000566 -9 1 1 2 P1 total -0.000360 0.000313 -10 1 1 2 P2 total -0.000047 0.000087 -11 1 1 2 P3 total 0.000239 0.000187 +12 1 1 1 P0 total 0.395065 0.033321 +13 1 1 1 P1 total 0.039204 0.006677 +14 1 1 1 P2 total 0.019644 0.003810 +15 1 1 1 P3 total 0.013039 0.002571 +8 1 1 2 P0 total 0.000526 0.000608 +9 1 1 2 P1 total -0.000303 0.000341 +10 1 1 2 P2 total 0.000045 0.000154 +11 1 1 2 P3 total 0.000069 0.000175 4 1 2 1 P0 total 0.000000 0.000000 5 1 2 1 P1 total 0.000000 0.000000 6 1 2 1 P2 total 0.000000 0.000000 7 1 2 1 P3 total 0.000000 0.000000 -0 1 2 2 P0 total 0.395768 0.029278 -1 1 2 2 P1 total 0.020575 0.012851 -2 1 2 2 P2 total 0.010026 0.016739 -3 1 2 2 P3 total 0.004998 0.013335 +0 1 2 2 P0 total 0.395750 0.053673 +1 1 2 2 P1 total -0.016112 0.011058 +2 1 2 2 P2 total -0.001146 0.010523 +3 1 2 2 P3 total 0.005353 0.008157 chi material group out nuclide mean std. dev. -1 1 1 total 1.0 0.039887 +1 1 1 total 1.0 0.015644 0 1 2 total 0.0 0.000000 chi-prompt material group out nuclide mean std. dev. -1 1 1 total 1.0 0.039887 +1 1 1 total 1.0 0.017529 0 1 2 total 0.0 0.000000 inverse-velocity material group in nuclide mean std. dev. -1 1 1 total 5.956290e-08 2.255751e-09 -0 1 2 total 2.886630e-06 7.418452e-08 +1 1 1 total 6.047675e-08 4.367288e-09 +0 1 2 total 2.861927e-06 2.241423e-07 prompt-nu-fission material group in nuclide mean std. dev. -1 1 1 total 0.018067 0.000817 -0 1 2 total 0.471762 0.013383 +1 1 1 total 0.018748 0.00054 +0 1 2 total 0.468507 0.03660 prompt-nu-fission matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 0.024633 0.002205 +3 1 1 1 total 0.019049 0.001675 2 1 1 2 total 0.000000 0.000000 -1 1 2 1 total 0.435159 0.014743 +1 1 2 1 total 0.454399 0.022578 0 1 2 2 total 0.000000 0.000000 diffusion-coefficient material group in nuclide mean std. dev. -1 1 1 total 0.901559 0.047536 -0 1 2 total 0.517778 0.014675 +1 1 1 total 0.868438 0.034686 +0 1 2 total 0.490787 0.036698 nu-diffusion-coefficient material group in nuclide mean std. dev. -1 1 1 total 0.901559 0.047536 -0 1 2 total 0.517778 0.014675 +1 1 1 total 0.868438 0.034686 +0 1 2 total 0.490787 0.036698 (n,elastic) material group in nuclide mean std. dev. -1 1 1 total 0.360179 0.016169 -0 1 2 total 0.395768 0.007541 +1 1 1 total 0.368341 0.013033 +0 1 2 total 0.395750 0.029309 (n,level) material group in nuclide mean std. dev. -1 1 1 total 0.000568 0.000028 +1 1 1 total 0.000518 0.000016 0 1 2 total 0.000000 0.000000 (n,2n) material group in nuclide mean std. dev. -1 1 1 total 0.000079 0.000042 +1 1 1 total 0.000019 0.000012 0 1 2 total 0.000000 0.000000 (n,na) - material group in nuclide mean std. dev. -1 1 1 total 8.510945e-07 8.515320e-07 -0 1 2 total 0.000000e+00 0.000000e+00 + material group in nuclide mean std. dev. +1 1 1 total 0.0 0.0 +0 1 2 total 0.0 0.0 (n,nc) material group in nuclide mean std. dev. -1 1 1 total 0.008258 0.000928 +1 1 1 total 0.007599 0.000559 0 1 2 total 0.000000 0.000000 (n,gamma) material group in nuclide mean std. dev. -1 1 1 total 0.018749 0.001838 -0 1 2 total 0.072358 0.001951 +1 1 1 total 0.019608 0.001470 +0 1 2 total 0.072029 0.005584 (n,a) material group in nuclide mean std. dev. -1 1 1 total 0.000119 0.000023 -0 1 2 total 0.000000 0.000000 +1 1 1 total 0.000109 0.00002 +0 1 2 total 0.000000 0.00000 (n,Xa) - material group in nuclide mean std. dev. -1 1 1 total 0.00012 0.000022 -0 1 2 total 0.00000 0.000000 + material group in nuclide mean std. dev. +1 1 1 total 0.000109 0.00002 +0 1 2 total 0.000000 0.00000 heating - material group in nuclide mean std. dev. -1 1 1 total 1.216089e+06 54827.397330 -0 1 2 total 3.262993e+07 904277.817101 + material group in nuclide mean std. dev. +1 1 1 total 1.270644e+06 3.732629e+04 +0 1 2 total 3.241569e+07 2.530346e+06 damage-energy material group in nuclide mean std. dev. -1 1 1 total 2317.176742 165.734097 -0 1 2 total 1371.933922 38.919660 +1 1 1 total 2405.735342 79.042000 +0 1 2 total 1362.470597 106.435803 (n,n1) material group in nuclide mean std. dev. -1 1 1 total 0.012055 0.000759 +1 1 1 total 0.011931 0.000455 0 1 2 total 0.000000 0.000000 (n,a0) material group in nuclide mean std. dev. -1 1 1 total 0.000109 0.000028 -0 1 2 total 0.000000 0.000000 +1 1 1 total 0.000108 0.00002 +0 1 2 total 0.000000 0.00000 (n,nc) matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 0.009563 0.001002 +3 1 1 1 total 0.005745 0.001068 2 1 1 2 total 0.000000 0.000000 1 1 2 1 total 0.000000 0.000000 0 1 2 2 total 0.000000 0.000000 (n,n1) matrix material group in group out nuclide mean std. dev. -3 1 1 1 total 0.013909 0.00145 -2 1 1 2 total 0.000000 0.00000 -1 1 2 1 total 0.000000 0.00000 -0 1 2 2 total 0.000000 0.00000 +3 1 1 1 total 0.013232 0.001025 +2 1 1 2 total 0.000000 0.000000 +1 1 2 1 total 0.000000 0.000000 +0 1 2 2 total 0.000000 0.000000 (n,2n) matrix material group in group out nuclide mean std. dev. 3 1 1 1 total 0.0 0.0 @@ -230,104 +230,104 @@ damage-energy 0 1 2 2 total 0.0 0.0 delayed-nu-fission material delayedgroup group in nuclide mean std. dev. -1 1 1 1 total 0.000004 1.857100e-07 -3 1 2 1 total 0.000025 1.293123e-06 -5 1 3 1 total 0.000026 1.448812e-06 -7 1 4 1 total 0.000068 4.132525e-06 -9 1 5 1 total 0.000037 2.670208e-06 -11 1 6 1 total 0.000015 1.084541e-06 -0 1 1 2 total 0.000108 3.067510e-06 -2 1 2 2 total 0.000558 1.583355e-05 -4 1 3 2 total 0.000533 1.511609e-05 -6 1 4 2 total 0.001195 3.389154e-05 -8 1 5 2 total 0.000490 1.389508e-05 -10 1 6 2 total 0.000205 5.820598e-06 +1 1 1 1 total 0.000004 1.226367e-07 +3 1 2 1 total 0.000026 6.725093e-07 +5 1 3 1 total 0.000027 7.028316e-07 +7 1 4 1 total 0.000068 1.919534e-06 +9 1 5 1 total 0.000037 1.268939e-06 +11 1 6 1 total 0.000015 5.136452e-07 +0 1 1 2 total 0.000107 8.388866e-06 +2 1 2 2 total 0.000554 4.330076e-05 +4 1 3 2 total 0.000529 4.133869e-05 +6 1 4 2 total 0.001186 9.268481e-05 +8 1 5 2 total 0.000486 3.799954e-05 +10 1 6 2 total 0.000204 1.591787e-05 chi-delayed material delayedgroup group out nuclide mean std. dev. -1 1 1 1 total 0.0 0.0 -3 1 2 1 total 0.0 0.0 -5 1 3 1 total 0.0 0.0 -7 1 4 1 total 0.0 0.0 -9 1 5 1 total 0.0 0.0 -11 1 6 1 total 0.0 0.0 -0 1 1 2 total 0.0 0.0 -2 1 2 2 total 0.0 0.0 -4 1 3 2 total 0.0 0.0 -6 1 4 2 total 0.0 0.0 -8 1 5 2 total 0.0 0.0 -10 1 6 2 total 0.0 0.0 +1 1 1 1 total 0.0 0.000000 +3 1 2 1 total 0.0 0.000000 +5 1 3 1 total 0.0 0.000000 +7 1 4 1 total 1.0 0.433956 +9 1 5 1 total 0.0 0.000000 +11 1 6 1 total 0.0 0.000000 +0 1 1 2 total 0.0 0.000000 +2 1 2 2 total 0.0 0.000000 +4 1 3 2 total 0.0 0.000000 +6 1 4 2 total 0.0 0.000000 +8 1 5 2 total 0.0 0.000000 +10 1 6 2 total 0.0 0.000000 beta material delayedgroup group in nuclide mean std. dev. -1 1 1 1 total 0.000223 0.000009 -3 1 2 1 total 0.001375 0.000067 -5 1 3 1 total 0.001439 0.000076 -7 1 4 1 total 0.003724 0.000217 -9 1 5 1 total 0.002049 0.000142 -11 1 6 1 total 0.000840 0.000058 -0 1 1 2 total 0.000228 0.000008 -2 1 2 2 total 0.001175 0.000041 -4 1 3 2 total 0.001122 0.000040 -6 1 4 2 total 0.002516 0.000089 -8 1 5 2 total 0.001031 0.000036 -10 1 6 2 total 0.000432 0.000015 +1 1 1 1 total 0.000225 0.000006 +3 1 2 1 total 0.001359 0.000033 +5 1 3 1 total 0.001412 0.000034 +7 1 4 1 total 0.003611 0.000094 +9 1 5 1 total 0.001950 0.000064 +11 1 6 1 total 0.000801 0.000026 +0 1 1 2 total 0.000228 0.000019 +2 1 2 2 total 0.001175 0.000096 +4 1 3 2 total 0.001122 0.000092 +6 1 4 2 total 0.002516 0.000206 +8 1 5 2 total 0.001031 0.000085 +10 1 6 2 total 0.000432 0.000035 decay-rate material delayedgroup nuclide mean std. dev. -0 1 1 total 0.013353 0.000379 -1 1 2 total 0.032612 0.001002 -2 1 3 total 0.121056 0.003938 -3 1 4 total 0.305642 0.010892 -4 1 5 total 0.860947 0.036893 -5 1 6 total 2.891708 0.122310 +0 1 1 total 0.013352 0.000905 +1 1 2 total 0.032619 0.002094 +2 1 3 total 0.121041 0.007464 +3 1 4 total 0.305491 0.017639 +4 1 5 total 0.860388 0.042833 +5 1 6 total 2.889807 0.145503 delayed-nu-fission matrix - material delayedgroup group in group out nuclide mean std. dev. -3 1 1 1 1 total 0.0 0.0 -7 1 2 1 1 total 0.0 0.0 -11 1 3 1 1 total 0.0 0.0 -15 1 4 1 1 total 0.0 0.0 -19 1 5 1 1 total 0.0 0.0 -23 1 6 1 1 total 0.0 0.0 -2 1 1 1 2 total 0.0 0.0 -6 1 2 1 2 total 0.0 0.0 -10 1 3 1 2 total 0.0 0.0 -14 1 4 1 2 total 0.0 0.0 -18 1 5 1 2 total 0.0 0.0 -22 1 6 1 2 total 0.0 0.0 -1 1 1 2 1 total 0.0 0.0 -5 1 2 2 1 total 0.0 0.0 -9 1 3 2 1 total 0.0 0.0 -13 1 4 2 1 total 0.0 0.0 -17 1 5 2 1 total 0.0 0.0 -21 1 6 2 1 total 0.0 0.0 -0 1 1 2 2 total 0.0 0.0 -4 1 2 2 2 total 0.0 0.0 -8 1 3 2 2 total 0.0 0.0 -12 1 4 2 2 total 0.0 0.0 -16 1 5 2 2 total 0.0 0.0 -20 1 6 2 2 total 0.0 0.0 + material delayedgroup group in group out nuclide mean std. dev. +3 1 1 1 1 total 0.000000 0.000000 +7 1 2 1 1 total 0.000000 0.000000 +11 1 3 1 1 total 0.000000 0.000000 +15 1 4 1 1 total 0.000207 0.000207 +19 1 5 1 1 total 0.000000 0.000000 +23 1 6 1 1 total 0.000000 0.000000 +2 1 1 1 2 total 0.000000 0.000000 +6 1 2 1 2 total 0.000000 0.000000 +10 1 3 1 2 total 0.000000 0.000000 +14 1 4 1 2 total 0.000000 0.000000 +18 1 5 1 2 total 0.000000 0.000000 +22 1 6 1 2 total 0.000000 0.000000 +1 1 1 2 1 total 0.000000 0.000000 +5 1 2 2 1 total 0.000000 0.000000 +9 1 3 2 1 total 0.000000 0.000000 +13 1 4 2 1 total 0.005002 0.001278 +17 1 5 2 1 total 0.000000 0.000000 +21 1 6 2 1 total 0.000000 0.000000 +0 1 1 2 2 total 0.000000 0.000000 +4 1 2 2 2 total 0.000000 0.000000 +8 1 3 2 2 total 0.000000 0.000000 +12 1 4 2 2 total 0.000000 0.000000 +16 1 5 2 2 total 0.000000 0.000000 +20 1 6 2 2 total 0.000000 0.000000 total material group in nuclide mean std. dev. -1 2 1 total 0.313574 0.016009 -0 2 2 total 0.300858 0.005911 +1 2 1 total 0.320478 0.012201 +0 2 2 total 0.300681 0.029685 transport material group in nuclide mean std. dev. -1 2 1 total 0.266154 0.017348 -0 2 2 total 0.300597 0.011062 +1 2 1 total 0.267653 0.015887 +0 2 2 total 0.327250 0.035614 nu-transport material group in nuclide mean std. dev. -1 2 1 total 0.266154 0.017348 -0 2 2 total 0.300597 0.011062 +1 2 1 total 0.267653 0.015887 +0 2 2 total 0.327250 0.035614 absorption - material group in nuclide mean std. dev. -1 2 1 total 0.00150 0.000118 -0 2 2 total 0.00542 0.000201 + material group in nuclide mean std. dev. +1 2 1 total 0.001040 0.000121 +0 2 2 total 0.005284 0.000548 reduced absorption material group in nuclide mean std. dev. -1 2 1 total 0.001481 0.000119 -0 2 2 total 0.005420 0.000201 +1 2 1 total 0.001040 0.000121 +0 2 2 total 0.005284 0.000548 capture - material group in nuclide mean std. dev. -1 2 1 total 0.00150 0.000118 -0 2 2 total 0.00542 0.000201 + material group in nuclide mean std. dev. +1 2 1 total 0.001040 0.000121 +0 2 2 total 0.005284 0.000548 fission material group in nuclide mean std. dev. 1 2 1 total 0.0 0.0 @@ -342,18 +342,18 @@ kappa-fission 0 2 2 total 0.0 0.0 scatter material group in nuclide mean std. dev. -1 2 1 total 0.312074 0.015934 -0 2 2 total 0.295438 0.005743 +1 2 1 total 0.319438 0.012181 +0 2 2 total 0.295397 0.029142 nu-scatter material group in nuclide mean std. dev. -1 2 1 total 0.318594 0.023203 -0 2 2 total 0.295662 0.031486 +1 2 1 total 0.314727 0.014272 +0 2 2 total 0.295807 0.038170 scatter matrix material group in group out legendre nuclide mean std. dev. -12 2 1 1 P0 total 0.318594 0.023203 -13 2 1 1 P1 total 0.047420 0.006684 -14 2 1 1 P2 total 0.029426 0.008048 -15 2 1 1 P3 total 0.007335 0.004092 +12 2 1 1 P0 total 0.314727 0.014272 +13 2 1 1 P1 total 0.052826 0.010175 +14 2 1 1 P2 total 0.033176 0.002264 +15 2 1 1 P3 total 0.006129 0.004317 8 2 1 2 P0 total 0.000000 0.000000 9 2 1 2 P1 total 0.000000 0.000000 10 2 1 2 P2 total 0.000000 0.000000 @@ -362,16 +362,16 @@ scatter matrix 5 2 2 1 P1 total 0.000000 0.000000 6 2 2 1 P2 total 0.000000 0.000000 7 2 2 1 P3 total 0.000000 0.000000 -0 2 2 2 P0 total 0.295662 0.031486 -1 2 2 2 P1 total 0.000261 0.009350 -2 2 2 2 P2 total -0.004912 0.007866 -3 2 2 2 P3 total -0.018278 0.012339 +0 2 2 2 P0 total 0.295807 0.038170 +1 2 2 2 P1 total -0.026569 0.019676 +2 2 2 2 P2 total -0.005395 0.007578 +3 2 2 2 P3 total -0.005680 0.012737 nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 2 1 1 P0 total 0.318594 0.023203 -13 2 1 1 P1 total 0.047420 0.006684 -14 2 1 1 P2 total 0.029426 0.008048 -15 2 1 1 P3 total 0.007335 0.004092 +12 2 1 1 P0 total 0.314727 0.014272 +13 2 1 1 P1 total 0.052826 0.010175 +14 2 1 1 P2 total 0.033176 0.002264 +15 2 1 1 P3 total 0.006129 0.004317 8 2 1 2 P0 total 0.000000 0.000000 9 2 1 2 P1 total 0.000000 0.000000 10 2 1 2 P2 total 0.000000 0.000000 @@ -380,16 +380,16 @@ nu-scatter matrix 5 2 2 1 P1 total 0.000000 0.000000 6 2 2 1 P2 total 0.000000 0.000000 7 2 2 1 P3 total 0.000000 0.000000 -0 2 2 2 P0 total 0.295662 0.031486 -1 2 2 2 P1 total 0.000261 0.009350 -2 2 2 2 P2 total -0.004912 0.007866 -3 2 2 2 P3 total -0.018278 0.012339 +0 2 2 2 P0 total 0.295807 0.038170 +1 2 2 2 P1 total -0.026569 0.019676 +2 2 2 2 P2 total -0.005395 0.007578 +3 2 2 2 P3 total -0.005680 0.012737 multiplicity matrix material group in group out nuclide mean std. dev. -3 2 1 1 total 1.0 0.071770 +3 2 1 1 total 1.0 0.043852 2 2 1 2 total 0.0 0.000000 1 2 2 1 total 0.0 0.000000 -0 2 2 2 total 1.0 0.103652 +0 2 2 2 total 1.0 0.139361 nu-fission matrix material group in group out nuclide mean std. dev. 3 2 1 1 total 0.0 0.0 @@ -398,16 +398,16 @@ nu-fission matrix 0 2 2 2 total 0.0 0.0 scatter probability matrix material group in group out nuclide mean std. dev. -3 2 1 1 total 1.0 0.071770 +3 2 1 1 total 1.0 0.043852 2 2 1 2 total 0.0 0.000000 1 2 2 1 total 0.0 0.000000 -0 2 2 2 total 1.0 0.103652 +0 2 2 2 total 1.0 0.139361 consistent scatter matrix material group in group out legendre nuclide mean std. dev. -12 2 1 1 P0 total 0.312074 0.027487 -13 2 1 1 P1 total 0.046450 0.006939 -14 2 1 1 P2 total 0.028824 0.008012 -15 2 1 1 P3 total 0.007185 0.004024 +12 2 1 1 P0 total 0.319438 0.018563 +13 2 1 1 P1 total 0.053616 0.010510 +14 2 1 1 P2 total 0.033673 0.002604 +15 2 1 1 P3 total 0.006221 0.004387 8 2 1 2 P0 total 0.000000 0.000000 9 2 1 2 P1 total 0.000000 0.000000 10 2 1 2 P2 total 0.000000 0.000000 @@ -416,16 +416,16 @@ consistent scatter matrix 5 2 2 1 P1 total 0.000000 0.000000 6 2 2 1 P2 total 0.000000 0.000000 7 2 2 1 P3 total 0.000000 0.000000 -0 2 2 2 P0 total 0.295438 0.031157 -1 2 2 2 P1 total 0.000261 0.009343 -2 2 2 2 P2 total -0.004909 0.007859 -3 2 2 2 P3 total -0.018264 0.012327 +0 2 2 2 P0 total 0.295397 0.050438 +1 2 2 2 P1 total -0.026532 0.019872 +2 2 2 2 P2 total -0.005388 0.007591 +3 2 2 2 P3 total -0.005672 0.012735 consistent nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 2 1 1 P0 total 0.312074 0.035456 -13 2 1 1 P1 total 0.046450 0.007699 -14 2 1 1 P2 total 0.028824 0.008274 -15 2 1 1 P3 total 0.007185 0.004057 +12 2 1 1 P0 total 0.319438 0.023255 +13 2 1 1 P1 total 0.053616 0.010769 +14 2 1 1 P2 total 0.033673 0.002993 +15 2 1 1 P3 total 0.006221 0.004396 8 2 1 2 P0 total 0.000000 0.000000 9 2 1 2 P1 total 0.000000 0.000000 10 2 1 2 P2 total 0.000000 0.000000 @@ -434,10 +434,10 @@ consistent nu-scatter matrix 5 2 2 1 P1 total 0.000000 0.000000 6 2 2 1 P2 total 0.000000 0.000000 7 2 2 1 P3 total 0.000000 0.000000 -0 2 2 2 P0 total 0.295438 0.043686 -1 2 2 2 P1 total 0.000261 0.009343 -2 2 2 2 P2 total -0.004909 0.007876 -3 2 2 2 P3 total -0.018264 0.012471 +0 2 2 2 P0 total 0.295397 0.065105 +1 2 2 2 P1 total -0.026532 0.020213 +2 2 2 2 P2 total -0.005388 0.007628 +3 2 2 2 P3 total -0.005672 0.012759 chi material group out nuclide mean std. dev. 1 2 1 total 0.0 0.0 @@ -448,8 +448,8 @@ chi-prompt 0 2 2 total 0.0 0.0 inverse-velocity material group in nuclide mean std. dev. -1 2 1 total 6.076563e-08 2.727519e-09 -0 2 2 total 2.996176e-06 1.110139e-07 +1 2 1 total 6.068670e-08 4.861582e-09 +0 2 2 total 2.921021e-06 3.028269e-07 prompt-nu-fission material group in nuclide mean std. dev. 1 2 1 total 0.0 0.0 @@ -462,72 +462,72 @@ prompt-nu-fission matrix 0 2 2 2 total 0.0 0.0 diffusion-coefficient material group in nuclide mean std. dev. -1 2 1 total 1.252406 0.081631 -0 2 2 total 1.108904 0.040809 +1 2 1 total 1.245396 0.073923 +0 2 2 total 1.018589 0.110853 nu-diffusion-coefficient material group in nuclide mean std. dev. -1 2 1 total 1.252406 0.081631 -0 2 2 total 1.108904 0.040809 +1 2 1 total 1.245396 0.073923 +0 2 2 total 1.018589 0.110853 (n,elastic) material group in nuclide mean std. dev. -1 2 1 total 0.302664 0.015531 -0 2 2 total 0.295438 0.005743 +1 2 1 total 0.310592 0.012188 +0 2 2 total 0.295397 0.029142 (n,level) material group in nuclide mean std. dev. 1 2 1 total 0.0 0.0 0 2 2 total 0.0 0.0 (n,2n) - material group in nuclide mean std. dev. -1 2 1 total 0.000019 0.000017 -0 2 2 total 0.000000 0.000000 + material group in nuclide mean std. dev. +1 2 1 total 0.0 0.0 +0 2 2 total 0.0 0.0 (n,na) material group in nuclide mean std. dev. -1 2 1 total 4.892570e-09 4.436228e-09 +1 2 1 total 2.157338e-13 1.864239e-13 0 2 2 total 0.000000e+00 0.000000e+00 (n,nc) - material group in nuclide mean std. dev. -1 2 1 total 0.001998 0.000408 -0 2 2 total 0.000000 0.000000 + material group in nuclide mean std. dev. +1 2 1 total 0.00187 0.000152 +0 2 2 total 0.00000 0.000000 (n,gamma) material group in nuclide mean std. dev. -1 2 1 total 0.001497 0.000118 -0 2 2 total 0.005419 0.000201 +1 2 1 total 0.001038 0.000121 +0 2 2 total 0.005283 0.000548 (n,a) material group in nuclide mean std. dev. -1 2 1 total 9.546292e-07 9.180854e-08 -0 2 2 total 2.736059e-07 5.318732e-09 +1 2 1 total 7.402079e-07 3.197538e-08 +0 2 2 total 2.735682e-07 2.698845e-08 (n,Xa) material group in nuclide mean std. dev. -1 2 1 total 9.595218e-07 9.558005e-08 -0 2 2 total 2.736059e-07 5.318732e-09 +1 2 1 total 7.402081e-07 3.197534e-08 +0 2 2 total 2.735682e-07 2.698845e-08 heating material group in nuclide mean std. dev. -1 2 1 total 2551.878627 212.765665 -0 2 2 total 2.332139 0.087384 +1 2 1 total 2479.710231 157.161879 +0 2 2 total 2.314706 0.265682 damage-energy - material group in nuclide mean std. dev. -1 2 1 total 1585.677533 130.382718 -0 2 2 total 0.295108 0.010079 + material group in nuclide mean std. dev. +1 2 1 total 1566.139383 61.602407 +0 2 2 total 0.288739 0.029698 (n,n1) material group in nuclide mean std. dev. -1 2 1 total 0.002835 0.000246 +1 2 1 total 0.002897 0.000181 0 2 2 total 0.000000 0.000000 (n,a0) material group in nuclide mean std. dev. -1 2 1 total 7.169006e-07 6.251188e-08 -0 2 2 total 2.733303e-07 5.313375e-09 +1 2 1 total 6.646569e-07 2.959064e-08 +0 2 2 total 2.732927e-07 2.696126e-08 (n,nc) matrix material group in group out nuclide mean std. dev. -3 2 1 1 total 0.001489 0.001491 +3 2 1 1 total 0.000488 0.000488 2 2 1 2 total 0.000000 0.000000 1 2 2 1 total 0.000000 0.000000 0 2 2 2 total 0.000000 0.000000 (n,n1) matrix - material group in group out nuclide mean std. dev. -3 2 1 1 total 0.001985 0.000507 -2 2 1 2 total 0.000000 0.000000 -1 2 2 1 total 0.000000 0.000000 -0 2 2 2 total 0.000000 0.000000 + material group in group out nuclide mean std. dev. +3 2 1 1 total 0.00244 0.001094 +2 2 1 2 total 0.00000 0.000000 +1 2 2 1 total 0.00000 0.000000 +0 2 2 2 total 0.00000 0.000000 (n,2n) matrix material group in group out nuclide mean std. dev. 3 2 1 1 total 0.0 0.0 @@ -612,28 +612,28 @@ delayed-nu-fission matrix 20 2 6 2 2 total 0.0 0.0 total material group in nuclide mean std. dev. -1 3 1 total 0.682896 0.024140 -0 3 2 total 2.032938 0.085675 +1 3 1 total 0.692034 0.019973 +0 3 2 total 2.033425 0.189463 transport material group in nuclide mean std. dev. -1 3 1 total 0.298986 0.026905 -0 3 2 total 1.471887 0.096907 +1 3 1 total 0.298754 0.021602 +0 3 2 total 1.459465 0.197868 nu-transport material group in nuclide mean std. dev. -1 3 1 total 0.298986 0.026905 -0 3 2 total 1.471887 0.096907 +1 3 1 total 0.298754 0.021602 +0 3 2 total 1.459465 0.197868 absorption material group in nuclide mean std. dev. -1 3 1 total 0.000693 0.000020 -0 3 2 total 0.031171 0.001403 +1 3 1 total 0.000699 0.000035 +0 3 2 total 0.031056 0.003017 reduced absorption material group in nuclide mean std. dev. -1 3 1 total 0.000693 0.000020 -0 3 2 total 0.031171 0.001403 +1 3 1 total 0.000699 0.000035 +0 3 2 total 0.031056 0.003017 capture material group in nuclide mean std. dev. -1 3 1 total 0.000693 0.000020 -0 3 2 total 0.031171 0.001403 +1 3 1 total 0.000699 0.000035 +0 3 2 total 0.031056 0.003017 fission material group in nuclide mean std. dev. 1 3 1 total 0.0 0.0 @@ -648,54 +648,54 @@ kappa-fission 0 3 2 total 0.0 0.0 scatter material group in nuclide mean std. dev. -1 3 1 total 0.682202 0.024123 -0 3 2 total 2.001768 0.084281 +1 3 1 total 0.691336 0.019945 +0 3 2 total 2.002368 0.186454 nu-scatter material group in nuclide mean std. dev. -1 3 1 total 0.672567 0.017434 -0 3 2 total 2.004576 0.129211 +1 3 1 total 0.684356 0.011639 +0 3 2 total 1.990840 0.178205 scatter matrix material group in group out legendre nuclide mean std. dev. -12 3 1 1 P0 total 0.641741 0.016600 -13 3 1 1 P1 total 0.383841 0.011878 -14 3 1 1 P2 total 0.149909 0.005512 -15 3 1 1 P3 total 0.004238 0.002485 -8 3 1 2 P0 total 0.030826 0.000973 -9 3 1 2 P1 total 0.009943 0.000415 -10 3 1 2 P2 total -0.003002 0.000628 -11 3 1 2 P3 total -0.004234 0.000393 -4 3 2 1 P0 total 0.000467 0.000467 -5 3 2 1 P1 total 0.000345 0.000345 -6 3 2 1 P2 total 0.000149 0.000149 -7 3 2 1 P3 total -0.000047 0.000047 -0 3 2 2 P0 total 2.004109 0.129225 -1 3 2 2 P1 total 0.511363 0.043448 -2 3 2 2 P2 total 0.108599 0.014070 -3 3 2 2 P3 total 0.035733 0.021921 +12 3 1 1 P0 total 0.652706 0.011111 +13 3 1 1 P1 total 0.393203 0.008164 +14 3 1 1 P2 total 0.162146 0.003332 +15 3 1 1 P3 total 0.014967 0.004773 +8 3 1 2 P0 total 0.031650 0.000613 +9 3 1 2 P1 total 0.009845 0.000647 +10 3 1 2 P2 total -0.003284 0.000758 +11 3 1 2 P3 total -0.003971 0.000187 +4 3 2 1 P0 total 0.000474 0.000475 +5 3 2 1 P1 total 0.000396 0.000397 +6 3 2 1 P2 total 0.000260 0.000261 +7 3 2 1 P3 total 0.000099 0.000099 +0 3 2 2 P0 total 1.990366 0.178042 +1 3 2 2 P1 total 0.523546 0.053239 +2 3 2 2 P2 total 0.101180 0.015832 +3 3 2 2 P3 total 0.017873 0.005685 nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 3 1 1 P0 total 0.641741 0.016600 -13 3 1 1 P1 total 0.383841 0.011878 -14 3 1 1 P2 total 0.149909 0.005512 -15 3 1 1 P3 total 0.004238 0.002485 -8 3 1 2 P0 total 0.030826 0.000973 -9 3 1 2 P1 total 0.009943 0.000415 -10 3 1 2 P2 total -0.003002 0.000628 -11 3 1 2 P3 total -0.004234 0.000393 -4 3 2 1 P0 total 0.000467 0.000467 -5 3 2 1 P1 total 0.000345 0.000345 -6 3 2 1 P2 total 0.000149 0.000149 -7 3 2 1 P3 total -0.000047 0.000047 -0 3 2 2 P0 total 2.004109 0.129225 -1 3 2 2 P1 total 0.511363 0.043448 -2 3 2 2 P2 total 0.108599 0.014070 -3 3 2 2 P3 total 0.035733 0.021921 +12 3 1 1 P0 total 0.652706 0.011111 +13 3 1 1 P1 total 0.393203 0.008164 +14 3 1 1 P2 total 0.162146 0.003332 +15 3 1 1 P3 total 0.014967 0.004773 +8 3 1 2 P0 total 0.031650 0.000613 +9 3 1 2 P1 total 0.009845 0.000647 +10 3 1 2 P2 total -0.003284 0.000758 +11 3 1 2 P3 total -0.003971 0.000187 +4 3 2 1 P0 total 0.000474 0.000475 +5 3 2 1 P1 total 0.000396 0.000397 +6 3 2 1 P2 total 0.000260 0.000261 +7 3 2 1 P3 total 0.000099 0.000099 +0 3 2 2 P0 total 1.990366 0.178042 +1 3 2 2 P1 total 0.523546 0.053239 +2 3 2 2 P2 total 0.101180 0.015832 +3 3 2 2 P3 total 0.017873 0.005685 multiplicity matrix material group in group out nuclide mean std. dev. -3 3 1 1 total 1.0 0.022200 -2 3 1 2 total 1.0 0.033880 +3 3 1 1 total 1.0 0.020267 +2 3 1 2 total 1.0 0.024112 1 3 2 1 total 1.0 1.414214 -0 3 2 2 total 1.0 0.066922 +0 3 2 2 total 1.0 0.093189 nu-fission matrix material group in group out nuclide mean std. dev. 3 3 1 1 total 0.0 0.0 @@ -704,46 +704,46 @@ nu-fission matrix 0 3 2 2 total 0.0 0.0 scatter probability matrix material group in group out nuclide mean std. dev. -3 3 1 1 total 0.954167 0.020729 -2 3 1 2 total 0.045833 0.001296 -1 3 2 1 total 0.000233 0.000233 -0 3 2 2 total 0.999767 0.066899 +3 3 1 1 total 0.953753 0.018903 +2 3 1 2 total 0.046247 0.001011 +1 3 2 1 total 0.000238 0.000239 +0 3 2 2 total 0.999762 0.093156 consistent scatter matrix material group in group out legendre nuclide mean std. dev. -12 3 1 1 P0 total 0.650935 0.027014 -13 3 1 1 P1 total 0.389340 0.017459 -14 3 1 1 P2 total 0.152056 0.007457 -15 3 1 1 P3 total 0.004299 0.002525 -8 3 1 2 P0 total 0.031268 0.001416 -9 3 1 2 P1 total 0.010085 0.000533 -10 3 1 2 P2 total -0.003045 0.000645 -11 3 1 2 P3 total -0.004295 0.000423 -4 3 2 1 P0 total 0.000466 0.000467 -5 3 2 1 P1 total 0.000344 0.000345 -6 3 2 1 P2 total 0.000148 0.000149 -7 3 2 1 P3 total -0.000047 0.000047 -0 3 2 2 P0 total 2.001301 0.158219 -1 3 2 2 P1 total 0.510647 0.049275 -2 3 2 2 P2 total 0.108446 0.014900 -3 3 2 2 P3 total 0.035683 0.021951 +12 3 1 1 P0 total 0.659363 0.023079 +13 3 1 1 P1 total 0.397213 0.014683 +14 3 1 1 P2 total 0.163800 0.006035 +15 3 1 1 P3 total 0.015120 0.004843 +8 3 1 2 P0 total 0.031973 0.001157 +9 3 1 2 P1 total 0.009945 0.000721 +10 3 1 2 P2 total -0.003318 0.000772 +11 3 1 2 P3 total -0.004011 0.000225 +4 3 2 1 P0 total 0.000477 0.000480 +5 3 2 1 P1 total 0.000399 0.000401 +6 3 2 1 P2 total 0.000262 0.000264 +7 3 2 1 P3 total 0.000099 0.000100 +0 3 2 2 P0 total 2.001892 0.263710 +1 3 2 2 P1 total 0.526577 0.073894 +2 3 2 2 P2 total 0.101766 0.018719 +3 3 2 2 P3 total 0.017976 0.005976 consistent nu-scatter matrix material group in group out legendre nuclide mean std. dev. -12 3 1 1 P0 total 0.650935 0.030637 -13 3 1 1 P1 total 0.389340 0.019481 -14 3 1 1 P2 total 0.152056 0.008185 -15 3 1 1 P3 total 0.004299 0.002526 -8 3 1 2 P0 total 0.031268 0.001768 -9 3 1 2 P1 total 0.010085 0.000633 -10 3 1 2 P2 total -0.003045 0.000653 -11 3 1 2 P3 total -0.004295 0.000447 -4 3 2 1 P0 total 0.000466 0.000808 -5 3 2 1 P1 total 0.000344 0.000597 -6 3 2 1 P2 total 0.000148 0.000257 -7 3 2 1 P3 total -0.000047 0.000081 -0 3 2 2 P0 total 2.001301 0.207294 -1 3 2 2 P1 total 0.510647 0.059966 -2 3 2 2 P2 total 0.108446 0.016574 -3 3 2 2 P3 total 0.035683 0.022080 +12 3 1 1 P0 total 0.659363 0.026669 +13 3 1 1 P1 total 0.397213 0.016746 +14 3 1 1 P2 total 0.163800 0.006888 +15 3 1 1 P3 total 0.015120 0.004853 +8 3 1 2 P0 total 0.031973 0.001391 +9 3 1 2 P1 total 0.009945 0.000759 +10 3 1 2 P2 total -0.003318 0.000776 +11 3 1 2 P3 total -0.004011 0.000245 +4 3 2 1 P0 total 0.000477 0.000827 +5 3 2 1 P1 total 0.000399 0.000692 +6 3 2 1 P2 total 0.000262 0.000455 +7 3 2 1 P3 total 0.000099 0.000172 +0 3 2 2 P0 total 2.001892 0.323026 +1 3 2 2 P1 total 0.526577 0.088703 +2 3 2 2 P2 total 0.101766 0.020985 +3 3 2 2 P3 total 0.017976 0.006207 chi material group out nuclide mean std. dev. 1 3 1 total 0.0 0.0 @@ -754,8 +754,8 @@ chi-prompt 0 3 2 total 0.0 0.0 inverse-velocity material group in nuclide mean std. dev. -1 3 1 total 6.023693e-08 1.678511e-09 -0 3 2 total 2.995346e-06 1.347817e-07 +1 3 1 total 6.187551e-08 3.945367e-09 +0 3 2 total 2.984343e-06 2.898715e-07 prompt-nu-fission material group in nuclide mean std. dev. 1 3 1 total 0.0 0.0 @@ -768,60 +768,60 @@ prompt-nu-fission matrix 0 3 2 2 total 0.0 0.0 diffusion-coefficient material group in nuclide mean std. dev. -1 3 1 total 1.114881 0.100326 -0 3 2 total 0.226467 0.014910 +1 3 1 total 1.115746 0.080676 +0 3 2 total 0.228394 0.030965 nu-diffusion-coefficient material group in nuclide mean std. dev. -1 3 1 total 1.114881 0.100326 -0 3 2 total 0.226467 0.014910 +1 3 1 total 1.115746 0.080676 +0 3 2 total 0.228394 0.030965 (n,elastic) material group in nuclide mean std. dev. -1 3 1 total 0.682168 0.024125 -0 3 2 total 2.001768 0.084281 +1 3 1 total 0.691333 0.019945 +0 3 2 total 2.002368 0.186454 (n,level) material group in nuclide mean std. dev. -1 3 1 total 0.000033 0.000019 +1 3 1 total 0.000003 0.000002 0 3 2 total 0.000000 0.000000 (n,2n) material group in nuclide mean std. dev. 1 3 1 total 0.0 0.0 0 3 2 total 0.0 0.0 (n,na) - material group in nuclide mean std. dev. -1 3 1 total 9.967562e-07 9.970492e-07 -0 3 2 total 0.000000e+00 0.000000e+00 + material group in nuclide mean std. dev. +1 3 1 total 0.0 0.0 +0 3 2 total 0.0 0.0 (n,nc) - material group in nuclide mean std. dev. -1 3 1 total 8.867935e-07 8.870902e-07 -0 3 2 total 0.000000e+00 0.000000e+00 + material group in nuclide mean std. dev. +1 3 1 total 0.0 0.0 +0 3 2 total 0.0 0.0 (n,gamma) material group in nuclide mean std. dev. -1 3 1 total 0.000219 0.000006 -0 3 2 total 0.010855 0.000488 +1 3 1 total 0.000225 0.000014 +0 3 2 total 0.010815 0.001050 (n,a) material group in nuclide mean std. dev. -1 3 1 total 0.000474 0.000015 -0 3 2 total 0.020316 0.000914 +1 3 1 total 0.000474 0.000021 +0 3 2 total 0.020241 0.001966 (n,Xa) material group in nuclide mean std. dev. -1 3 1 total 0.000475 0.000015 -0 3 2 total 0.020316 0.000914 +1 3 1 total 0.000474 0.000021 +0 3 2 total 0.020242 0.001966 heating material group in nuclide mean std. dev. -1 3 1 total 77986.174023 6103.108384 -0 3 2 total 59060.658662 3576.641806 +1 3 1 total 74978.139095 3970.725596 +0 3 2 total 58539.697122 6443.645451 damage-energy material group in nuclide mean std. dev. -1 3 1 total 1107.847239 59.901669 -0 3 2 total 331.691439 14.926212 +1 3 1 total 1161.596397 41.187452 +0 3 2 total 330.473159 32.100259 (n,n1) - material group in nuclide mean std. dev. -1 3 1 total 0.000001 3.988839e-07 -0 3 2 total 0.000000 0.000000e+00 + material group in nuclide mean std. dev. +1 3 1 total 2.912377e-07 3.897408e-08 +0 3 2 total 0.000000e+00 0.000000e+00 (n,a0) material group in nuclide mean std. dev. -1 3 1 total 0.000084 0.000016 -0 3 2 total 0.001278 0.000058 +1 3 1 total 0.000082 0.000009 +0 3 2 total 0.001273 0.000124 (n,nc) matrix material group in group out nuclide mean std. dev. 3 3 1 1 total 0.0 0.0 diff --git a/tests/regression_tests/mgxs_library_no_nuclides/test.py b/tests/regression_tests/mgxs_library_no_nuclides/test.py index af14a5dc8f..a02086af3e 100644 --- a/tests/regression_tests/mgxs_library_no_nuclides/test.py +++ b/tests/regression_tests/mgxs_library_no_nuclides/test.py @@ -39,7 +39,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=False): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_nuclides/results_true.dat b/tests/regression_tests/mgxs_library_nuclides/results_true.dat index c2188997d7..c05ec9b48d 100644 --- a/tests/regression_tests/mgxs_library_nuclides/results_true.dat +++ b/tests/regression_tests/mgxs_library_nuclides/results_true.dat @@ -1 +1 @@ -4ae3b5a70ad72b1be261aee3ab19e0261d1c12f4d4ca50b712d1ba76041bd5387c69fa9fa326619ad588db206cd9aaf464b0025d71ea9b8b1137af0102bca87f \ No newline at end of file +d1e4ab2c0d85bb5da617db9c7a3731494114e2fd3ba75ae8eaa1f0a36648f73fcbcfb487390789b0124719cabdcbfa84af4bb118f11bdc548d1065e1b5af836a \ No newline at end of file diff --git a/tests/regression_tests/mgxs_library_nuclides/test.py b/tests/regression_tests/mgxs_library_nuclides/test.py index 8a7673565e..a10070358a 100644 --- a/tests/regression_tests/mgxs_library_nuclides/test.py +++ b/tests/regression_tests/mgxs_library_nuclides/test.py @@ -36,7 +36,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=False) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=False) def _get_results(self, hash_output=True): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/mgxs_library_specific_nuclides/results_true.dat b/tests/regression_tests/mgxs_library_specific_nuclides/results_true.dat index eaf56b9666..0c44eb132c 100644 --- a/tests/regression_tests/mgxs_library_specific_nuclides/results_true.dat +++ b/tests/regression_tests/mgxs_library_specific_nuclides/results_true.dat @@ -1 +1 @@ -08d5c199c51496f86fdd739bf7ee0e143a9a159da0f4d364ec970557e5c1fc92a202d906dcae91812e665fd2e88dd7db1e4913ef6b91f456f23b52093c83f483 \ No newline at end of file +efcd9fd6be2ed6c98bbe5279cbacdb287597fcbbc4ed49e164b07e0861f28877b1bef2ad82d70fdac95965f7ed0d0990f77c8545718836b1b55a16b4243208d0 \ No newline at end of file diff --git a/tests/regression_tests/mgxs_library_specific_nuclides/test.py b/tests/regression_tests/mgxs_library_specific_nuclides/test.py index 61910e539e..0ccbb83bdb 100644 --- a/tests/regression_tests/mgxs_library_specific_nuclides/test.py +++ b/tests/regression_tests/mgxs_library_specific_nuclides/test.py @@ -37,7 +37,7 @@ class MGXSTestHarness(PyAPITestHarness): self.mgxs_lib.build_library() # Add tallies - self.mgxs_lib.add_to_tallies_file(self._model.tallies, merge=True) + self.mgxs_lib.add_to_tallies(self._model.tallies, merge=True) def _get_results(self, hash_output=True): """Digest info in the statepoint and return as a string.""" diff --git a/tests/regression_tests/microxs/test_reference_materials_direct.csv b/tests/regression_tests/microxs/test_reference_materials_direct.csv index 3259d0151a..4a63fed85a 100644 --- a/tests/regression_tests/microxs/test_reference_materials_direct.csv +++ b/tests/regression_tests/microxs/test_reference_materials_direct.csv @@ -1,7 +1,7 @@ nuclides,reactions,groups,xs -U235,"(n,gamma)",1,0.14765501510184456 -U235,fission,1,1.2517200956290817 -O16,"(n,gamma)",1,0.00010872314985710938 +U235,"(n,gamma)",1,0.1475718536187164 +U235,fission,1,1.2504996049257149 +O16,"(n,gamma)",1,0.00010981236259441559 O16,fission,1,0.0 -Xe135,"(n,gamma)",1,0.014333667335215764 +Xe135,"(n,gamma)",1,0.014570546772870611 Xe135,fission,1,0.0 diff --git a/tests/regression_tests/microxs/test_reference_materials_flux.csv b/tests/regression_tests/microxs/test_reference_materials_flux.csv index 5023e0d0e6..5eb29902e4 100644 --- a/tests/regression_tests/microxs/test_reference_materials_flux.csv +++ b/tests/regression_tests/microxs/test_reference_materials_flux.csv @@ -1,7 +1,7 @@ nuclides,reactions,groups,xs -U235,"(n,gamma)",1,0.15018326758942505 -U235,fission,1,1.2603151141390958 -O16,"(n,gamma)",1,0.00012159621938463765 +U235,"(n,gamma)",1,0.15003016703758473 +U235,fission,1,1.2646269005413537 +O16,"(n,gamma)",1,0.00012069778439640301 O16,fission,1,0.0 -Xe135,"(n,gamma)",1,0.015180177095633546 +Xe135,"(n,gamma)",1,0.014820264774863562 Xe135,fission,1,0.0 diff --git a/tests/regression_tests/microxs/test_reference_mesh_direct.csv b/tests/regression_tests/microxs/test_reference_mesh_direct.csv index bd07a3237a..60160ee513 100644 --- a/tests/regression_tests/microxs/test_reference_mesh_direct.csv +++ b/tests/regression_tests/microxs/test_reference_mesh_direct.csv @@ -1,7 +1,7 @@ nuclides,reactions,groups,xs -U235,"(n,gamma)",1,0.14765501510184456 -U235,fission,1,1.2517200956290815 -O16,"(n,gamma)",1,0.00010872314985710936 +U235,"(n,gamma)",1,0.14757185361871633 +U235,fission,1,1.2504996049257142 +O16,"(n,gamma)",1,0.0001098123625944155 O16,fission,1,0.0 -Xe135,"(n,gamma)",1,0.014333667335215761 +Xe135,"(n,gamma)",1,0.0145705467728706 Xe135,fission,1,0.0 diff --git a/tests/regression_tests/microxs/test_reference_mesh_flux.csv b/tests/regression_tests/microxs/test_reference_mesh_flux.csv index d946ada802..5eb29902e4 100644 --- a/tests/regression_tests/microxs/test_reference_mesh_flux.csv +++ b/tests/regression_tests/microxs/test_reference_mesh_flux.csv @@ -1,7 +1,7 @@ nuclides,reactions,groups,xs -U235,"(n,gamma)",1,0.15018326758942507 -U235,fission,1,1.2603151141390958 -O16,"(n,gamma)",1,0.00012159621938463766 +U235,"(n,gamma)",1,0.15003016703758473 +U235,fission,1,1.2646269005413537 +O16,"(n,gamma)",1,0.00012069778439640301 O16,fission,1,0.0 -Xe135,"(n,gamma)",1,0.015180177095633546 +Xe135,"(n,gamma)",1,0.014820264774863562 Xe135,fission,1,0.0 diff --git a/tests/regression_tests/multipole/results_true.dat b/tests/regression_tests/multipole/results_true.dat index 8e82655ce5..40b42b1a05 100644 --- a/tests/regression_tests/multipole/results_true.dat +++ b/tests/regression_tests/multipole/results_true.dat @@ -1,36 +1,36 @@ k-combined: -1.354889E+00 8.437211E-03 +1.315804E+00 7.070811E-02 tally 1: -3.869969E+00 -3.000421E+00 -2.800393E+00 -1.570851E+00 -5.399091E-01 -5.842233E-02 -4.577147E-01 -4.203362E-02 +3.840178E+00 +2.953217E+00 +2.769369E+00 +1.535605E+00 +5.400560E-01 +5.840168E-02 +4.595308E-01 +4.237758E-02 0.000000E+00 0.000000E+00 -2.286465E+01 -1.045869E+02 +2.283789E+01 +1.044032E+02 0.000000E+00 0.000000E+00 -6.971793E-04 -9.724819E-08 -2.283955E+01 -1.043576E+02 -4.659256E-06 -2.170865E-11 -3.663230E+02 -2.685383E+04 -2.800393E+00 -1.570851E+00 -2.204999E+00 -9.728014E-01 -3.612213E+02 -2.611152E+04 -4.659256E-06 -2.170865E-11 +6.960971E-04 +9.704386E-08 +2.281620E+01 +1.042051E+02 +3.667073E-05 +1.048567E-09 +3.655557E+02 +2.676173E+04 +2.769369E+00 +1.535605E+00 +2.199058E+00 +9.681253E-01 +3.604950E+02 +2.602657E+04 +3.667073E-05 +1.048567E-09 Cell ID = 11 Name = @@ -38,5 +38,6 @@ Cell Region = -1 Rotation = None Temperature = [500. 700. 0. 800.] + Density = None Translation = None Volume = None diff --git a/tests/regression_tests/output/results_true.dat b/tests/regression_tests/output/results_true.dat index bbf03de943..97b997ae6b 100644 --- a/tests/regression_tests/output/results_true.dat +++ b/tests/regression_tests/output/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 diff --git a/tests/regression_tests/particle_restart_eigval/results_true.dat b/tests/regression_tests/particle_restart_eigval/results_true.dat index bd81920cae..3feeb5e74b 100644 --- a/tests/regression_tests/particle_restart_eigval/results_true.dat +++ b/tests/regression_tests/particle_restart_eigval/results_true.dat @@ -1,16 +1,16 @@ current batch: -1.100000E+01 +8.000000E+00 current generation: 1.000000E+00 particle id: -2.540000E+02 +6.000000E+01 run mode: eigenvalue particle weight: 1.000000E+00 particle energy: -2.220048E+06 +2.028153E+06 particle xyz: --4.820850E+01 2.432936E+01 4.397668E+01 +-3.678172E+01 -6.073321E+01 2.756488E+01 particle uvw: --3.148565E-01 9.184190E-01 2.395245E-01 +-3.284774E-01 -8.920284E-01 3.104639E-01 diff --git a/tests/regression_tests/particle_restart_eigval/settings.xml b/tests/regression_tests/particle_restart_eigval/settings.xml index 64b1a4dd45..de580e4c48 100644 --- a/tests/regression_tests/particle_restart_eigval/settings.xml +++ b/tests/regression_tests/particle_restart_eigval/settings.xml @@ -6,7 +6,7 @@ 12 5 1200 - + 1000000 -10 -10 -5 10 10 5 diff --git a/tests/regression_tests/particle_restart_eigval/test.py b/tests/regression_tests/particle_restart_eigval/test.py index f9d22edb8a..bad3f158c0 100644 --- a/tests/regression_tests/particle_restart_eigval/test.py +++ b/tests/regression_tests/particle_restart_eigval/test.py @@ -2,5 +2,5 @@ from tests.testing_harness import ParticleRestartTestHarness def test_particle_restart_eigval(): - harness = ParticleRestartTestHarness('particle_11_254.h5') + harness = ParticleRestartTestHarness('particle_8_60.h5') harness.main() diff --git a/tests/regression_tests/periodic/results_true.dat b/tests/regression_tests/periodic/results_true.dat index 2189597e11..626004b16b 100644 --- a/tests/regression_tests/periodic/results_true.dat +++ b/tests/regression_tests/periodic/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.623300E+00 2.572983E-02 +1.624889E+00 1.108153E-02 diff --git a/tests/regression_tests/periodic_6fold/results_true.dat b/tests/regression_tests/periodic_6fold/results_true.dat index e60182809a..04aa308781 100644 --- a/tests/regression_tests/periodic_6fold/results_true.dat +++ b/tests/regression_tests/periodic_6fold/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.858730E+00 6.824588E-03 +1.848492E+00 2.933785E-03 diff --git a/tests/regression_tests/periodic_cyls/__init__.py b/tests/regression_tests/periodic_cyls/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/periodic_cyls/test.py b/tests/regression_tests/periodic_cyls/test.py new file mode 100644 index 0000000000..a341e37994 --- /dev/null +++ b/tests/regression_tests/periodic_cyls/test.py @@ -0,0 +1,91 @@ +import openmc +import numpy as np +import pytest +from openmc.utility_funcs import change_directory +from tests.testing_harness import PyAPITestHarness + + +@pytest.fixture +def xcyl_model(): + model = openmc.Model() + # Define materials + fuel = openmc.Material() + fuel.add_nuclide('U235', 0.2) + fuel.add_nuclide('U238', 0.8) + fuel.set_density('g/cc', 19.1) + model.materials = openmc.Materials([fuel]) + + # Define geometry + # finite cylinder + x_min = openmc.XPlane(x0=0.0, boundary_type='reflective') + x_max = openmc.XPlane(x0=20.0, boundary_type='reflective') + x_cyl = openmc.XCylinder(r=20.0,boundary_type='vacuum') + # slice cylinder for periodic BC + periodic_bounding_yplane = openmc.YPlane(y0=0, boundary_type='periodic') + periodic_bounding_plane = openmc.Plane( + a=0.0, b=-np.sqrt(3) / 3, c=1, boundary_type='periodic', + ) + sixth_cyl_cell = openmc.Cell(1, fill=fuel, region = + +x_min &- x_max & -x_cyl & +periodic_bounding_yplane & +periodic_bounding_plane) + periodic_bounding_yplane.periodic_surface = periodic_bounding_plane + periodic_bounding_plane.periodic_surface = periodic_bounding_yplane + + model.geometry = openmc.Geometry([sixth_cyl_cell]) + + + # Define settings + model.settings.particles = 1000 + model.settings.batches = 4 + model.settings.inactive = 0 + model.settings.source = openmc.IndependentSource(space=openmc.stats.Box( + (0, 0, 0), (20, 20, 20)) + ) + return model + +@pytest.fixture +def ycyl_model(): + model = openmc.Model() + # Define materials + fuel = openmc.Material() + fuel.add_nuclide('U235', 0.2) + fuel.add_nuclide('U238', 0.8) + fuel.set_density('g/cc', 19.1) + model.materials = openmc.Materials([fuel]) + + # Define geometry + # finite cylinder + y_min = openmc.YPlane(y0=0.0, boundary_type='reflective') + y_max = openmc.YPlane(y0=20.0, boundary_type='reflective') + y_cyl = openmc.YCylinder(r=20.0,boundary_type='vacuum') + # slice cylinder for periodic BC + periodic_bounding_xplane = openmc.XPlane(x0=0, boundary_type='periodic') + periodic_bounding_plane = openmc.Plane( + a=-np.sqrt(3) / 3, b=0.0, c=1, boundary_type='periodic', + ) + sixth_cyl_cell = openmc.Cell(1, fill=fuel, region = + +y_min &- y_max & -y_cyl & +periodic_bounding_xplane & +periodic_bounding_plane) + periodic_bounding_xplane.periodic_surface = periodic_bounding_plane + periodic_bounding_plane.periodic_surface = periodic_bounding_xplane + model.geometry = openmc.Geometry([sixth_cyl_cell]) + + + # Define settings + model.settings.particles = 1000 + model.settings.batches = 4 + model.settings.inactive = 0 + model.settings.source = openmc.IndependentSource(space=openmc.stats.Box( + (0, 0, 0), (20, 20, 20)) + ) + return model + +def test_xcyl(xcyl_model): + with change_directory("xcyl_model"): + openmc.reset_auto_ids() + harness = PyAPITestHarness('statepoint.4.h5', xcyl_model) + harness.main() + +def test_ycyl(ycyl_model): + with change_directory("ycyl_model"): + openmc.reset_auto_ids() + harness = PyAPITestHarness('statepoint.4.h5', ycyl_model) + harness.main() \ No newline at end of file diff --git a/tests/regression_tests/periodic_cyls/xcyl_model/inputs_true.dat b/tests/regression_tests/periodic_cyls/xcyl_model/inputs_true.dat new file mode 100644 index 0000000000..7d1ecf426a --- /dev/null +++ b/tests/regression_tests/periodic_cyls/xcyl_model/inputs_true.dat @@ -0,0 +1,29 @@ + + + + + + + + + + + + + + + + + + + eigenvalue + 1000 + 4 + 0 + + + 0 0 0 20 20 20 + + + + diff --git a/tests/regression_tests/periodic_cyls/xcyl_model/results_true.dat b/tests/regression_tests/periodic_cyls/xcyl_model/results_true.dat new file mode 100644 index 0000000000..c7e3eb6703 --- /dev/null +++ b/tests/regression_tests/periodic_cyls/xcyl_model/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +1.082283E+00 6.676373E-02 diff --git a/tests/regression_tests/periodic_cyls/ycyl_model/inputs_true.dat b/tests/regression_tests/periodic_cyls/ycyl_model/inputs_true.dat new file mode 100644 index 0000000000..f3ca7e0f4a --- /dev/null +++ b/tests/regression_tests/periodic_cyls/ycyl_model/inputs_true.dat @@ -0,0 +1,29 @@ + + + + + + + + + + + + + + + + + + + eigenvalue + 1000 + 4 + 0 + + + 0 0 0 20 20 20 + + + + diff --git a/tests/regression_tests/periodic_cyls/ycyl_model/results_true.dat b/tests/regression_tests/periodic_cyls/ycyl_model/results_true.dat new file mode 100644 index 0000000000..562467f2cd --- /dev/null +++ b/tests/regression_tests/periodic_cyls/ycyl_model/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +1.082652E+00 3.316031E-02 diff --git a/tests/regression_tests/periodic_hex/results_true.dat b/tests/regression_tests/periodic_hex/results_true.dat index 584089a15d..eff00b6e16 100644 --- a/tests/regression_tests/periodic_hex/results_true.dat +++ b/tests/regression_tests/periodic_hex/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.284468E+00 2.781588E-02 +2.285622E+00 2.576768E-03 diff --git a/tests/regression_tests/photon_production_fission/results_true.dat b/tests/regression_tests/photon_production_fission/results_true.dat index b17b3621a0..af325d4b02 100644 --- a/tests/regression_tests/photon_production_fission/results_true.dat +++ b/tests/regression_tests/photon_production_fission/results_true.dat @@ -1,12 +1,12 @@ k-combined: -2.278476E+00 6.220292E-02 +2.297165E+00 1.955494E-02 tally 1: -2.664071E+00 -2.369250E+00 +2.696393E+00 +2.423937E+00 0.000000E+00 0.000000E+00 -2.664071E+00 -2.369250E+00 +2.696393E+00 +2.423937E+00 0.000000E+00 0.000000E+00 0.000000E+00 @@ -18,52 +18,52 @@ tally 1: 0.000000E+00 0.000000E+00 tally 2: -2.640755E+00 -2.326201E+00 -4.245217E+08 -6.012128E+16 +2.672029E+00 +2.380251E+00 +4.288244E+08 +6.130569E+16 0.000000E+00 0.000000E+00 -2.640755E+00 -2.326201E+00 -4.245217E+08 -6.012128E+16 +2.672029E+00 +2.380251E+00 +4.288244E+08 +6.130569E+16 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.675918E+05 -9.365733E+09 +1.711908E+05 +9.769096E+09 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.675918E+05 -9.365733E+09 +1.711908E+05 +9.769096E+09 0.000000E+00 0.000000E+00 tally 3: -2.657846E+00 -2.354717E+00 -4.245217E+08 -6.012128E+16 +2.649127E+00 +2.339294E+00 +4.288244E+08 +6.130569E+16 0.000000E+00 0.000000E+00 -2.657846E+00 -2.354717E+00 -4.245217E+08 -6.012128E+16 +2.649127E+00 +2.339294E+00 +4.288244E+08 +6.130569E+16 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.675918E+05 -9.365733E+09 +1.711908E+05 +9.769096E+09 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.675918E+05 -9.365733E+09 +1.711908E+05 +9.769096E+09 0.000000E+00 0.000000E+00 diff --git a/tests/regression_tests/ptables_off/results_true.dat b/tests/regression_tests/ptables_off/results_true.dat index 1652088ce8..3742748625 100644 --- a/tests/regression_tests/ptables_off/results_true.dat +++ b/tests/regression_tests/ptables_off/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.978318E-01 1.560055E-03 +2.968228E-01 1.770320E-03 diff --git a/tests/regression_tests/quadric_surfaces/results_true.dat b/tests/regression_tests/quadric_surfaces/results_true.dat index 382c4241e0..6fb569f522 100644 --- a/tests/regression_tests/quadric_surfaces/results_true.dat +++ b/tests/regression_tests/quadric_surfaces/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.193830E+00 1.824184E-02 +1.216213E+00 2.789559E-02 diff --git a/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat b/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat index 30e62a8853..0adfc54884 100644 --- a/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat +++ b/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat @@ -212,8 +212,8 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True - True + true + true naive diff --git a/tests/regression_tests/random_ray_adjoint_fixed_source/results_true.dat b/tests/regression_tests/random_ray_adjoint_fixed_source/results_true.dat index 7178e2f111..e9aa9015b3 100644 --- a/tests/regression_tests/random_ray_adjoint_fixed_source/results_true.dat +++ b/tests/regression_tests/random_ray_adjoint_fixed_source/results_true.dat @@ -6,4 +6,4 @@ tally 2: 9.482551E+08 tally 3: 1.956327E+05 -7.654469E+09 +7.654468E+09 diff --git a/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat b/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat index cd4e92aa1b..073348c41e 100644 --- a/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat +++ b/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat @@ -85,8 +85,8 @@ -1.26 -1.26 -1 1.26 1.26 1 - True - True + true + true diff --git a/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat b/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat index 657c841b56..dfef53cd2f 100644 --- a/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat +++ b/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat @@ -1,171 +1,171 @@ k-combined: 1.006640E+00 1.812969E-03 tally 1: -6.684129E+00 -8.939821E+00 -2.685967E+00 -1.443592E+00 +1.208044E+00 +2.920182E-01 +4.854426E-01 +4.715453E-02 0.000000E+00 0.000000E+00 -6.358774E+00 -8.091444E+00 -9.687217E-01 -1.878029E-01 +1.149242E+00 +2.643067E-01 +1.750801E-01 +6.134563E-03 0.000000E+00 0.000000E+00 -5.963160E+00 -7.117108E+00 -1.932332E-01 -7.473914E-03 +1.077743E+00 +2.324814E-01 +3.492371E-02 +2.441363E-04 0.000000E+00 0.000000E+00 -5.137593E+00 -5.283310E+00 -1.714616E-01 -5.884834E-03 -1.086218E-06 -2.361752E-13 -4.857253E+00 -4.719856E+00 -5.689580E-02 -6.476286E-04 -2.989356E-03 -1.787808E-06 -4.830516E+00 -4.666801E+00 -7.203015E-03 -1.037676E-05 -3.620020E+00 -2.620927E+00 -5.161382E+00 -5.328124E+00 -6.786255E-02 -9.210763E-04 -5.531943E+00 -6.120553E+00 -5.414034E+00 -5.864661E+00 +9.285362E-01 +1.725808E-01 +3.098889E-02 +1.922297E-04 +1.963161E-07 +7.714727E-15 +8.778641E-01 +1.541719E-01 +1.028293E-02 +2.115448E-05 +5.402741E-04 +5.839789E-08 +8.730274E-01 +1.524358E-01 +1.301813E-03 +3.389450E-07 +6.542525E-01 +8.560964E-02 +9.328247E-01 +1.740366E-01 +1.226491E-02 +3.008584E-05 +9.997969E-01 +1.999204E-01 +9.784958E-01 +1.915688E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -5.632338E+00 -6.347626E+00 +1.017952E+00 +2.073461E-01 0.000000E+00 0.000000E+00 0.000000E+00 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+2.320295E-01 +3.567737E-02 +2.547314E-04 0.000000E+00 0.000000E+00 -5.130744E+00 -5.268844E+00 -1.749233E-01 -6.123348E-03 -1.108148E-06 -2.457474E-13 -4.857340E+00 -4.720019E+00 -5.816659E-02 -6.768049E-04 -3.056125E-03 -1.868351E-06 -4.830629E+00 -4.667018E+00 -7.366289E-03 -1.085264E-05 -3.702077E+00 -2.741125E+00 -5.164864E+00 -5.335279E+00 -6.947917E-02 -9.655086E-04 -5.663725E+00 -6.415806E+00 +9.272977E-01 +1.721077E-01 +3.161443E-02 +2.000179E-04 +2.002789E-07 +8.027290E-15 +8.778794E-01 +1.541769E-01 +1.051257E-02 +2.210729E-05 +5.523400E-04 +6.102818E-08 +8.730477E-01 +1.524429E-01 +1.331320E-03 +3.544869E-07 +6.690816E-01 +8.953516E-02 +9.334544E-01 +1.742707E-01 +1.255707E-02 +3.153710E-05 +1.023613E+00 +2.095641E-01 diff --git a/tests/regression_tests/random_ray_auto_convert/infinite_medium/results_true.dat b/tests/regression_tests/random_ray_auto_convert/infinite_medium/results_true.dat index a0d7fc545f..f984f37186 100644 --- a/tests/regression_tests/random_ray_auto_convert/infinite_medium/results_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/infinite_medium/results_true.dat @@ -1,2 +1,2 @@ k-combined: -7.796949E-01 1.055316E-02 +7.479770E-01 1.624548E-02 diff --git a/tests/regression_tests/random_ray_auto_convert/material_wise/results_true.dat b/tests/regression_tests/random_ray_auto_convert/material_wise/results_true.dat index ebf510cfc7..3bade01e05 100644 --- a/tests/regression_tests/random_ray_auto_convert/material_wise/results_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/material_wise/results_true.dat @@ -1,2 +1,2 @@ k-combined: -7.375068E-01 7.015839E-03 +7.372542E-01 6.967831E-03 diff --git a/tests/regression_tests/random_ray_auto_convert/stochastic_slab/results_true.dat b/tests/regression_tests/random_ray_auto_convert/stochastic_slab/results_true.dat index 2f444fad3c..674dee4aaf 100644 --- a/tests/regression_tests/random_ray_auto_convert/stochastic_slab/results_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/stochastic_slab/results_true.dat @@ -1,2 +1,2 @@ k-combined: -7.499679E-01 8.107614E-03 +6.413334E-01 2.083132E-02 diff --git a/tests/regression_tests/random_ray_auto_convert/test.py b/tests/regression_tests/random_ray_auto_convert/test.py index fa7f2f17f4..99a931dce8 100644 --- a/tests/regression_tests/random_ray_auto_convert/test.py +++ b/tests/regression_tests/random_ray_auto_convert/test.py @@ -27,7 +27,7 @@ def test_random_ray_auto_convert(method): # Convert to a multi-group model model.convert_to_multigroup( - method=method, groups='CASMO-2', nparticles=30, + method=method, groups='CASMO-2', nparticles=100, overwrite_mgxs_library=False, mgxs_path="mgxs.h5" ) diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/__init__.py b/tests/regression_tests/random_ray_auto_convert_source_energy/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat new file mode 100644 index 0000000000..80a166c678 --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat @@ -0,0 +1,61 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 10 + 5 + + + 7000000.0 1.0 + + + multi-group + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 + 150.0 + + + + + + linear + + + 2 2 + -0.63 -0.63 + 0.63 0.63 + + + diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/results_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/results_true.dat new file mode 100644 index 0000000000..1fb09fd68a --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +7.657815E-01 2.317564E-02 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat new file mode 100644 index 0000000000..464c89a5df --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat @@ -0,0 +1,64 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 10 + 5 + + + -0.63 -0.63 -1 0.63 0.63 1 + + + true + + + multi-group + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 + 150.0 + + + + + + linear + + + 2 2 + -0.63 -0.63 + 0.63 0.63 + + + diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/results_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/results_true.dat new file mode 100644 index 0000000000..073c5c99ff --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +7.827784E-01 2.062954E-02 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat new file mode 100644 index 0000000000..80a166c678 --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat @@ -0,0 +1,61 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 10 + 5 + + + 7000000.0 1.0 + + + multi-group + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 + 150.0 + + + + + + linear + + + 2 2 + -0.63 -0.63 + 0.63 0.63 + + + diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/results_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/results_true.dat new file mode 100644 index 0000000000..c5cdf8e29f --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +7.479571E-01 2.398563E-02 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat new file mode 100644 index 0000000000..464c89a5df --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat @@ -0,0 +1,64 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + + + + + + eigenvalue + 100 + 10 + 5 + + + -0.63 -0.63 -1 0.63 0.63 1 + + + true + + + multi-group + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 + 150.0 + + + + + + linear + + + 2 2 + -0.63 -0.63 + 0.63 0.63 + + + diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/results_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/results_true.dat new file mode 100644 index 0000000000..c6cce2e39c --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/results_true.dat @@ -0,0 +1,2 @@ +k-combined: +7.620306E-01 2.175179E-02 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/test.py b/tests/regression_tests/random_ray_auto_convert_source_energy/test.py new file mode 100644 index 0000000000..bb9119d895 --- /dev/null +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/test.py @@ -0,0 +1,66 @@ +import os + +import openmc +from openmc.examples import pwr_pin_cell +from openmc import RegularMesh +from openmc.utility_funcs import change_directory +import pytest + +from tests.testing_harness import TolerantPyAPITestHarness + + +class MGXSTestHarness(TolerantPyAPITestHarness): + def _cleanup(self): + super()._cleanup() + f = 'mgxs.h5' + if os.path.exists(f): + os.remove(f) + + +@pytest.mark.parametrize("source_type", ["model", "user"]) +@pytest.mark.parametrize("method", ["stochastic_slab", "infinite_medium"]) +def test_random_ray_auto_convert_source_energy(method, source_type): + dirname = f"{method}/{source_type}" + with change_directory(dirname): + openmc.reset_auto_ids() + + # Start with a normal continuous energy model + model = pwr_pin_cell() + + # Define the source energy distribution, using different methods + source_energy = None + if source_type == "model": + model.settings.source = openmc.IndependentSource( + energy=openmc.stats.delta_function(7.0e6) + ) + elif source_type == "user": + source_energy = openmc.stats.delta_function(1.0e4) + + # Convert to a multi-group model + model.convert_to_multigroup( + method=method, groups='CASMO-8', nparticles=100, + overwrite_mgxs_library=False, mgxs_path="mgxs.h5", + source_energy=source_energy + ) + + # Convert to a random ray model + model.convert_to_random_ray() + + # Set the number of particles + model.settings.particles = 100 + + # Overlay a basic 2x2 mesh + n = 2 + mesh = RegularMesh() + mesh.dimension = (n, n) + bbox = model.geometry.bounding_box + mesh.lower_left = (bbox.lower_left[0], bbox.lower_left[1]) + mesh.upper_right = (bbox.upper_right[0], bbox.upper_right[1]) + model.settings.random_ray['source_region_meshes'] = [ + (mesh, [model.geometry.root_universe])] + + # Set the source shape to linear + model.settings.random_ray['source_shape'] = 'linear' + + harness = MGXSTestHarness('statepoint.10.h5', model) + harness.main() diff --git a/tests/regression_tests/random_ray_diagonal_stabilization/results_true.dat b/tests/regression_tests/random_ray_diagonal_stabilization/results_true.dat index c6ce6aab94..034d7f7c64 100644 --- a/tests/regression_tests/random_ray_diagonal_stabilization/results_true.dat +++ b/tests/regression_tests/random_ray_diagonal_stabilization/results_true.dat @@ -1,2 +1,2 @@ k-combined: -7.152917E-01 1.430362E-02 +7.134473E-01 1.422763E-02 diff --git a/tests/regression_tests/random_ray_diagonal_stabilization/test.py b/tests/regression_tests/random_ray_diagonal_stabilization/test.py index c7a1c9f7cd..8d36e1d258 100644 --- a/tests/regression_tests/random_ray_diagonal_stabilization/test.py +++ b/tests/regression_tests/random_ray_diagonal_stabilization/test.py @@ -23,7 +23,7 @@ def test_random_ray_diagonal_stabilization(): # MGXS data with some negatives on the diagonal, in order # to trigger diagonal correction. model.convert_to_multigroup( - method='material_wise', groups='CASMO-70', nparticles=30, + method='material_wise', groups='CASMO-70', nparticles=13, overwrite_mgxs_library=True, mgxs_path="mgxs.h5", correction='P0' ) diff --git a/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat index 4b8af76aaf..9f1987f3ac 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat index 82fe48b614..b4f57dbfa8 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat index c4fd06f421..ab91f74e50 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat index 4085b0c7a1..220fa7db64 100644 --- a/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear diff --git a/tests/regression_tests/random_ray_fixed_source_linear/linear/results_true.dat b/tests/regression_tests/random_ray_fixed_source_linear/linear/results_true.dat index 2fc08d0a42..e90d6bfdcb 100644 --- a/tests/regression_tests/random_ray_fixed_source_linear/linear/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_linear/linear/results_true.dat @@ -1,6 +1,6 @@ tally 1: -2.339085E+00 -2.747304E-01 +2.339086E+00 +2.747305E-01 tally 2: 1.089827E-01 6.069324E-04 diff --git a/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat index ff085d2fbb..f8c4430852 100644 --- a/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear_xy diff --git a/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat index 12c4d74edb..c84e544fcc 100644 --- a/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat index 07adb1ff55..05c4846e6b 100644 --- a/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat index ab077ae8aa..0c870e1006 100644 --- a/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - False + false diff --git a/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat index c4fd06f421..ab91f74e50 100644 --- a/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat index a124b5e3c4..0c05a71df3 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat @@ -115,7 +115,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - False + false flat diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/results_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/results_true.dat index 831eac5019..4d2fb6c579 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/results_true.dat @@ -83,7 +83,7 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.073356E+02 +1.073355E+02 4.630895E+02 1.263975E+01 6.427678E+00 @@ -107,7 +107,7 @@ tally 1: 2.388612E-03 5.941898E-01 1.414866E-02 -5.319555E+01 +5.319554E+01 1.134034E+02 1.967517E-01 1.551313E-03 @@ -122,7 +122,7 @@ tally 1: 8.044764E+01 2.602455E+02 3.474828E-01 -4.908567E-03 +4.908566E-03 9.665057E-01 3.797493E-02 1.561720E+02 diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat index cc557afb6e..a67495bf16 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat @@ -115,7 +115,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - False + false linear_xy diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/results_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/results_true.dat index 49813144d2..bf602d3e2d 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/results_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/results_true.dat @@ -23,7 +23,7 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -5.235812E+01 +5.235813E+01 1.099243E+02 0.000000E+00 0.000000E+00 @@ -72,12 +72,12 @@ tally 1: 0.000000E+00 0.000000E+00 9.495275E+01 -3.613372E+02 +3.613373E+02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -5.799250E+01 +5.799251E+01 1.356178E+02 0.000000E+00 0.000000E+00 @@ -86,7 +86,7 @@ tally 1: 1.066414E+02 4.570291E+02 1.254014E+01 -6.325640E+00 +6.325641E+00 3.052020E+01 3.746918E+01 4.977302E+01 @@ -107,7 +107,7 @@ tally 1: 2.371074E-03 5.920173E-01 1.404478E-02 -5.299862E+01 +5.299863E+01 1.125576E+02 1.959914E-01 1.539191E-03 @@ -118,11 +118,11 @@ tally 1: 5.781230E-02 1.341759E-04 1.430525E-01 -8.215326E-04 +8.215327E-04 7.995734E+01 2.570099E+02 3.452934E-01 -4.844058E-03 +4.844059E-03 9.604162E-01 3.747587E-02 1.556795E+02 diff --git a/tests/regression_tests/random_ray_halton_samples/inputs_true.dat b/tests/regression_tests/random_ray_halton_samples/inputs_true.dat index 3f058e45c2..36d5f6f227 100644 --- a/tests/regression_tests/random_ray_halton_samples/inputs_true.dat +++ b/tests/regression_tests/random_ray_halton_samples/inputs_true.dat @@ -85,7 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - True + true halton diff --git a/tests/regression_tests/random_ray_halton_samples/results_true.dat b/tests/regression_tests/random_ray_halton_samples/results_true.dat index 7eb307da05..256f8a744a 100644 --- a/tests/regression_tests/random_ray_halton_samples/results_true.dat +++ b/tests/regression_tests/random_ray_halton_samples/results_true.dat @@ -1,171 +1,171 @@ k-combined: 8.388051E-01 7.383265E-03 tally 1: -5.033308E+00 -5.072162E+00 -1.917335E+00 -7.360725E-01 -4.666410E+00 -4.360038E+00 -2.851812E+00 -1.629362E+00 -4.365590E-01 -3.818884E-02 -1.062497E+00 -2.262071E-01 -1.697621E+00 -5.829333E-01 -5.639912E-02 -6.427568E-04 -1.372642E-01 -3.807294E-03 -2.376683E+00 -1.151027E+00 -8.060902E-02 -1.323179E-03 -1.961862E-01 -7.837693E-03 -7.145452E+00 -1.037540E+01 -8.551803E-02 -1.486269E-03 -2.081363E-01 -8.803955E-03 -2.053205E+01 -8.469498E+01 -3.235618E-02 -2.102891E-04 -8.006311E-02 -1.287559E-03 -1.326545E+01 -3.519484E+01 -1.867471E-01 -6.975133E-03 -5.194275E-01 -5.396284E-02 -7.558115E+00 -1.142535E+01 +1.065839E+00 +2.274384E-01 +4.060094E-01 +3.300592E-02 +9.881457E-01 +1.955066E-01 +6.038893E-01 +7.306038E-02 +9.244411E-02 +1.712380E-03 +2.249905E-01 +1.014308E-02 +3.594916E-01 +2.614145E-02 +1.194318E-02 +2.882412E-05 +2.906731E-02 +1.707363E-04 +5.032954E-01 +5.161897E-02 +1.707007E-02 +5.933921E-05 +4.154514E-02 +3.514889E-04 +1.513147E+00 +4.652938E-01 +1.810962E-02 +6.665306E-05 +4.407572E-02 +3.948212E-04 +4.347893E+00 +3.798064E+00 +6.851785E-03 +9.430195E-06 +1.695426E-02 +5.773923E-05 +2.809071E+00 +1.578195E+00 +3.954523E-02 +3.127754E-04 +1.099931E-01 +2.419775E-03 +1.600493E+00 +5.123291E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -3.386211E+00 -2.294414E+00 +7.170555E-01 +1.028835E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.827274E+00 -6.782305E-01 +3.869491E-01 +3.041553E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -2.702858E+00 -1.489752E+00 +5.723683E-01 +6.680970E-02 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -7.475537E+00 -1.133971E+01 +1.583046E+00 +5.085372E-01 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.828685E+01 -6.719606E+01 +3.872447E+00 +3.013344E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.143600E+01 -2.615734E+01 +2.421670E+00 +1.172938E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -4.590713E+00 -4.224107E+00 -1.705847E+00 -5.831967E-01 -4.151691E+00 -3.454497E+00 -2.730853E+00 -1.495413E+00 -4.072633E-01 -3.325944E-02 -9.911973E-01 -1.970084E-01 -1.664732E+00 -5.598668E-01 -5.385645E-02 -5.858353E-04 -1.310758E-01 -3.470126E-03 -2.312239E+00 -1.088485E+00 -7.662778E-02 -1.195422E-03 -1.864967E-01 -7.080943E-03 -7.105765E+00 -1.025960E+01 -8.287512E-02 -1.396474E-03 -2.017039E-01 -8.272053E-03 -2.099024E+01 -8.854251E+01 -3.191885E-02 -2.048368E-04 -7.898095E-02 -1.254175E-03 -1.355820E+01 -3.676862E+01 -1.815102E-01 -6.590727E-03 -5.048614E-01 -5.098890E-02 -5.093659E+00 -5.192360E+00 -1.874632E+00 -7.031793E-01 -4.562478E+00 -4.165199E+00 -2.870213E+00 -1.650126E+00 -4.244068E-01 -3.608745E-02 -1.032921E+00 -2.137598E-01 -1.703400E+00 -5.873029E-01 -5.464557E-02 -6.042855E-04 -1.329964E-01 -3.579413E-03 -2.389118E+00 -1.163674E+00 -7.832237E-02 -1.251254E-03 -1.906210E-01 -7.411654E-03 -7.162706E+00 -1.042515E+01 -8.273831E-02 -1.391799E-03 -2.013709E-01 -8.244359E-03 -2.043145E+01 -8.383557E+01 -3.096158E-02 -1.924116E-04 -7.661226E-02 -1.178098E-03 -1.314148E+01 -3.454143E+01 -1.771732E-01 -6.279887E-03 -4.927984E-01 -4.858410E-02 +9.721128E-01 +1.894086E-01 +3.612242E-01 +2.615053E-02 +8.791475E-01 +1.548996E-01 +5.782742E-01 +6.705354E-02 +8.624040E-02 +1.491336E-03 +2.098919E-01 +8.833753E-03 +3.525265E-01 +2.510689E-02 +1.140473E-02 +2.627142E-05 +2.775683E-02 +1.556157E-04 +4.896481E-01 +4.881407E-02 +1.622698E-02 +5.360976E-05 +3.949322E-02 +3.175511E-04 +1.504743E+00 +4.601003E-01 +1.754995E-02 +6.262618E-05 +4.271358E-02 +3.709679E-04 +4.444922E+00 +3.970609E+00 +6.759184E-03 +9.185746E-06 +1.672513E-02 +5.624252E-05 +2.871068E+00 +1.648778E+00 +3.843643E-02 +2.955428E-04 +1.069090E-01 +2.286455E-03 +1.078620E+00 +2.328291E-01 +3.969671E-01 +3.153110E-02 +9.661384E-01 +1.867708E-01 +6.077864E-01 +7.399164E-02 +8.987086E-02 +1.618157E-03 +2.187277E-01 +9.584966E-03 +3.607158E-01 +2.633746E-02 +1.157185E-02 +2.709895E-05 +2.816358E-02 +1.605174E-04 +5.059289E-01 +5.218618E-02 +1.658585E-02 +5.611375E-05 +4.036663E-02 +3.323832E-04 +1.516801E+00 +4.675245E-01 +1.752096E-02 +6.241641E-05 +4.264304E-02 +3.697253E-04 +4.326588E+00 +3.759517E+00 +6.556454E-03 +8.628460E-06 +1.622349E-02 +5.283037E-05 +2.782815E+00 +1.548888E+00 +3.751781E-02 +2.815972E-04 +1.043539E-01 +2.178566E-03 diff --git a/tests/regression_tests/random_ray_k_eff/inputs_true.dat b/tests/regression_tests/random_ray_k_eff/inputs_true.dat index 33c9cac339..545bd1d457 100644 --- a/tests/regression_tests/random_ray_k_eff/inputs_true.dat +++ b/tests/regression_tests/random_ray_k_eff/inputs_true.dat @@ -85,7 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - True + true diff --git a/tests/regression_tests/random_ray_k_eff/results_true.dat b/tests/regression_tests/random_ray_k_eff/results_true.dat index a21929d53b..ace18df8cc 100644 --- a/tests/regression_tests/random_ray_k_eff/results_true.dat +++ b/tests/regression_tests/random_ray_k_eff/results_true.dat @@ -1,171 +1,171 @@ k-combined: -8.400321E-01 8.023358E-03 +8.400321E-01 8.023357E-03 tally 1: -5.086559E+00 -5.180935E+00 -1.885166E+00 -7.115503E-01 -4.588116E+00 -4.214784E+00 -2.860400E+00 -1.639328E+00 -4.245221E-01 -3.610929E-02 -1.033202E+00 -2.138892E-01 -1.692631E+00 -5.793966E-01 -5.445818E-02 -5.996625E-04 -1.325403E-01 -3.552030E-03 -2.372248E+00 -1.146944E+00 -7.808142E-02 -1.242278E-03 -1.900346E-01 -7.358490E-03 -7.134948E+00 -1.034824E+01 -8.272647E-02 -1.391871E-03 -2.013421E-01 -8.244788E-03 -2.043539E+01 -8.389902E+01 -3.099367E-02 -1.930673E-04 -7.669167E-02 -1.182113E-03 -1.313212E+01 -3.449537E+01 -1.764293E-01 -6.225586E-03 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b/tests/regression_tests/random_ray_k_eff_mesh/inputs_true.dat @@ -85,7 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - True + true diff --git a/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat b/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat index 535db3b551..2ae8fad85f 100644 --- a/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat +++ b/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat @@ -1,171 +1,171 @@ k-combined: 8.379203E-01 8.057199E-03 tally 1: -5.080171E+00 -5.167984E+00 -1.880341E+00 -7.079266E-01 -4.576373E+00 -4.193319E+00 -2.859914E+00 -1.638769E+00 -4.243332E-01 -3.607732E-02 -1.032742E+00 -2.136998E-01 -1.692643E+00 -5.794069E-01 -5.445214E-02 -5.995212E-04 -1.325256E-01 -3.551193E-03 -2.372336E+00 -1.147031E+00 -7.807378E-02 -1.242019E-03 -1.900160E-01 -7.356955E-03 -7.135636E+00 -1.035026E+01 -8.273225E-02 -1.392069E-03 -2.013562E-01 -8.245961E-03 -2.044034E+01 -8.394042E+01 -3.100485E-02 -1.932097E-04 -7.671933E-02 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a/tests/regression_tests/random_ray_linear/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_linear/linear/inputs_true.dat @@ -85,7 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - True + true linear diff --git a/tests/regression_tests/random_ray_linear/linear/results_true.dat b/tests/regression_tests/random_ray_linear/linear/results_true.dat index 6617c78216..77d41f3732 100644 --- a/tests/regression_tests/random_ray_linear/linear/results_true.dat +++ b/tests/regression_tests/random_ray_linear/linear/results_true.dat @@ -1,171 +1,171 @@ k-combined: 1.095967E+00 1.543581E-02 tally 1: -2.548108E+01 -3.269093E+01 -9.271804E+00 -4.327275E+00 -2.256572E+01 -2.563210E+01 -1.816107E+01 -1.653421E+01 -2.659203E+00 -3.544951E-01 -6.471969E+00 -2.099810E+00 -1.364193E+01 -9.308675E+00 -4.362828E-01 -9.521133E-03 -1.061825E+00 -5.639730E-02 -1.746102E+01 -1.524680E+01 -5.733016E-01 -1.643671E-02 -1.395301E+00 -9.736091E-02 -4.539598E+01 -1.030472E+02 -5.263055E-01 -1.385088E-02 -1.280938E+00 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b/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat index 81527c4793..7f76f2fd1c 100644 --- a/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat @@ -85,7 +85,7 @@ -1.26 -1.26 -1 1.26 1.26 1 - True + true linear_xy diff --git a/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat b/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat index abfd03c067..052608b425 100644 --- a/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat +++ b/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat @@ -1,171 +1,171 @@ k-combined: 1.104727E+00 1.593303E-02 tally 1: -2.566934E+01 -3.317503E+01 -9.417202E+00 -4.465518E+00 -2.291958E+01 -2.645097E+01 -1.823903E+01 -1.667438E+01 -2.679931E+00 -3.600420E-01 -6.522415E+00 -2.132667E+00 -1.365623E+01 -9.327448E+00 -4.370682E-01 -9.554968E-03 -1.063736E+00 -5.659772E-02 -1.750634E+01 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+1.203670E-03 +4.314785E-01 +9.312148E-03 diff --git a/tests/regression_tests/random_ray_low_density/__init__.py b/tests/regression_tests/random_ray_low_density/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/regression_tests/random_ray_low_density/inputs_true.dat b/tests/regression_tests/random_ray_low_density/inputs_true.dat new file mode 100644 index 0000000000..ab91f74e50 --- /dev/null +++ b/tests/regression_tests/random_ray_low_density/inputs_true.dat @@ -0,0 +1,244 @@ + + + + mgxs.h5 + + + + + + + + + + + + + + + + + + + + + 2.5 2.5 2.5 + 12 12 12 + 0.0 0.0 0.0 + +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +1 1 2 2 2 2 2 2 2 2 3 3 +1 1 2 2 2 2 2 2 2 2 3 3 + +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +2 2 2 2 2 2 2 2 2 2 3 3 +2 2 2 2 2 2 2 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3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 +3 3 3 3 3 3 3 3 3 3 3 3 + + + + + + + + + + fixed source + 90 + 10 + 5 + + + 100.0 1.0 + + + universe + 1 + + + multi-group + + 500.0 + 100.0 + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true + + + + + 1 + + + 2 + + + 3 + + + 3 + flux + tracklength + + + 2 + flux + tracklength + + + 1 + flux + tracklength + + + diff --git a/tests/regression_tests/random_ray_low_density/results_true.dat b/tests/regression_tests/random_ray_low_density/results_true.dat new file mode 100644 index 0000000000..a4b3ee1bcd --- /dev/null +++ b/tests/regression_tests/random_ray_low_density/results_true.dat @@ -0,0 +1,9 @@ +tally 1: +5.973607E-01 +7.155477E-02 +tally 2: +3.206216E-02 +2.063375E-04 +tally 3: +2.096415E-03 +8.804963E-07 diff --git a/tests/regression_tests/random_ray_low_density/test.py b/tests/regression_tests/random_ray_low_density/test.py new file mode 100644 index 0000000000..1b4ffb7818 --- /dev/null +++ b/tests/regression_tests/random_ray_low_density/test.py @@ -0,0 +1,60 @@ +import os + +import numpy as np +import openmc +from openmc.examples import random_ray_three_region_cube + +from tests.testing_harness import TolerantPyAPITestHarness + + +class MGXSTestHarness(TolerantPyAPITestHarness): + def _cleanup(self): + super()._cleanup() + f = 'mgxs.h5' + if os.path.exists(f): + os.remove(f) + + +def test_random_ray_low_density(): + model = random_ray_three_region_cube() + + # Rebuild the MGXS library to have a material with very + # low macroscopic cross sections + ebins = [1e-5, 20.0e6] + groups = openmc.mgxs.EnergyGroups(group_edges=ebins) + + void_sigma_a = 4.0e-6 + void_sigma_s = 3.0e-4 + void_mat_data = openmc.XSdata('void', groups) + void_mat_data.order = 0 + void_mat_data.set_total([void_sigma_a + void_sigma_s]) + void_mat_data.set_absorption([void_sigma_a]) + void_mat_data.set_scatter_matrix( + np.rollaxis(np.array([[[void_sigma_s]]]), 0, 3)) + + absorber_sigma_a = 0.75 + absorber_sigma_s = 0.25 + absorber_mat_data = openmc.XSdata('absorber', groups) + absorber_mat_data.order = 0 + absorber_mat_data.set_total([absorber_sigma_a + absorber_sigma_s]) + absorber_mat_data.set_absorption([absorber_sigma_a]) + absorber_mat_data.set_scatter_matrix( + np.rollaxis(np.array([[[absorber_sigma_s]]]), 0, 3)) + + multiplier = 0.0000001 + source_sigma_a = void_sigma_a * multiplier + source_sigma_s = void_sigma_s * multiplier + source_mat_data = openmc.XSdata('source', groups) + source_mat_data.order = 0 + source_mat_data.set_total([source_sigma_a + source_sigma_s]) + source_mat_data.set_absorption([source_sigma_a]) + source_mat_data.set_scatter_matrix( + np.rollaxis(np.array([[[source_sigma_s]]]), 0, 3)) + + mg_cross_sections_file = openmc.MGXSLibrary(groups) + mg_cross_sections_file.add_xsdatas( + [source_mat_data, void_mat_data, absorber_mat_data]) + mg_cross_sections_file.export_to_hdf5() + + harness = MGXSTestHarness('statepoint.10.h5', model) + harness.main() diff --git a/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat b/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat index 82ad979da8..088f803bfa 100644 --- a/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat +++ b/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat @@ -211,7 +211,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/random_ray_point_source_locator/results_true.dat b/tests/regression_tests/random_ray_point_source_locator/results_true.dat index 1785dda574..8c6f358dd3 100644 --- a/tests/regression_tests/random_ray_point_source_locator/results_true.dat +++ b/tests/regression_tests/random_ray_point_source_locator/results_true.dat @@ -1,9 +1,9 @@ tally 1: -2.633900E+00 -2.948207E+00 +2.633923E+00 +2.948228E+00 tally 2: -1.440463E-01 -3.294032E-03 +1.440456E-01 +3.293984E-03 tally 3: 9.425207E-03 1.089748E-05 diff --git a/tests/regression_tests/random_ray_void/flat/inputs_true.dat b/tests/regression_tests/random_ray_void/flat/inputs_true.dat index ea8c22f0b5..aa28e7b68b 100644 --- a/tests/regression_tests/random_ray_void/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_void/flat/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true flat diff --git a/tests/regression_tests/random_ray_void/linear/inputs_true.dat b/tests/regression_tests/random_ray_void/linear/inputs_true.dat index a089604ef4..e4b2f22fa2 100644 --- a/tests/regression_tests/random_ray_void/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_void/linear/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear diff --git a/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat index 089534d744..8e8a8ed9b8 100644 --- a/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true hybrid diff --git a/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat index 56507df045..1e25b97da6 100644 --- a/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true naive diff --git a/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat index 0331b562cd..78c1626976 100644 --- a/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true simulation_averaged diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat index 343833210e..47a8a71824 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear hybrid diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/results_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/results_true.dat index 2fc08d0a42..e90d6bfdcb 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/results_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/results_true.dat @@ -1,6 +1,6 @@ tally 1: -2.339085E+00 -2.747304E-01 +2.339086E+00 +2.747305E-01 tally 2: 1.089827E-01 6.069324E-04 diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat index 50be43eb38..80a9ada4d5 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear naive diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat index 3d64ab9783..4f032a62a8 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat @@ -212,7 +212,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true linear simulation_averaged diff --git a/tests/regression_tests/reflective_plane/results_true.dat b/tests/regression_tests/reflective_plane/results_true.dat index a1acfaad7e..a4d6edb677 100644 --- a/tests/regression_tests/reflective_plane/results_true.dat +++ b/tests/regression_tests/reflective_plane/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.276857E+00 8.776678E-03 +2.279066E+00 4.793565E-03 diff --git a/tests/regression_tests/resonance_scattering/results_true.dat b/tests/regression_tests/resonance_scattering/results_true.dat index 8316e720e2..72f0933b83 100644 --- a/tests/regression_tests/resonance_scattering/results_true.dat +++ b/tests/regression_tests/resonance_scattering/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.462509E+00 2.205413E-02 +1.462428E+00 1.828903E-02 diff --git a/tests/regression_tests/rotation/results_true.dat b/tests/regression_tests/rotation/results_true.dat index 0fb8ba981f..6db3d329a0 100644 --- a/tests/regression_tests/rotation/results_true.dat +++ b/tests/regression_tests/rotation/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.175600E-01 1.117465E-02 +4.459219E-01 1.899168E-02 diff --git a/tests/regression_tests/salphabeta/results_true.dat b/tests/regression_tests/salphabeta/results_true.dat index d5c7f66e90..75a81075e9 100644 --- a/tests/regression_tests/salphabeta/results_true.dat +++ b/tests/regression_tests/salphabeta/results_true.dat @@ -1,2 +1,2 @@ k-combined: -8.694866E-01 2.033328E-02 +8.628529E-01 3.120924E-02 diff --git a/tests/regression_tests/score_current/results_true.dat b/tests/regression_tests/score_current/results_true.dat index ff939301d0..6bb74445ce 100644 --- a/tests/regression_tests/score_current/results_true.dat +++ b/tests/regression_tests/score_current/results_true.dat @@ -1,274 +1,490 @@ k-combined: -2.298294E-01 3.256961E-01 +7.729082E-01 3.775399E-02 tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.150000E-01 -2.753000E-03 -1.820000E-01 -6.756000E-03 +1.200000E-01 +2.924000E-03 +1.740000E-01 +6.270000E-03 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 -1.110000E-01 -2.601000E-03 -1.530000E-01 -4.865000E-03 -1.910000E-01 -7.535000E-03 +1.200000E-01 +3.044000E-03 +1.510000E-01 +4.615000E-03 +1.710000E-01 +6.067000E-03 0.000000E+00 0.000000E+00 -7.100000E-02 -1.079000E-03 -1.500000E-01 -4.606000E-03 -1.820000E-01 -6.756000E-03 -1.150000E-01 -2.753000E-03 -1.610000E-01 -5.383000E-03 -1.230000E-01 -3.141000E-03 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -1.370000E-01 -3.951000E-03 -2.600000E-01 -1.366400E-02 -1.930000E-01 -7.573000E-03 -0.000000E+00 -0.000000E+00 -8.500000E-02 -1.533000E-03 -2.040000E-01 -8.426000E-03 -1.230000E-01 -3.141000E-03 -1.610000E-01 -5.383000E-03 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 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+0.000000E+00 +0.000000E+00 +1.690000E-01 +6.135000E-03 +0.000000E+00 +0.000000E+00 +1.220000E-01 +3.344000E-03 +0.000000E+00 +0.000000E+00 +1.540000E-01 +4.986000E-03 +0.000000E+00 +0.000000E+00 +2.690000E-01 +1.478100E-02 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.030000E-01 +2.543000E-03 +0.000000E+00 +0.000000E+00 +1.870000E-01 +7.267000E-03 +0.000000E+00 +0.000000E+00 +1.690000E-01 +5.731000E-03 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +0.000000E+00 +1.220000E-01 +3.344000E-03 +0.000000E+00 +0.000000E+00 +1.690000E-01 +6.135000E-03 +0.000000E+00 +0.000000E+00 0.000000E+00 0.000000E+00 -1.820000E-01 -6.660000E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1901,11 +1917,11 @@ tally 2: 0.000000E+00 0.000000E+00 1.170000E-01 -2.789000E-03 +2.807000E-03 0.000000E+00 0.000000E+00 -1.300000E-01 -3.604000E-03 +1.760000E-01 +6.534000E-03 0.000000E+00 0.000000E+00 0.000000E+00 @@ -1916,32 +1932,16 @@ tally 2: 0.000000E+00 0.000000E+00 0.000000E+00 -1.120000E-01 -2.640000E-03 +6.000000E-02 +8.060000E-04 0.000000E+00 0.000000E+00 -1.430000E-01 -4.163000E-03 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -4.900000E-02 -5.630000E-04 -0.000000E+00 -0.000000E+00 -1.670000E-01 -5.653000E-03 -0.000000E+00 -0.000000E+00 -1.670000E-01 -5.701000E-03 +1.290000E-01 +3.487000E-03 +0.000000E+00 +0.000000E+00 +1.790000E-01 +6.747000E-03 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/tests/regression_tests/seed/results_true.dat b/tests/regression_tests/seed/results_true.dat index bcd7118253..ff34071c10 100644 --- a/tests/regression_tests/seed/results_true.dat +++ b/tests/regression_tests/seed/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.069730E-01 2.632099E-03 +3.015003E-01 5.094212E-03 diff --git a/tests/regression_tests/source/inputs_true.dat b/tests/regression_tests/source/inputs_true.dat index 9f10b79d6b..0c3764ba6f 100644 --- a/tests/regression_tests/source/inputs_true.dat +++ b/tests/regression_tests/source/inputs_true.dat @@ -25,7 +25,7 @@ -2.0 0.0 2.0 0.2 0.3 0.2 - + -1.0 0.0 1.0 0.5 0.25 0.25 diff --git a/tests/regression_tests/source/results_true.dat b/tests/regression_tests/source/results_true.dat index 673d27c8af..7d03c696d3 100644 --- a/tests/regression_tests/source/results_true.dat +++ b/tests/regression_tests/source/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.959436E-01 2.782384E-03 +3.080655E-01 4.837707E-03 diff --git a/tests/regression_tests/source_file/results_true.dat b/tests/regression_tests/source_file/results_true.dat index 264e3d580d..359e0526e6 100644 --- a/tests/regression_tests/source_file/results_true.dat +++ b/tests/regression_tests/source_file/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.983135E-01 5.116978E-03 +2.827397E-01 1.150437E-03 diff --git a/tests/regression_tests/source_mcpl_file/results_true.dat b/tests/regression_tests/source_mcpl_file/results_true.dat index 264e3d580d..3ba1a45200 100644 --- a/tests/regression_tests/source_mcpl_file/results_true.dat +++ b/tests/regression_tests/source_mcpl_file/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.983135E-01 5.116978E-03 +2.827397E-01 1.150438E-03 diff --git a/tests/regression_tests/sourcepoint_batch/results_true.dat b/tests/regression_tests/sourcepoint_batch/results_true.dat index 2770f25ed1..3665bdd08d 100644 --- a/tests/regression_tests/sourcepoint_batch/results_true.dat +++ b/tests/regression_tests/sourcepoint_batch/results_true.dat @@ -1,3 +1,3 @@ k-combined: -3.074376E-01 3.049465E-03 -3.667754E+00 -7.701697E+00 2.213664E+00 +2.920435E-01 9.109227E-04 +1.101997E+00 -8.197502E+00 4.294606E+00 diff --git a/tests/regression_tests/sourcepoint_latest/results_true.dat b/tests/regression_tests/sourcepoint_latest/results_true.dat index bbf03de943..97b997ae6b 100644 --- a/tests/regression_tests/sourcepoint_latest/results_true.dat +++ b/tests/regression_tests/sourcepoint_latest/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 diff --git a/tests/regression_tests/sourcepoint_restart/results_true.dat b/tests/regression_tests/sourcepoint_restart/results_true.dat index b6d85872d1..c20b5f2a0a 100644 --- a/tests/regression_tests/sourcepoint_restart/results_true.dat +++ b/tests/regression_tests/sourcepoint_restart/results_true.dat @@ -1,46 +1,14 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 tally 1: 1.300000E-02 -4.700000E-05 -5.741381E-03 -9.030024E-06 +3.900000E-05 +5.833114E-03 +7.476880E-06 0.000000E+00 0.000000E+00 -3.067112E-04 -9.407179E-08 -1.000000E-03 -1.000000E-06 -3.015814E-04 -9.095135E-08 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -2.600000E-02 -1.420000E-04 -1.268989E-02 -3.464490E-05 -0.000000E+00 -0.000000E+00 -2.948908E-04 -8.696057E-08 -1.000000E-03 -1.000000E-06 -1.535009E-03 -1.224718E-06 -1.000000E-03 -1.000000E-06 -0.000000E+00 -0.000000E+00 -3.200000E-02 -2.760000E-04 -1.248507E-02 -3.714039E-05 -0.000000E+00 -0.000000E+00 -9.208601E-04 -4.708050E-07 +1.164000E-03 +5.072152E-07 0.000000E+00 0.000000E+00 0.000000E+00 @@ -49,602 +17,26 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -1.900000E-02 -7.500000E-05 -8.218811E-03 -1.462963E-05 +2.100000E-02 +1.110000E-04 +1.108363E-02 +2.889480E-05 0.000000E+00 0.000000E+00 -9.070399E-04 -2.743247E-07 -0.000000E+00 -0.000000E+00 -9.047443E-04 -8.185622E-07 -1.000000E-03 -1.000000E-06 -0.000000E+00 -0.000000E+00 -1.200000E-02 -5.000000E-05 -3.938144E-03 -5.245641E-06 -0.000000E+00 -0.000000E+00 -3.067112E-04 -9.407179E-08 -1.000000E-03 -1.000000E-06 -5.897816E-04 -3.478423E-07 -0.000000E+00 -0.000000E+00 -2.948908E-04 -8.696057E-08 -2.000000E-02 -1.260000E-04 -9.079852E-03 -2.657486E-05 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 -0.000000E+00 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a/tests/regression_tests/statepoint_batch/materials.xml b/tests/regression_tests/statepoint_batch/materials.xml deleted file mode 100644 index 2472a74717..0000000000 --- a/tests/regression_tests/statepoint_batch/materials.xml +++ /dev/null @@ -1,9 +0,0 @@ - - - - - - - - - diff --git a/tests/regression_tests/statepoint_batch/results_true.dat b/tests/regression_tests/statepoint_batch/results_true.dat deleted file mode 100644 index f5c855d777..0000000000 --- a/tests/regression_tests/statepoint_batch/results_true.dat +++ /dev/null @@ -1,2 +0,0 @@ -k-combined: -3.048864E-01 1.689118E-03 diff --git a/tests/regression_tests/statepoint_batch/settings.xml b/tests/regression_tests/statepoint_batch/settings.xml deleted file mode 100644 index e2f8dad47b..0000000000 --- a/tests/regression_tests/statepoint_batch/settings.xml +++ /dev/null @@ -1,17 +0,0 @@ - - - - - - eigenvalue - 10 - 5 - 1000 - - - - -4 -4 -4 4 4 4 - - - - diff --git a/tests/regression_tests/statepoint_batch/test.py b/tests/regression_tests/statepoint_batch/test.py deleted file mode 100644 index 323b28fc65..0000000000 --- a/tests/regression_tests/statepoint_batch/test.py +++ /dev/null @@ -1,18 +0,0 @@ -from tests.testing_harness import TestHarness - - -class StatepointTestHarness(TestHarness): - def __init__(self): - super().__init__(None) - - def _test_output_created(self): - """Make sure statepoint files have been created.""" - sps = ('statepoint.03.h5', 'statepoint.06.h5', 'statepoint.09.h5') - for sp in sps: - self._sp_name = sp - TestHarness._test_output_created(self) - - -def test_statepoint_batch(): - harness = StatepointTestHarness() - harness.main() diff --git a/tests/regression_tests/statepoint_restart/results_true.dat b/tests/regression_tests/statepoint_restart/results_true.dat index aebc971f49..b919b30005 100644 --- a/tests/regression_tests/statepoint_restart/results_true.dat +++ b/tests/regression_tests/statepoint_restart/results_true.dat @@ -1,66 +1,18 @@ k-combined: -3.070134E-01 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+1442,11 @@ tally 1: 0.000000E+00 0.000000E+00 tally 2: -5.818100E-01 -6.772558E-02 -6.344749E-01 -8.054355E-02 -3.690180E+00 -2.724752E+00 -4.102635E+01 -3.367908E+02 +5.554367E-01 +6.170503E-02 +6.055520E-01 +7.334109E-02 +3.526894E+00 +2.488065E+00 +3.925114E+01 +3.081807E+02 diff --git a/tests/regression_tests/statepoint_sourcesep/results_true.dat b/tests/regression_tests/statepoint_sourcesep/results_true.dat index bbf03de943..97b997ae6b 100644 --- a/tests/regression_tests/statepoint_sourcesep/results_true.dat +++ b/tests/regression_tests/statepoint_sourcesep/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 diff --git a/tests/regression_tests/stride/results_true.dat b/tests/regression_tests/stride/results_true.dat index a654111500..825de37667 100644 --- a/tests/regression_tests/stride/results_true.dat +++ b/tests/regression_tests/stride/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.978080E-01 6.106774E-03 +2.953207E-01 2.874356E-03 diff --git a/tests/regression_tests/surface_source/surface_source_true.h5 b/tests/regression_tests/surface_source/surface_source_true.h5 index d056d73284..d343d12aed 100644 Binary files a/tests/regression_tests/surface_source/surface_source_true.h5 and b/tests/regression_tests/surface_source/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source/surface_source_true.mcpl b/tests/regression_tests/surface_source/surface_source_true.mcpl index 7c819ac9bd..ca4b7c2c42 100644 Binary files a/tests/regression_tests/surface_source/surface_source_true.mcpl and b/tests/regression_tests/surface_source/surface_source_true.mcpl differ diff --git a/tests/regression_tests/surface_source_write/case-01/results_true.dat b/tests/regression_tests/surface_source_write/case-01/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-01/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-01/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-01/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-01/surface_source_true.h5 index 82dca4d032..3a2315acc1 100644 Binary files a/tests/regression_tests/surface_source_write/case-01/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-01/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-02/results_true.dat b/tests/regression_tests/surface_source_write/case-02/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-02/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-02/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-02/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-02/surface_source_true.h5 index 872efa0707..2c2d5bc001 100644 Binary files a/tests/regression_tests/surface_source_write/case-02/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-02/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-03/results_true.dat b/tests/regression_tests/surface_source_write/case-03/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-03/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-03/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-03/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-03/surface_source_true.h5 index 04a6ac9a38..d14771f5a0 100644 Binary files a/tests/regression_tests/surface_source_write/case-03/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-03/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-04/results_true.dat b/tests/regression_tests/surface_source_write/case-04/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-04/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-04/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-04/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-04/surface_source_true.h5 index 75c309eb4f..d2acc69910 100644 Binary files a/tests/regression_tests/surface_source_write/case-04/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-04/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-05/results_true.dat b/tests/regression_tests/surface_source_write/case-05/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-05/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-05/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-05/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-05/surface_source_true.h5 index 1a2f54d765..553090b19e 100644 Binary files a/tests/regression_tests/surface_source_write/case-05/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-05/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-06/results_true.dat b/tests/regression_tests/surface_source_write/case-06/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-06/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-06/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-06/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-06/surface_source_true.h5 index bef135e5ac..60a9f4f821 100644 Binary files a/tests/regression_tests/surface_source_write/case-06/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-06/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-07/results_true.dat b/tests/regression_tests/surface_source_write/case-07/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-07/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-07/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-07/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-07/surface_source_true.h5 index f84a5c4c5b..cb3079251c 100644 Binary files a/tests/regression_tests/surface_source_write/case-07/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-07/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-08/results_true.dat b/tests/regression_tests/surface_source_write/case-08/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-08/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-08/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-08/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-08/surface_source_true.h5 index 1fd302a7cd..ed3aba9077 100644 Binary files a/tests/regression_tests/surface_source_write/case-08/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-08/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-09/results_true.dat b/tests/regression_tests/surface_source_write/case-09/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-09/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-09/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-09/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-09/surface_source_true.h5 index af832f060c..d62363f97f 100644 Binary files a/tests/regression_tests/surface_source_write/case-09/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-09/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-10/results_true.dat b/tests/regression_tests/surface_source_write/case-10/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-10/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-10/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-10/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-10/surface_source_true.h5 index 1512d86929..acaf39cb48 100644 Binary files a/tests/regression_tests/surface_source_write/case-10/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-10/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-11/results_true.dat b/tests/regression_tests/surface_source_write/case-11/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-11/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-11/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-11/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-11/surface_source_true.h5 index 0edb06c88e..962f95fdda 100644 Binary files a/tests/regression_tests/surface_source_write/case-11/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-11/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-12/results_true.dat b/tests/regression_tests/surface_source_write/case-12/results_true.dat index d793a7e421..ad927bdf30 100644 --- a/tests/regression_tests/surface_source_write/case-12/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-12/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.752377E-02 6.773395E-03 +4.929000E-02 8.212396E-03 diff --git a/tests/regression_tests/surface_source_write/case-12/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-12/surface_source_true.h5 index ea81a82509..4b830d057d 100644 Binary files a/tests/regression_tests/surface_source_write/case-12/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-12/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-13/results_true.dat b/tests/regression_tests/surface_source_write/case-13/results_true.dat index d793a7e421..ad927bdf30 100644 --- a/tests/regression_tests/surface_source_write/case-13/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-13/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.752377E-02 6.773395E-03 +4.929000E-02 8.212396E-03 diff --git a/tests/regression_tests/surface_source_write/case-13/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-13/surface_source_true.h5 index 08bd809852..f53e2c3a2b 100644 Binary files a/tests/regression_tests/surface_source_write/case-13/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-13/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-14/results_true.dat b/tests/regression_tests/surface_source_write/case-14/results_true.dat index d793a7e421..ad927bdf30 100644 --- a/tests/regression_tests/surface_source_write/case-14/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-14/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.752377E-02 6.773395E-03 +4.929000E-02 8.212396E-03 diff --git a/tests/regression_tests/surface_source_write/case-14/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-14/surface_source_true.h5 index 50cddcc70c..ec049fec48 100644 Binary files a/tests/regression_tests/surface_source_write/case-14/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-14/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-15/results_true.dat b/tests/regression_tests/surface_source_write/case-15/results_true.dat index d793a7e421..ad927bdf30 100644 --- a/tests/regression_tests/surface_source_write/case-15/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-15/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.752377E-02 6.773395E-03 +4.929000E-02 8.212396E-03 diff --git a/tests/regression_tests/surface_source_write/case-15/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-15/surface_source_true.h5 index 3e15017a16..fd5892096c 100644 Binary files a/tests/regression_tests/surface_source_write/case-15/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-15/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-16/results_true.dat b/tests/regression_tests/surface_source_write/case-16/results_true.dat index a97be70cae..cd0619c1fe 100644 --- a/tests/regression_tests/surface_source_write/case-16/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-16/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.496403E+00 3.891283E-02 +1.403371E+00 1.456192E-02 diff --git a/tests/regression_tests/surface_source_write/case-16/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-16/surface_source_true.h5 index 49f67e8205..147ce03583 100644 Binary files a/tests/regression_tests/surface_source_write/case-16/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-16/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-17/results_true.dat b/tests/regression_tests/surface_source_write/case-17/results_true.dat index a97be70cae..cd0619c1fe 100644 --- a/tests/regression_tests/surface_source_write/case-17/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-17/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.496403E+00 3.891283E-02 +1.403371E+00 1.456192E-02 diff --git a/tests/regression_tests/surface_source_write/case-17/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-17/surface_source_true.h5 index 35878eecae..436063aee2 100644 Binary files a/tests/regression_tests/surface_source_write/case-17/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-17/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-18/results_true.dat b/tests/regression_tests/surface_source_write/case-18/results_true.dat index a97be70cae..cd0619c1fe 100644 --- a/tests/regression_tests/surface_source_write/case-18/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-18/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.496403E+00 3.891283E-02 +1.403371E+00 1.456192E-02 diff --git a/tests/regression_tests/surface_source_write/case-18/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-18/surface_source_true.h5 index 36da9e7a7f..436063aee2 100644 Binary files a/tests/regression_tests/surface_source_write/case-18/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-18/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-19/results_true.dat b/tests/regression_tests/surface_source_write/case-19/results_true.dat index a97be70cae..cd0619c1fe 100644 --- a/tests/regression_tests/surface_source_write/case-19/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-19/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.496403E+00 3.891283E-02 +1.403371E+00 1.456192E-02 diff --git a/tests/regression_tests/surface_source_write/case-19/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-19/surface_source_true.h5 index f4261451dd..eda3e030bd 100644 Binary files a/tests/regression_tests/surface_source_write/case-19/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-19/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-20/results_true.dat b/tests/regression_tests/surface_source_write/case-20/results_true.dat index 7ccce7cc3a..44293cf091 100644 --- a/tests/regression_tests/surface_source_write/case-20/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-20/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.149925E+00 2.542255E-01 +1.266853E+00 4.552028E-02 diff --git a/tests/regression_tests/surface_source_write/case-20/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-20/surface_source_true.h5 index fa8a4e6287..083ce90c89 100644 Binary files a/tests/regression_tests/surface_source_write/case-20/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-20/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-21/results_true.dat b/tests/regression_tests/surface_source_write/case-21/results_true.dat index 7ccce7cc3a..44293cf091 100644 --- a/tests/regression_tests/surface_source_write/case-21/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-21/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.149925E+00 2.542255E-01 +1.266853E+00 4.552028E-02 diff --git a/tests/regression_tests/surface_source_write/case-21/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-21/surface_source_true.h5 index ed87ce849f..f7e886db4f 100644 Binary files a/tests/regression_tests/surface_source_write/case-21/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-21/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-a01/results_true.dat b/tests/regression_tests/surface_source_write/case-a01/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-a01/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-a01/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-a01/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-a01/surface_source_true.h5 index 4a86235679..807211e3ac 100644 Binary files a/tests/regression_tests/surface_source_write/case-a01/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-a01/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d01/results_true.dat b/tests/regression_tests/surface_source_write/case-d01/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d01/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d01/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d01/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d01/surface_source_true.h5 index 8f8cd604dc..9a66315ffe 100644 Binary files a/tests/regression_tests/surface_source_write/case-d01/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d01/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d02/results_true.dat b/tests/regression_tests/surface_source_write/case-d02/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d02/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d02/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d02/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d02/surface_source_true.h5 index 3abc471e04..2910629425 100644 Binary files a/tests/regression_tests/surface_source_write/case-d02/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d02/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d03/results_true.dat b/tests/regression_tests/surface_source_write/case-d03/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d03/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d03/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d03/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d03/surface_source_true.h5 index 8435e8f17f..0af7160d4b 100644 Binary files a/tests/regression_tests/surface_source_write/case-d03/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d03/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d04/results_true.dat b/tests/regression_tests/surface_source_write/case-d04/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d04/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d04/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d04/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d04/surface_source_true.h5 index 6c45d92e61..90ab00748b 100644 Binary files a/tests/regression_tests/surface_source_write/case-d04/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d04/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d05/results_true.dat b/tests/regression_tests/surface_source_write/case-d05/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d05/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d05/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d05/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d05/surface_source_true.h5 index 24b04a862e..2f55216798 100644 Binary files a/tests/regression_tests/surface_source_write/case-d05/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d05/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d06/results_true.dat b/tests/regression_tests/surface_source_write/case-d06/results_true.dat index 7fb415cb15..26b9e30a3b 100644 --- a/tests/regression_tests/surface_source_write/case-d06/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d06/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.263843E-01 3.193920E-02 +9.288719E-01 6.877101E-03 diff --git a/tests/regression_tests/surface_source_write/case-d06/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d06/surface_source_true.h5 index 3eb95bef96..27227ad49c 100644 Binary files a/tests/regression_tests/surface_source_write/case-d06/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d06/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d07/results_true.dat b/tests/regression_tests/surface_source_write/case-d07/results_true.dat index 63ea1a64d4..5a4ea66898 100644 --- a/tests/regression_tests/surface_source_write/case-d07/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d07/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.756086E-01 4.639209E-02 +9.947197E-01 3.711779E-02 diff --git a/tests/regression_tests/surface_source_write/case-d07/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d07/surface_source_true.h5 index 0332f2dcfb..fd9f0dc572 100644 Binary files a/tests/regression_tests/surface_source_write/case-d07/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d07/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-d08/results_true.dat b/tests/regression_tests/surface_source_write/case-d08/results_true.dat index 63ea1a64d4..5a4ea66898 100644 --- a/tests/regression_tests/surface_source_write/case-d08/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-d08/results_true.dat @@ -1,2 +1,2 @@ k-combined: -9.756086E-01 4.639209E-02 +9.947197E-01 3.711779E-02 diff --git a/tests/regression_tests/surface_source_write/case-d08/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-d08/surface_source_true.h5 index 2525592045..fd9f0dc572 100644 Binary files a/tests/regression_tests/surface_source_write/case-d08/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-d08/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-e01/results_true.dat b/tests/regression_tests/surface_source_write/case-e01/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-e01/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-e01/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-e01/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-e01/surface_source_true.h5 index 3047519e8c..bbfbd152bc 100644 Binary files a/tests/regression_tests/surface_source_write/case-e01/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-e01/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-e02/results_true.dat b/tests/regression_tests/surface_source_write/case-e02/results_true.dat index 8979eb5547..d4d1d1e5ad 100644 --- a/tests/regression_tests/surface_source_write/case-e02/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-e02/results_true.dat @@ -1,2 +1,2 @@ k-combined: -5.169123E-02 9.144814E-03 +5.642735E-02 1.494035E-02 diff --git a/tests/regression_tests/surface_source_write/case-e02/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-e02/surface_source_true.h5 index 8061528533..bbfbd152bc 100644 Binary files a/tests/regression_tests/surface_source_write/case-e02/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-e02/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_source_write/case-e03/results_true.dat b/tests/regression_tests/surface_source_write/case-e03/results_true.dat index d793a7e421..ad927bdf30 100644 --- a/tests/regression_tests/surface_source_write/case-e03/results_true.dat +++ b/tests/regression_tests/surface_source_write/case-e03/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.752377E-02 6.773395E-03 +4.929000E-02 8.212396E-03 diff --git a/tests/regression_tests/surface_source_write/case-e03/surface_source_true.h5 b/tests/regression_tests/surface_source_write/case-e03/surface_source_true.h5 index becc9254a3..22e108745d 100644 Binary files a/tests/regression_tests/surface_source_write/case-e03/surface_source_true.h5 and b/tests/regression_tests/surface_source_write/case-e03/surface_source_true.h5 differ diff --git a/tests/regression_tests/surface_tally/results_true.dat b/tests/regression_tests/surface_tally/results_true.dat index 8b27fa1928..70d5cad2c6 100644 --- a/tests/regression_tests/surface_tally/results_true.dat +++ b/tests/regression_tests/surface_tally/results_true.dat @@ -1,52 +1,52 @@ mean,std. dev. -2.1200000e-02,1.8366636e-03 -7.4900000e-02,2.2083176e-03 -1.6220000e-01,2.8079253e-03 -6.4010000e-01,8.6838931e-03 -2.1000000e-03,3.7859389e-04 -5.6000000e-03,6.8637534e-04 -1.1700000e-02,1.4456832e-03 -4.1700000e-02,2.7041121e-03 -2.1200000e-02,1.8366636e-03 -7.4900000e-02,2.2083176e-03 -1.6220000e-01,2.8079253e-03 -6.4010000e-01,8.6838931e-03 -2.1000000e-03,3.7859389e-04 -5.6000000e-03,6.8637534e-04 -1.1700000e-02,1.4456832e-03 -4.1700000e-02,2.7041121e-03 -5.2000000e-03,5.9254629e-04 -3.9200000e-02,2.5508169e-03 -4.0200000e-02,1.9310331e-03 -4.1360000e-01,8.0072190e-03 -0.0000000e+00,0.0000000e+00 -1.9000000e-03,3.7859389e-04 +2.4100000e-02,2.1052844e-03 +6.7900000e-02,2.3211587e-03 +1.6860000e-01,4.4800794e-03 +6.4710000e-01,9.1826527e-03 +2.2000000e-03,3.8873013e-04 +5.5000000e-03,1.0979779e-03 +1.2500000e-02,1.5438048e-03 +4.4700000e-02,1.9035055e-03 +2.4100000e-02,2.1052844e-03 +6.7900000e-02,2.3211587e-03 +1.6860000e-01,4.4800794e-03 +6.4710000e-01,9.1826527e-03 +2.2000000e-03,3.8873013e-04 +5.5000000e-03,1.0979779e-03 +1.2500000e-02,1.5438048e-03 +4.4700000e-02,1.9035055e-03 +7.3000000e-03,9.8938814e-04 +3.6600000e-02,2.5086517e-03 +4.1600000e-02,2.4864075e-03 +4.2380000e-01,9.6087923e-03 1.0000000e-04,1.0000000e-04 -1.6400000e-02,1.2840907e-03 --5.2000000e-03,5.9254629e-04 --3.9200000e-02,2.5508169e-03 --4.0200000e-02,1.9310331e-03 --4.1360000e-01,8.0072190e-03 -0.0000000e+00,0.0000000e+00 --1.9000000e-03,3.7859389e-04 +1.5000000e-03,4.5338235e-04 +3.0000000e-04,1.5275252e-04 +1.7300000e-02,1.4609738e-03 +-7.3000000e-03,9.8938814e-04 +-3.6600000e-02,2.5086517e-03 +-4.1600000e-02,2.4864075e-03 +-4.2380000e-01,9.6087923e-03 -1.0000000e-04,1.0000000e-04 --1.6400000e-02,1.2840907e-03 -1.6000000e-02,2.1602469e-03 -3.5700000e-02,2.9441090e-03 -1.2200000e-01,3.5932035e-03 -2.2650000e-01,9.2463206e-03 +-1.5000000e-03,4.5338235e-04 +-3.0000000e-04,1.5275252e-04 +-1.7300000e-02,1.4609738e-03 +1.6800000e-02,1.5902481e-03 +3.1300000e-02,3.8094911e-03 +1.2700000e-01,5.0990195e-03 +2.2330000e-01,9.3631073e-03 2.1000000e-03,3.7859389e-04 -3.7000000e-03,8.1717671e-04 -1.1600000e-02,1.4772347e-03 -2.5300000e-02,1.9723083e-03 +4.0000000e-03,1.0540926e-03 +1.2200000e-02,1.6110728e-03 +2.7400000e-02,1.6613248e-03 0.0000000e+00,0.0000000e+00 --2.9700000e-02,2.4587711e-03 +-3.2000000e-02,1.5634719e-03 0.0000000e+00,0.0000000e+00 --3.5090000e-01,3.7161808e-03 +-3.5400000e-01,7.5938572e-03 0.0000000e+00,0.0000000e+00 --2.1000000e-03,4.8189441e-04 +-3.0000000e-03,6.4978629e-04 0.0000000e+00,0.0000000e+00 --2.1400000e-02,1.7397318e-03 +-2.1800000e-02,1.4892205e-03 0.0000000e+00,0.0000000e+00 0.0000000e+00,0.0000000e+00 0.0000000e+00,0.0000000e+00 diff --git a/tests/regression_tests/survival_biasing/results_true.dat b/tests/regression_tests/survival_biasing/results_true.dat index 7402722017..932414e98b 100644 --- a/tests/regression_tests/survival_biasing/results_true.dat +++ b/tests/regression_tests/survival_biasing/results_true.dat @@ -1,20 +1,20 @@ k-combined: -9.879232E-01 8.097582E-03 +9.517646E-01 1.303111E-02 tally 1: -4.295331E+01 -3.691096E+02 -1.802724E+01 -6.501934E+01 -2.193500E+00 -9.627609E-01 -1.893529E+00 -7.174104E-01 -4.902380E+00 -4.808570E+00 -3.418014E-02 -2.337353E-04 -3.667128E+08 -2.690758E+16 +4.164635E+01 +3.470110E+02 +1.724300E+01 +5.949580E+01 +2.124917E+00 +9.034789E-01 +1.844790E+00 +6.809026E-01 +4.784396E+00 +4.579552E+00 +3.348849E-02 +2.243613E-04 +3.573090E+08 +2.554338E+16 tally 2: -1.802724E+01 -6.501934E+01 +1.724300E+01 +5.949580E+01 diff --git a/tests/regression_tests/tallies/results_true.dat b/tests/regression_tests/tallies/results_true.dat index 3dda0f9b21..1d3aca4b07 100644 --- a/tests/regression_tests/tallies/results_true.dat +++ b/tests/regression_tests/tallies/results_true.dat @@ -1 +1 @@ -ddfbb0a6f5498eb8ff33bb10beb64e244b015861919eb4837bd82855e5fd87c3ff97dfa382d3d60afa81c48d9f857fba8e0b99263e7b35587f8adb75be1fc0ec \ No newline at end of file +d01c3accd5b4de2aa166a77df28cfe42f5738a44c2480752fcfae7564a507362fff006b6dffb7b1dfe248e14bacef0070cabacea5d75c5996653e5605f7c7384 \ No newline at end of file diff --git a/tests/regression_tests/tally_aggregation/results_true.dat b/tests/regression_tests/tally_aggregation/results_true.dat index 172adbfe13..ee6263373a 100644 --- a/tests/regression_tests/tally_aggregation/results_true.dat +++ b/tests/regression_tests/tally_aggregation/results_true.dat @@ -1,97 +1,97 @@ -[[1.6001087e-05 5.4190949e-04] - [3.2669968e-01 1.7730523e-01] - [1.8149266e-02 7.1525113e-01]], [[1.6239097e-05 5.7499676e-04] - [3.1268633e-01 1.7004165e-01] - [1.8873778e-02 7.0217885e-01]], [[1.6693071e-05 5.4106379e-04] - [3.3370208e-01 1.8051505e-01] - [1.9081306e-02 7.3647547e-01]], [[1.6725399e-05 5.1680146e-04] - [3.2854628e-01 1.7757185e-01] - [1.9529646e-02 7.1005198e-01]][[2.4751834e-07 4.3304565e-05] - [8.6840718e-03 4.3442535e-03] - [3.7054051e-04 6.5678133e-03]], [[4.0830852e-07 4.9612204e-05] - [1.2104241e-02 5.9708675e-03] - [7.1398189e-04 8.2408482e-03]], [[2.6546344e-07 2.5234256e-05] - [6.5083211e-03 3.2185071e-03] - [4.2935150e-04 5.1707774e-03]], [[2.7845203e-07 3.4453402e-05] - [3.3125427e-03 1.7749508e-03] - [6.0407731e-04 7.5353872e-03]][[1.0455251e-06 8.1938339e-04] - [1.1392765e+00 5.6434761e-01] - [1.4142831e-06 5.1213654e-01]], [[2.2009815e-06 1.0418935e-03] - [1.4422554e-01 1.0070647e-01] - [3.9488382e-05 7.9236390e-01]], [[1.4606612e-05 2.2374470e-04] - [1.2962842e-02 2.9268594e-02] - [3.1339824e-04 1.1056439e+00]], [[4.7805535e-05 8.9749934e-05] - [5.1694597e-03 1.1111105e-02] - [7.5279695e-02 4.5381305e-01]][[1.4955183e-08 1.1461548e-05] - [1.6454649e-02 8.1236707e-03] - [2.0028007e-08 6.8264819e-03]], [[1.6334486e-07 7.7617340e-05] - [2.1161584e-03 1.4078445e-03] - [1.4742097e-05 6.9350862e-03]], [[1.7444757e-07 1.9026095e-06] - [1.4084092e-04 2.0345990e-04] - [5.9546175e-06 8.6038812e-03]], [[5.6449127e-07 1.0110585e-06] - [5.9158873e-05 1.2485325e-04] - [1.0936497e-03 5.0836702e-03]][[0.2866239 0.2725595]], [[0.2729156 0.258831 ]], [[0.2920724 0.2755922]], [[0.287667 0.2703207]], [[0.035617 0.2232707]], [[0.0353082 0.2224423]], [[0.0370072 0.2288263]], [[0.0363348 0.219573 ]], [[0.0033013 0.2850034]], [[0.0032726 0.2771099]], [[0.0034234 0.2951295]], [[0.0032935 0.2778935]], [[0.0193227 0.1122647]], [[0.0200799 0.1144123]], [[0.0202971 0.1179836]], [[0.0207973 0.1203534]][[0.0086351 0.0061876]], [[0.0120688 0.0074831]], [[0.0064221 0.0035246]], [[0.0030483 0.0024267]], [[0.0009185 0.0033896]], [[0.0009223 0.0039584]], [[0.0010541 0.0038599]], [[0.0012934 0.0028331]], [[6.5126963e-05 2.8486593e-03]], [[7.1110242e-05 4.3424340e-03]], [[5.8911409e-05 2.4296178e-03]], [[8.4278765e-05 6.4182190e-03]], [[0.0003712 0.0020298]], [[0.0007152 0.0036115]], [[0.0004298 0.0019677]], [[0.0006046 0.0021965]][[2.0694650e-04] - [4.2868191e-01] - [1.3029457e-01]], [[1.9694048e-04] - [4.0809445e-01] - [1.2345525e-01]], [[2.1012645e-04] - [4.3670571e-01] - [1.3074883e-01]], [[2.0641548e-04] - [4.3014207e-01] - [1.2763930e-01]], [[0.0002584] - [0.0608867] - [0.1977426]], [[0.0003026] - [0.0602368] - [0.1972111]], [[0.0002509] - [0.0624699] - [0.2031126]], [[0.0002322] - [0.0613385] - [0.1943371]], [[5.9349736e-05] - [1.0506741e-02] - [2.7773865e-01]], [[5.7855564e-05] - [1.0389781e-02] - [2.6993483e-01]], [[6.1819700e-05] - [1.0910874e-02] - [2.8758020e-01]], [[5.9326317e-05] - [1.0424040e-02] - [2.7070367e-01]], [[3.3192167e-05] - [3.9295320e-03] - [1.2762462e-01]], [[3.3882691e-05] - [4.0069157e-03] - [1.3045143e-01]], [[3.4882103e-05] - [4.1306182e-03] - [1.3411514e-01]], [[3.5598508e-05] - [4.2134987e-03] - [1.3690156e-01]][[6.4505980e-06] - [9.6369034e-03] - [4.4700460e-03]], [[8.2880772e-06] - [1.3456171e-02] - [4.5368708e-03]], [[3.9384462e-06] - [7.1570638e-03] - [1.5629142e-03]], [[2.3565894e-06] - [3.4040401e-03] - [1.8956916e-03]], [[4.2806047e-05] - [1.1841015e-03] - [3.3058802e-03]], [[4.8905696e-05] - [1.0360139e-03] - [3.9298937e-03]], [[2.4911390e-05] - [1.2173305e-03] - [3.8114473e-03]], [[3.4347869e-05] - [1.5820360e-03] - [2.6824612e-03]], [[1.0809230e-06] - [1.0316180e-04] - [2.8475354e-03]], [[6.4150814e-07] - [1.1179425e-04] - [4.3415770e-03]], [[7.3848139e-07] - [9.3111666e-05] - [2.4285475e-03]], [[1.2349384e-06] - [1.7152843e-04] - [6.4164799e-03]], [[4.5871493e-07] - [5.4732075e-05] - [2.0627309e-03]], [[8.1649994e-07] - [9.7699188e-05] - [3.6803256e-03]], [[4.5174850e-07] - [5.3913784e-05] - [2.0133571e-03]], [[5.0962865e-07] - [6.0338032e-05] - [2.2773911e-03]] \ No newline at end of file +[[1.6242805e-05 6.2367673e-04] + [3.2895972e-01 1.7786452e-01] + [1.8044266e-02 7.0451122e-01]], [[1.6113947e-05 5.3572864e-04] + [3.1517504e-01 1.7132833e-01] + [1.8305682e-02 7.0072832e-01]], [[1.6472052e-05 5.5758006e-04] + [3.2362364e-01 1.7597163e-01] + [1.9107080e-02 7.2600440e-01]], [[1.6693277e-05 4.9204218e-04] + [3.2429262e-01 1.7600573e-01] + [1.9042489e-02 7.3053854e-01]][[2.9719061e-07 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b/tests/regression_tests/tally_arithmetic/results_true.dat @@ -1,49 +1,49 @@ -[2.04229e-07 1.28343e-13 1.79333e-04 1.12698e-10 1.89952e-07 1.51210e-07 - 1.66796e-04 1.32777e-04 6.13215e-03 3.85362e-09 3.14746e-03 1.97795e-09 - 5.70345e-03 4.54021e-03 2.92742e-03 2.33037e-03 2.10575e-07 1.28419e-13 - 1.84905e-04 1.12764e-10 1.89188e-07 1.50221e-07 1.66125e-04 1.31908e-04 - 6.32269e-03 3.85587e-09 3.24526e-03 1.97911e-09 5.68054e-03 4.51051e-03 - 2.91566e-03 2.31512e-03 1.96696e-07 1.26388e-13 1.72718e-04 1.10981e-10 - 1.91283e-07 1.53449e-07 1.67964e-04 1.34743e-04 5.90596e-03 3.79491e-09 - 3.03136e-03 1.94782e-09 5.74342e-03 4.60742e-03 2.94794e-03 2.36486e-03 - 2.06016e-07 1.35264e-13 1.80901e-04 1.18775e-10 2.05873e-07 1.65814e-07 - 1.80776e-04 1.45600e-04 6.18579e-03 4.06142e-09 3.17499e-03 2.08461e-09 - 6.18150e-03 4.97869e-03 3.17279e-03 2.55542e-03 2.36089e-03 4.46651e-05 - 1.02263e-02 1.93469e-04 1.18179e-04 2.62375e-05 5.11897e-04 1.13649e-04 - 2.56040e-02 4.84394e-04 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1.97911e-09 5.68054e-03 4.51051e-03 - 2.91566e-03 2.31512e-03 1.96696e-07 1.26388e-13 1.72718e-04 1.10981e-10 - 1.91283e-07 1.53449e-07 1.67964e-04 1.34743e-04 5.90596e-03 3.79491e-09 - 3.03136e-03 1.94782e-09 5.74342e-03 4.60742e-03 2.94794e-03 2.36486e-03 - 2.06016e-07 1.35264e-13 1.80901e-04 1.18775e-10 2.05873e-07 1.65814e-07 - 1.80776e-04 1.45600e-04 6.18579e-03 4.06142e-09 3.17499e-03 2.08461e-09 - 6.18150e-03 4.97869e-03 3.17279e-03 2.55542e-03 2.36089e-03 4.46651e-05 - 1.02263e-02 1.93469e-04 1.18179e-04 2.62375e-05 5.11897e-04 1.13649e-04 - 2.56040e-02 4.84394e-04 4.55595e-02 8.61927e-04 1.28165e-03 2.84546e-04 - 2.28056e-03 5.06320e-04 2.29877e-03 4.53056e-05 9.95724e-03 1.96244e-04 - 1.14803e-04 2.57898e-05 4.97276e-04 1.11710e-04 2.49302e-02 4.91340e-04 - 4.43606e-02 8.74289e-04 1.24504e-03 2.79691e-04 2.21542e-03 4.97680e-04 - 2.31940e-03 4.34238e-05 1.00466e-02 1.88093e-04 1.17620e-04 2.69280e-05 - 5.09479e-04 1.16640e-04 2.51540e-02 4.70932e-04 4.47588e-02 8.37974e-04 - 1.27560e-03 2.92034e-04 2.26979e-03 5.19644e-04 2.19212e-03 4.53914e-05 - 9.49530e-03 1.96615e-04 1.09609e-04 2.41615e-05 4.74778e-04 1.04657e-04 - 2.37736e-02 4.92271e-04 4.23026e-02 8.75944e-04 1.18871e-03 2.62032e-04 - 2.11519e-03 4.66257e-04][0.0057 0.00454 0.00293 0.00233 0.00568 0.00451 0.00292 0.00232 0.00574 - 0.00461 0.00295 0.00236 0.00618 0.00498 0.00317 0.00256 0.00128 0.00028 - 0.00228 0.00051 0.00125 0.00028 0.00222 0.0005 0.00128 0.00029 0.00227 - 0.00052 0.00119 0.00026 0.00212 0.00047][0.00018 0.00017 0.00315 0.00293 0.00018 0.00017 0.00325 0.00292 0.00017 - 0.00017 0.00303 0.00295 0.00018 0.00018 0.00317 0.00317 0.01023 0.00051 - 0.04556 0.00228 0.00996 0.0005 0.04436 0.00222 0.01005 0.00051 0.04476 - 0.00227 0.0095 0.00047 0.0423 0.00212][0.00293 0.00292 0.00295 0.00317 0.00228 0.00222 0.00227 0.00212] \ No newline at end of file +[2.29467e-07 1.47622e-13 2.02646e-04 1.30367e-10 2.20704e-07 1.76624e-07 + 1.94907e-04 1.55980e-04 6.32267e-03 4.06754e-09 3.26873e-03 2.10286e-09 + 6.08121e-03 4.86666e-03 3.14390e-03 2.51599e-03 1.89223e-07 1.06256e-13 + 1.67106e-04 9.38364e-11 1.53300e-07 1.20220e-07 1.35382e-04 1.06168e-04 + 5.21380e-03 2.92775e-09 2.69546e-03 1.51361e-09 4.22399e-03 3.31252e-03 + 2.18374e-03 1.71253e-03 2.21146e-07 1.41349e-13 1.95297e-04 1.24828e-10 + 2.11844e-07 1.69398e-07 1.87083e-04 1.49598e-04 6.09339e-03 3.89470e-09 + 3.15020e-03 2.01351e-09 5.83710e-03 4.66754e-03 3.01770e-03 2.41305e-03 + 1.92872e-07 1.05908e-13 1.70328e-04 9.35293e-11 1.59466e-07 1.25399e-07 + 1.40827e-04 1.10741e-04 5.31433e-03 2.91817e-09 2.74744e-03 1.50865e-09 + 4.39388e-03 3.45520e-03 2.27158e-03 1.78629e-03 2.44601e-03 4.71663e-05 + 1.09430e-02 2.11013e-04 1.23573e-04 2.76181e-05 5.52841e-04 1.23558e-04 + 2.71755e-02 5.24023e-04 4.76200e-02 9.18253e-04 1.37291e-03 3.06841e-04 + 2.40577e-03 5.37681e-04 2.29014e-03 4.44674e-05 1.02456e-02 1.98938e-04 + 1.12524e-04 2.48126e-05 5.03411e-04 1.11007e-04 2.54438e-02 4.94038e-04 + 4.45855e-02 8.65710e-04 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4.66754e-03 3.01770e-03 2.41305e-03 + 1.92872e-07 1.05908e-13 1.70328e-04 9.35293e-11 1.59466e-07 1.25399e-07 + 1.40827e-04 1.10741e-04 5.31433e-03 2.91817e-09 2.74744e-03 1.50865e-09 + 4.39388e-03 3.45520e-03 2.27158e-03 1.78629e-03 2.44601e-03 4.71663e-05 + 1.09430e-02 2.11013e-04 1.23573e-04 2.76181e-05 5.52841e-04 1.23558e-04 + 2.71755e-02 5.24023e-04 4.76200e-02 9.18253e-04 1.37291e-03 3.06841e-04 + 2.40577e-03 5.37681e-04 2.29014e-03 4.44674e-05 1.02456e-02 1.98938e-04 + 1.12524e-04 2.48126e-05 5.03411e-04 1.11007e-04 2.54438e-02 4.94038e-04 + 4.45855e-02 8.65710e-04 1.25016e-03 2.75671e-04 2.19067e-03 4.83061e-04 + 2.38500e-03 4.58053e-05 1.06700e-02 2.04924e-04 1.22899e-04 2.95267e-05 + 5.49826e-04 1.32097e-04 2.64977e-02 5.08903e-04 4.64323e-02 8.91758e-04 + 1.36542e-03 3.28045e-04 2.39265e-03 5.74839e-04 2.17094e-03 4.21772e-05 + 9.71236e-03 1.88693e-04 1.09358e-04 2.46984e-05 4.89245e-04 1.10496e-04 + 2.41194e-02 4.68594e-04 4.22648e-02 8.21124e-04 1.21498e-03 2.74402e-04 + 2.12902e-03 4.80839e-04][0.00608 0.00487 0.00314 0.00252 0.00422 0.00331 0.00218 0.00171 0.00584 + 0.00467 0.00302 0.00241 0.00439 0.00346 0.00227 0.00179 0.00137 0.00031 + 0.00241 0.00054 0.00125 0.00028 0.00219 0.00048 0.00137 0.00033 0.00239 + 0.00057 0.00121 0.00027 0.00213 0.00048][0.0002 0.00019 0.00327 0.00314 0.00017 0.00014 0.0027 0.00218 0.0002 + 0.00019 0.00315 0.00302 0.00017 0.00014 0.00275 0.00227 0.01094 0.00055 + 0.04762 0.00241 0.01025 0.0005 0.04459 0.00219 0.01067 0.00055 0.04643 + 0.00239 0.00971 0.00049 0.04226 0.00213][0.00314 0.00218 0.00302 0.00227 0.00241 0.00219 0.00239 0.00213] \ No newline at end of file diff --git a/tests/regression_tests/tally_assumesep/results_true.dat b/tests/regression_tests/tally_assumesep/results_true.dat index 9d7cbf9c3d..c9ccf09282 100644 --- a/tests/regression_tests/tally_assumesep/results_true.dat +++ b/tests/regression_tests/tally_assumesep/results_true.dat @@ -1,11 +1,11 @@ k-combined: -5.683578E-01 1.129170E-02 +6.268465E-01 1.154810E-02 tally 1: -6.753950E+00 -9.188305E+00 +7.828708E+00 +1.230478E+01 tally 2: -2.278558E-01 -1.052944E-02 +2.582239E-01 +1.360117E-02 tally 3: -1.179091E+01 -2.795539E+01 +1.339335E+01 +3.663458E+01 diff --git a/tests/regression_tests/tally_nuclides/results_true.dat b/tests/regression_tests/tally_nuclides/results_true.dat index 7f9641fc8f..93a0e03fb5 100644 --- a/tests/regression_tests/tally_nuclides/results_true.dat +++ b/tests/regression_tests/tally_nuclides/results_true.dat @@ -1,28 +1,28 @@ k-combined: -1.132463E+00 5.721067E-02 +9.732610E-01 1.400780E-02 tally 1: -7.310528E+00 -1.080411E+01 -1.664215E+00 -5.567756E-01 -1.609340E+00 -5.205634E-01 -5.646313E+00 -6.459724E+00 -7.310528E+00 -1.080411E+01 -1.664215E+00 -5.567756E-01 -1.609340E+00 -5.205634E-01 -5.646313E+00 -6.459724E+00 +7.123025E+00 +1.021136E+01 +1.619905E+00 +5.258592E-01 +1.561322E+00 +4.881841E-01 +5.503120E+00 +6.105683E+00 +7.123025E+00 +1.021136E+01 +1.619905E+00 +5.258592E-01 +1.561322E+00 +4.881841E-01 +5.503120E+00 +6.105683E+00 tally 2: -7.310528E+00 -1.080411E+01 -1.664215E+00 -5.567756E-01 -1.609340E+00 -5.205634E-01 -5.646313E+00 -6.459724E+00 +7.123025E+00 +1.021136E+01 +1.619905E+00 +5.258592E-01 +1.561322E+00 +4.881841E-01 +5.503120E+00 +6.105683E+00 diff --git a/tests/regression_tests/tally_slice_merge/results_true.dat b/tests/regression_tests/tally_slice_merge/results_true.dat index 58b15fc18d..4b2cbdf1ad 100644 --- a/tests/regression_tests/tally_slice_merge/results_true.dat +++ b/tests/regression_tests/tally_slice_merge/results_true.dat @@ -1,45 +1,45 @@ cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 0.00e+00 6.25e-01 U235 fission 1.75e-01 1.20e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 0.00e+00 6.25e-01 U235 nu-fission 4.26e-01 2.92e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 0.00e+00 6.25e-01 U238 fission 2.41e-07 1.61e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 0.00e+00 6.25e-01 U238 nu-fission 6.00e-07 4.01e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 6.25e-01 2.00e+07 U235 fission 2.89e-02 2.07e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 6.25e-01 2.00e+07 U235 nu-fission 7.07e-02 5.06e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 6.25e-01 2.00e+07 U238 fission 1.41e-02 5.76e-04 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 6.25e-01 2.00e+07 U238 nu-fission 3.95e-02 1.90e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 0.00e+00 6.25e-01 U235 fission 1.51e-01 1.17e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 0.00e+00 6.25e-01 U235 nu-fission 3.69e-01 2.86e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 0.00e+00 6.25e-01 U238 fission 2.07e-07 1.47e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 0.00e+00 6.25e-01 U238 nu-fission 5.17e-07 3.66e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 6.25e-01 2.00e+07 U235 fission 2.57e-02 2.43e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 6.25e-01 2.00e+07 U235 nu-fission 6.30e-02 5.92e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 6.25e-01 2.00e+07 U238 fission 1.47e-02 1.41e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 27 6.25e-01 2.00e+07 U238 nu-fission 4.12e-02 4.02e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. -0 21 0.00e+00 6.25e-01 U235 fission 1.75e-01 1.20e-02 -1 21 0.00e+00 6.25e-01 U235 nu-fission 4.26e-01 2.92e-02 -2 21 0.00e+00 6.25e-01 U238 fission 2.41e-07 1.61e-08 -3 21 0.00e+00 6.25e-01 U238 nu-fission 6.00e-07 4.01e-08 -4 21 6.25e-01 2.00e+07 U235 fission 2.89e-02 2.07e-03 -5 21 6.25e-01 2.00e+07 U235 nu-fission 7.07e-02 5.06e-03 -6 21 6.25e-01 2.00e+07 U238 fission 1.41e-02 5.76e-04 -7 21 6.25e-01 2.00e+07 U238 nu-fission 3.95e-02 1.90e-03 -8 27 0.00e+00 6.25e-01 U235 fission 1.51e-01 1.17e-02 -9 27 0.00e+00 6.25e-01 U235 nu-fission 3.69e-01 2.86e-02 -10 27 0.00e+00 6.25e-01 U238 fission 2.07e-07 1.47e-08 -11 27 0.00e+00 6.25e-01 U238 nu-fission 5.17e-07 3.66e-08 -12 27 6.25e-01 2.00e+07 U235 fission 2.57e-02 2.43e-03 -13 27 6.25e-01 2.00e+07 U235 nu-fission 6.30e-02 5.92e-03 -14 27 6.25e-01 2.00e+07 U238 fission 1.47e-02 1.41e-03 -15 27 6.25e-01 2.00e+07 U238 nu-fission 4.12e-02 4.02e-03 +0 21 0.00e+00 6.25e-01 U235 fission 1.93e-01 1.92e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 0.00e+00 6.25e-01 U235 nu-fission 4.70e-01 4.67e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 0.00e+00 6.25e-01 U238 fission 2.65e-07 2.60e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 0.00e+00 6.25e-01 U238 nu-fission 6.60e-07 6.47e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 6.25e-01 2.00e+07 U235 fission 3.39e-02 1.53e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 6.25e-01 2.00e+07 U235 nu-fission 8.30e-02 3.75e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 6.25e-01 2.00e+07 U238 fission 1.70e-02 2.01e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 6.25e-01 2.00e+07 U238 nu-fission 4.76e-02 6.12e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 0.00e+00 6.25e-01 U235 fission 7.61e-02 5.84e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 0.00e+00 6.25e-01 U235 nu-fission 1.85e-01 1.42e-02 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 0.00e+00 6.25e-01 U238 fission 1.06e-07 7.62e-09 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 0.00e+00 6.25e-01 U238 nu-fission 2.64e-07 1.90e-08 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 6.25e-01 2.00e+07 U235 fission 1.69e-02 1.34e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 6.25e-01 2.00e+07 U235 nu-fission 4.15e-02 3.29e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 6.25e-01 2.00e+07 U238 fission 1.10e-02 1.69e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 27 6.25e-01 2.00e+07 U238 nu-fission 3.13e-02 5.35e-03 cell energy low [eV] energy high [eV] nuclide score mean std. dev. +0 21 0.00e+00 6.25e-01 U235 fission 1.93e-01 1.92e-02 +1 21 0.00e+00 6.25e-01 U235 nu-fission 4.70e-01 4.67e-02 +2 21 0.00e+00 6.25e-01 U238 fission 2.65e-07 2.60e-08 +3 21 0.00e+00 6.25e-01 U238 nu-fission 6.60e-07 6.47e-08 +4 21 6.25e-01 2.00e+07 U235 fission 3.39e-02 1.53e-03 +5 21 6.25e-01 2.00e+07 U235 nu-fission 8.30e-02 3.75e-03 +6 21 6.25e-01 2.00e+07 U238 fission 1.70e-02 2.01e-03 +7 21 6.25e-01 2.00e+07 U238 nu-fission 4.76e-02 6.12e-03 +8 27 0.00e+00 6.25e-01 U235 fission 7.61e-02 5.84e-03 +9 27 0.00e+00 6.25e-01 U235 nu-fission 1.85e-01 1.42e-02 +10 27 0.00e+00 6.25e-01 U238 fission 1.06e-07 7.62e-09 +11 27 0.00e+00 6.25e-01 U238 nu-fission 2.64e-07 1.90e-08 +12 27 6.25e-01 2.00e+07 U235 fission 1.69e-02 1.34e-03 +13 27 6.25e-01 2.00e+07 U235 nu-fission 4.15e-02 3.29e-03 +14 27 6.25e-01 2.00e+07 U238 fission 1.10e-02 1.69e-03 +15 27 6.25e-01 2.00e+07 U238 nu-fission 3.13e-02 5.35e-03 sum(distribcell) energy low [eV] energy high [eV] nuclide score mean std. dev. 0 (0, 100, 2000, 30000) 0.00e+00 6.25e-01 U235 fission 0.00e+00 0.00e+00 1 (0, 100, 2000, 30000) 0.00e+00 6.25e-01 U235 nu-fission 0.00e+00 0.00e+00 2 (0, 100, 2000, 30000) 0.00e+00 6.25e-01 U238 fission 0.00e+00 0.00e+00 3 (0, 100, 2000, 30000) 0.00e+00 6.25e-01 U238 nu-fission 0.00e+00 0.00e+00 -4 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U235 fission 9.53e-07 9.53e-07 -5 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U235 nu-fission 2.37e-06 2.37e-06 -6 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U238 fission 1.25e-08 1.25e-08 -7 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U238 nu-fission 3.15e-08 3.15e-08 +4 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U235 fission 0.00e+00 0.00e+00 +5 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U235 nu-fission 0.00e+00 0.00e+00 +6 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U238 fission 0.00e+00 0.00e+00 +7 (0, 100, 2000, 30000) 6.25e-01 2.00e+07 U238 nu-fission 0.00e+00 0.00e+00 8 (500, 5000, 50000) 0.00e+00 6.25e-01 U235 fission 0.00e+00 0.00e+00 9 (500, 5000, 50000) 0.00e+00 6.25e-01 U235 nu-fission 0.00e+00 0.00e+00 10 (500, 5000, 50000) 0.00e+00 6.25e-01 U238 fission 0.00e+00 0.00e+00 @@ -49,19 +49,19 @@ 14 (500, 5000, 50000) 6.25e-01 2.00e+07 U238 fission 0.00e+00 0.00e+00 15 (500, 5000, 50000) 6.25e-01 2.00e+07 U238 nu-fission 0.00e+00 0.00e+00 sum(mesh) energy low [eV] energy high [eV] nuclide score mean std. dev. -0 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U235 fission 6.73e-03 3.04e-03 -1 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U235 nu-fission 1.64e-02 7.40e-03 -2 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U238 fission 8.80e-09 3.84e-09 -3 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U238 nu-fission 2.19e-08 9.56e-09 -4 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U235 fission 9.89e-04 3.53e-04 -5 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U235 nu-fission 2.42e-03 8.60e-04 -6 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U238 fission 5.01e-04 2.13e-04 -7 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U238 nu-fission 1.36e-03 5.86e-04 -8 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U235 fission 1.63e-02 4.21e-03 -9 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U235 nu-fission 3.98e-02 1.02e-02 -10 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U238 fission 2.28e-08 5.90e-09 -11 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U238 nu-fission 5.67e-08 1.47e-08 -12 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U235 fission 1.79e-03 4.31e-04 -13 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U235 nu-fission 4.37e-03 1.05e-03 -14 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U238 fission 7.51e-04 2.51e-04 -15 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U238 nu-fission 2.02e-03 6.71e-04 +0 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U235 fission 1.94e-03 1.03e-03 +1 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U235 nu-fission 4.74e-03 2.50e-03 +2 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U238 fission 2.74e-09 1.42e-09 +3 ((1, 1), (1, 2)) 0.00e+00 6.25e-01 U238 nu-fission 6.83e-09 3.53e-09 +4 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U235 fission 9.02e-04 3.69e-04 +5 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U235 nu-fission 2.24e-03 9.12e-04 +6 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U238 fission 1.44e-03 8.42e-04 +7 ((1, 1), (1, 2)) 6.25e-01 2.00e+07 U238 nu-fission 4.37e-03 2.64e-03 +8 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U235 fission 1.27e-02 2.76e-03 +9 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U235 nu-fission 3.09e-02 6.72e-03 +10 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U238 fission 1.70e-08 3.57e-09 +11 ((2, 1), (2, 2)) 0.00e+00 6.25e-01 U238 nu-fission 4.25e-08 8.90e-09 +12 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U235 fission 1.43e-03 1.69e-04 +13 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U235 nu-fission 3.52e-03 4.20e-04 +14 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U238 fission 1.37e-03 2.98e-04 +15 ((2, 1), (2, 2)) 6.25e-01 2.00e+07 U238 nu-fission 4.16e-03 1.08e-03 diff --git a/tests/regression_tests/torus/results_true.dat b/tests/regression_tests/torus/results_true.dat index 42fb209cce..84cd3c7a44 100644 --- a/tests/regression_tests/torus/results_true.dat +++ b/tests/regression_tests/torus/results_true.dat @@ -1,2 +1,2 @@ k-combined: -7.667201E-01 1.136882E-02 +7.666453E-01 1.478848E-02 diff --git a/tests/regression_tests/trace/results_true.dat b/tests/regression_tests/trace/results_true.dat index bbf03de943..97b997ae6b 100644 --- a/tests/regression_tests/trace/results_true.dat +++ b/tests/regression_tests/trace/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 diff --git a/tests/regression_tests/track_output/results_true.dat b/tests/regression_tests/track_output/results_true.dat index 148b54a30b..205ac3eecb 100644 --- a/tests/regression_tests/track_output/results_true.dat +++ b/tests/regression_tests/track_output/results_true.dat @@ -143,76 +143,74 @@ neutron [((-9.469716e-01, -2.580266e-01, 1.414357e-01), (1.438873e-01, 2.365819e ((-3.920090e+00, -9.211794e-01, 2.908406e+00), (9.094673e-01, -3.659267e-01, -1.974002e-01), 9.547085e+00, 1.260840e-07, 1.000000e+00, 23, 2387, 1) ((-3.729948e+00, -9.976834e-01, 2.867135e+00), (-2.916959e-01, -6.494657e-01, -7.022164e-01), 8.590591e+00, 1.750036e-07, 1.000000e+00, 23, 2387, 1) ((-3.744933e+00, -1.031047e+00, 2.831062e+00), (-2.916959e-01, -6.494657e-01, -7.022164e-01), 8.590591e+00, 1.876753e-07, 0.000000e+00, 23, 2387, 1)] -neutron [((6.474155e+00, -5.192870e+00, 5.413003e+00), (-9.112559e-01, 3.950037e-01, 1.165536e-01), 2.052226e+06, 4.450859e-05, 1.000000e+00, 21, 2367, 2) - ((6.037250e+00, -5.003484e+00, 5.468885e+00), (-9.112559e-01, 3.950037e-01, 1.165536e-01), 2.052226e+06, 4.450883e-05, 1.000000e+00, 22, 2367, 3) - ((5.942573e+00, -4.962444e+00, 5.480995e+00), (-9.112559e-01, 3.950037e-01, 1.165536e-01), 2.052226e+06, 4.450889e-05, 1.000000e+00, 23, 2367, 1) - ((5.861800e+00, -4.927431e+00, 5.491326e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450893e-05, 1.000000e+00, 23, 2367, 1) - ((5.725160e+00, -4.971424e+00, 5.491002e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450903e-05, 1.000000e+00, 23, 2366, 1) - ((5.494150e+00, -5.045802e+00, 5.490454e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450919e-05, 1.000000e+00, 22, 2366, 3) - ((5.392865e+00, -5.078412e+00, 5.490213e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450927e-05, 1.000000e+00, 21, 2366, 2) - ((4.612759e+00, -5.329579e+00, 5.488362e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450982e-05, 1.000000e+00, 22, 2366, 3) - ((4.511474e+00, -5.362189e+00, 5.488121e+00), (-9.518772e-01, -3.064714e-01, -2.259335e-03), 1.141417e+06, 4.450989e-05, 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((7.207392e+00, -1.107494e+01, 4.532123e+00), (9.936512e-01, 4.529367e-02, -1.029847e-01), 8.142074e-02, 5.333706e-05, 1.000000e+00, 23, 2311, 1) + ((7.252245e+00, -1.107290e+01, 4.527474e+00), (9.936512e-01, 4.529367e-02, -1.029847e-01), 8.142074e-02, 5.345144e-05, 0.000000e+00, 23, 2311, 1)] diff --git a/tests/regression_tests/translation/results_true.dat b/tests/regression_tests/translation/results_true.dat index f832aa2964..6e03d2224f 100644 --- a/tests/regression_tests/translation/results_true.dat +++ b/tests/regression_tests/translation/results_true.dat @@ -1,2 +1,2 @@ k-combined: -4.087580E-01 4.466279E-03 +4.076610E-01 6.454244E-03 diff --git a/tests/regression_tests/trigger_batch_interval/results_true.dat b/tests/regression_tests/trigger_batch_interval/results_true.dat index 0571d6c4f9..92fa99d87a 100644 --- a/tests/regression_tests/trigger_batch_interval/results_true.dat +++ b/tests/regression_tests/trigger_batch_interval/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.767929E-01 5.327552E-03 +9.863217E-01 6.499354E-03 tally 1: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 tally 2: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 diff --git a/tests/regression_tests/trigger_no_batch_interval/results_true.dat b/tests/regression_tests/trigger_no_batch_interval/results_true.dat index 0571d6c4f9..92fa99d87a 100644 --- a/tests/regression_tests/trigger_no_batch_interval/results_true.dat +++ b/tests/regression_tests/trigger_no_batch_interval/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.767929E-01 5.327552E-03 +9.863217E-01 6.499354E-03 tally 1: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 tally 2: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 diff --git a/tests/regression_tests/trigger_no_status/results_true.dat b/tests/regression_tests/trigger_no_status/results_true.dat index fb6c0086ab..a62e1b3fe5 100644 --- a/tests/regression_tests/trigger_no_status/results_true.dat +++ b/tests/regression_tests/trigger_no_status/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.682315E-01 3.302924E-03 +9.858966E-01 1.500542E-02 tally 1: -7.046510E+00 -9.932168E+00 -1.591675E+00 -5.067777E-01 -1.541572E+00 -4.753743E-01 -5.454835E+00 -5.951990E+00 -7.046510E+00 -9.932168E+00 -1.591675E+00 -5.067777E-01 -1.541572E+00 -4.753743E-01 -5.454835E+00 -5.951990E+00 +7.081828E+00 +1.003709E+01 +1.607382E+00 +5.171386E-01 +1.559242E+00 +4.866413E-01 +5.474447E+00 +5.997737E+00 +7.081828E+00 +1.003709E+01 +1.607382E+00 +5.171386E-01 +1.559242E+00 +4.866413E-01 +5.474447E+00 +5.997737E+00 tally 2: -7.046510E+00 -9.932168E+00 -1.591675E+00 -5.067777E-01 -1.541572E+00 -4.753743E-01 -5.454835E+00 -5.951990E+00 +7.081828E+00 +1.003709E+01 +1.607382E+00 +5.171386E-01 +1.559242E+00 +4.866413E-01 +5.474447E+00 +5.997737E+00 diff --git a/tests/regression_tests/trigger_statepoint_restart/inputs_true.dat b/tests/regression_tests/trigger_statepoint_restart/inputs_true.dat index 01755ad8bc..59a8297009 100644 --- a/tests/regression_tests/trigger_statepoint_restart/inputs_true.dat +++ b/tests/regression_tests/trigger_statepoint_restart/inputs_true.dat @@ -16,7 +16,7 @@ 15 10 - 0.003 + 0.002 std_dev diff --git a/tests/regression_tests/trigger_statepoint_restart/results_true.dat b/tests/regression_tests/trigger_statepoint_restart/results_true.dat index 3e6619d74d..3cb1e230dd 100644 --- a/tests/regression_tests/trigger_statepoint_restart/results_true.dat +++ b/tests/regression_tests/trigger_statepoint_restart/results_true.dat @@ -1,5 +1,5 @@ k-combined: -3.014717E-01 2.864764E-03 +2.948661E-01 1.949846E-03 tally 1: -8.946107E+01 -7.281263E+02 +5.515170E+01 +4.349007E+02 diff --git a/tests/regression_tests/trigger_statepoint_restart/test.py b/tests/regression_tests/trigger_statepoint_restart/test.py index 8144c1d0b0..b242f7f1cf 100644 --- a/tests/regression_tests/trigger_statepoint_restart/test.py +++ b/tests/regression_tests/trigger_statepoint_restart/test.py @@ -29,7 +29,7 @@ def model(): settings.inactive = 10 settings.particles = 400 # Choose a sufficiently low threshold to enable use of trigger - settings.keff_trigger = {'type': 'std_dev', 'threshold': 0.003} + settings.keff_trigger = {'type': 'std_dev', 'threshold': 0.002} settings.trigger_max_batches = 1000 settings.trigger_batch_interval = 1 settings.trigger_active = True @@ -41,10 +41,10 @@ def model(): tallies = openmc.Tallies([t]) # Put it all together - model = openmc.model.Model(materials=materials, - geometry=geometry, - settings=settings, - tallies=tallies) + model = openmc.Model(materials=materials, + geometry=geometry, + settings=settings, + tallies=tallies) return model diff --git a/tests/regression_tests/trigger_tallies/results_true.dat b/tests/regression_tests/trigger_tallies/results_true.dat index 0571d6c4f9..92fa99d87a 100644 --- a/tests/regression_tests/trigger_tallies/results_true.dat +++ b/tests/regression_tests/trigger_tallies/results_true.dat @@ -1,28 +1,28 @@ k-combined: -9.767929E-01 5.327552E-03 +9.863217E-01 6.499354E-03 tally 1: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 tally 2: -1.405471E+01 -1.976444E+01 -3.186139E+00 -1.015515E+00 -3.088643E+00 -9.542994E-01 -1.086857E+01 -1.182011E+01 +1.423436E+01 +2.027258E+01 +3.223740E+00 +1.039872E+00 +3.125016E+00 +9.771709E-01 +1.101062E+01 +1.212977E+01 diff --git a/tests/regression_tests/triso/results_true.dat b/tests/regression_tests/triso/results_true.dat index fa1842e547..d9850e410f 100644 --- a/tests/regression_tests/triso/results_true.dat +++ b/tests/regression_tests/triso/results_true.dat @@ -1,2 +1,2 @@ k-combined: -1.716873E+00 5.266107E-02 +1.604832E+00 2.031393E-03 diff --git a/tests/regression_tests/uniform_fs/results_true.dat b/tests/regression_tests/uniform_fs/results_true.dat index 46654b49b4..f7ceecfb73 100644 --- a/tests/regression_tests/uniform_fs/results_true.dat +++ b/tests/regression_tests/uniform_fs/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.685309E-01 1.861720E-03 +3.675645E-01 4.342970E-03 diff --git a/tests/regression_tests/universe/results_true.dat b/tests/regression_tests/universe/results_true.dat index bbf03de943..97b997ae6b 100644 --- a/tests/regression_tests/universe/results_true.dat +++ b/tests/regression_tests/universe/results_true.dat @@ -1,2 +1,2 @@ k-combined: -3.070134E-01 3.900396E-03 +2.940336E-01 7.338463E-04 diff --git a/tests/regression_tests/unstructured_mesh/test.py b/tests/regression_tests/unstructured_mesh/test.py index 0082198dde..7607531d8b 100644 --- a/tests/regression_tests/unstructured_mesh/test.py +++ b/tests/regression_tests/unstructured_mesh/test.py @@ -256,7 +256,7 @@ for i, (lib, estimator, ext_geom, holes) in enumerate(product(*param_values)): def test_unstructured_mesh_tets(model, test_opts): # skip the test if the library is not enabled if test_opts['library'] == 'moab' and not openmc.lib._dagmc_enabled(): - pytest.skip("DAGMC (and MOAB) mesh not enbaled in this build.") + pytest.skip("DAGMC (and MOAB) mesh not enabled in this build.") if test_opts['library'] == 'libmesh' and not openmc.lib._libmesh_enabled(): pytest.skip("LibMesh is not enabled in this build.") diff --git a/tests/regression_tests/unstructured_mesh/test_mesh_dagmc_tets.vtk b/tests/regression_tests/unstructured_mesh/test_mesh_dagmc_tets.vtk new file mode 100644 index 0000000000..2ddd228cf1 --- /dev/null +++ b/tests/regression_tests/unstructured_mesh/test_mesh_dagmc_tets.vtk @@ -0,0 +1,159 @@ +# vtk DataFile Version 2.0 +made_with_cad_to_dagmc_package, Created by Gmsh 4.12.1 +ASCII +DATASET UNSTRUCTURED_GRID +POINTS 14 double +-0.5 -0.5 0.5 +-0.5 -0.5 -0.5 +-0.5 0.5 0.5 +-0.5 0.5 -0.5 +0.5 -0.5 0.5 +0.5 -0.5 -0.5 +0.5 0.5 0.5 +0.5 0.5 -0.5 +-0.5 0 0 +0.5 0 0 +0 -0.5 0 +0 0.5 0 +0 0 -0.5 +0 0 0.5 + +CELLS 68 268 +1 0 +1 1 +1 2 +1 3 +1 4 +1 5 +1 6 +1 7 +2 1 0 +2 0 2 +2 3 2 +2 1 3 +2 5 4 +2 4 6 +2 7 6 +2 5 7 +2 1 5 +2 0 4 +2 3 7 +2 2 6 +3 1 0 8 +3 0 2 8 +3 3 1 8 +3 2 3 8 +3 5 9 4 +3 4 9 6 +3 7 9 5 +3 6 9 7 +3 0 1 10 +3 4 0 10 +3 1 5 10 +3 5 4 10 +3 2 11 3 +3 6 11 2 +3 3 11 7 +3 7 11 6 +3 1 3 12 +3 5 1 12 +3 3 7 12 +3 7 5 12 +3 0 13 2 +3 4 13 0 +3 2 13 6 +3 6 13 4 +4 13 8 12 10 +4 11 8 12 13 +4 12 11 13 9 +4 10 12 13 9 +4 12 3 11 7 +4 13 2 8 0 +4 8 12 1 3 +4 11 3 8 2 +4 10 8 1 0 +4 0 10 13 4 +4 1 12 10 5 +4 11 2 13 6 +4 4 9 13 6 +4 6 9 11 7 +4 10 9 4 5 +4 7 9 12 5 +4 3 8 12 11 +4 1 12 8 10 +4 8 11 2 13 +4 10 13 8 0 +4 13 10 9 4 +4 11 13 9 6 +4 12 11 9 7 +4 9 10 12 5 + +CELL_TYPES 68 +1 +1 +1 +1 +1 +1 +1 +1 +3 +3 +3 +3 +3 +3 +3 +3 +3 +3 +3 +3 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +5 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 +10 diff --git a/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat index 448b4b145c..5fa6505ddf 100644 --- a/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat @@ -227,7 +227,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true naive diff --git a/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat index d82aa6fae8..ceb89e6e34 100644 --- a/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat @@ -227,7 +227,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat index 9e4b21d27b..c7691e950c 100644 --- a/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat @@ -227,7 +227,7 @@ 0.0 0.0 0.0 30.0 30.0 30.0 - True + true diff --git a/tests/regression_tests/white_plane/results_true.dat b/tests/regression_tests/white_plane/results_true.dat index 6f1d064eb3..ffb19491dd 100644 --- a/tests/regression_tests/white_plane/results_true.dat +++ b/tests/regression_tests/white_plane/results_true.dat @@ -1,2 +1,2 @@ k-combined: -2.279719E+00 5.380792E-03 +2.274312E+00 4.223342E-03 diff --git a/tests/testing_harness.py b/tests/testing_harness.py index 11ced5b38a..1ad91b7a89 100644 --- a/tests/testing_harness.py +++ b/tests/testing_harness.py @@ -68,7 +68,7 @@ class TestHarness: if config['mpi']: mpi_args = [config['mpiexec'], '-n', config['mpi_np']] openmc.run(openmc_exec=config['exe'], mpi_args=mpi_args, - event_based=config['event']) + event_based=config['event']) else: openmc.run(openmc_exec=config['exe'], event_based=config['event']) @@ -305,9 +305,12 @@ class PyAPITestHarness(TestHarness): else: self.execute_test() - def execute_test(self): + def execute_test(self, change_dir=False): """Build input XMLs, run OpenMC, and verify correct results.""" + base_dir = os.getcwd() if change_dir else None try: + if change_dir: + os.chdir(self.workdir) self._build_inputs() inputs = self._get_inputs() self._write_inputs(inputs) @@ -319,10 +322,15 @@ class PyAPITestHarness(TestHarness): self._compare_results() finally: self._cleanup() + if base_dir: + os.chdir(base_dir) - def update_results(self): + def update_results(self, change_dir=False): """Update results_true.dat and inputs_true.dat""" + base_dir = os.getcwd() if change_dir else None try: + if change_dir: + os.chdir(self.workdir) self._build_inputs() inputs = self._get_inputs() self._write_inputs(inputs) @@ -334,6 +342,8 @@ class PyAPITestHarness(TestHarness): self._overwrite_results() finally: self._cleanup() + if base_dir: + os.chdir(base_dir) def _build_inputs(self): """Write input XML files.""" @@ -371,7 +381,8 @@ class PyAPITestHarness(TestHarness): """Delete XMLs, statepoints, tally, and test files.""" super()._cleanup() output = ['materials.xml', 'geometry.xml', 'settings.xml', - 'tallies.xml', 'plots.xml', 'inputs_test.dat', 'model.xml'] + 'tallies.xml', 'plots.xml', 'inputs_test.dat', 'model.xml', + 'collision_track.h5', 'collision_track.mcpl'] for f in output: if os.path.exists(f): os.remove(f) @@ -389,6 +400,7 @@ class TolerantPyAPITestHarness(PyAPITestHarness): due to single precision usage (e.g., as in the random ray solver). """ + def _are_files_equal(self, actual_path, expected_path, tolerance): def isfloat(value): try: @@ -428,7 +440,8 @@ class TolerantPyAPITestHarness(PyAPITestHarness): def _compare_results(self): """Make sure the current results agree with the reference.""" - compare = self._are_files_equal('results_test.dat', 'results_true.dat', 1e-6) + compare = self._are_files_equal( + 'results_test.dat', 'results_true.dat', 1e-6) if not compare: expected = open('results_true.dat').readlines() actual = open('results_test.dat').readlines() @@ -476,6 +489,7 @@ class WeightWindowPyAPITestHarness(PyAPITestHarness): class PlotTestHarness(TestHarness): """Specialized TestHarness for running OpenMC plotting tests.""" + def __init__(self, plot_names, voxel_convert_checks=[]): super().__init__(None) self._plot_names = plot_names @@ -523,3 +537,105 @@ class PlotTestHarness(TestHarness): outstr = sha512.hexdigest() return outstr + + +class CollisionTrackTestHarness(PyAPITestHarness): + def __init__(self, statepoint_name, model=None, inputs_true=None, workdir=None): + super().__init__(statepoint_name, model, inputs_true) + self.workdir = workdir + + def _test_output_created(self): + """Make sure collision_track.h5 has also been created.""" + super()._test_output_created() + if self._model.settings.collision_track: + assert os.path.exists( + "collision_track.h5" + ), "collision_track file has not been created." + + def _compare_output(self): + """Compare collision_track.h5 files.""" + if self._model.settings.collision_track: + collision_track_true = self._return_collision_track_data( + "collision_track_true.h5") + collision_track_test = self._return_collision_track_data( + "collision_track.h5") + np.testing.assert_allclose( + collision_track_true, collision_track_test, rtol=1e-07) + + def main(self): + """Accept commandline arguments and either run or update tests.""" + if config["build_inputs"]: + self.build_inputs() + elif config["update"]: + self.update_results(change_dir=True) + else: + self.execute_test(change_dir=True) + + def build_inputs(self): + """Build inputs.""" + base_dir = os.getcwd() + try: + os.chdir(self.workdir) + self._build_inputs() + finally: + os.chdir(base_dir) + + def _overwrite_results(self): + """Also add the 'collision_track.h5' file during overwriting.""" + super()._overwrite_results() + if os.path.exists("collision_track.h5"): + shutil.copyfile("collision_track.h5", "collision_track_true.h5") + + @staticmethod + def _return_collision_track_data(filepath): + """ + Read a collision_track file and return a sorted array composed + of flatten arrays of collision information. + + Parameters + ---------- + filepath : str + Path to the collision_track file + + Returns + ------- + data : np.array + Sorted array composed of flatten arrays of collision_track data for + each collision information + """ + data = [] + keys = [] + + # Read source file + source = openmc.read_collision_track_file(filepath) + for src in source: + r = src['r'] + u = src['u'] + e = src['E'] + de = src['dE'] + time = src['time'] + wgt = src['wgt'] + delayed_group = src['delayed_group'] + cell_id = src['cell_id'] + nuclide_id = src['nuclide_id'] + material_id = src['material_id'] + universe_id = src['universe_id'] + n_collision = src['n_collision'] + event_mt = src['event_mt'] + key = ( + f"{r[0]:.10e} {r[1]:.10e} {r[2]:.10e} {u[0]:.10e} {u[1]:.10e} {u[2]:.10e}" + f"{e:.10e} {de:.10e} {time:.10e} {wgt:.10e} {event_mt} {delayed_group} {cell_id}" + f"{nuclide_id} {material_id} {universe_id} {n_collision} " + ) + keys.append(key) + values = [*r, *u, e, de, time, wgt, event_mt, + delayed_group, cell_id, nuclide_id, material_id, + universe_id, n_collision] + assert len(values) == 17 + data.append(values) + + data = np.array(data) + keys = np.array(keys) + sorted_idx = np.argsort(keys, kind='stable') + + return data[sorted_idx] diff --git a/tests/unit_tests/dagmc/test_lost_particles.py b/tests/unit_tests/dagmc/test_lost_particles.py index 502bd795e8..3a4166009d 100644 --- a/tests/unit_tests/dagmc/test_lost_particles.py +++ b/tests/unit_tests/dagmc/test_lost_particles.py @@ -70,12 +70,12 @@ def test_lost_particles(run_in_tmpdir, broken_dagmc_model): openmc.run() # run this again, but with the dagmc universe as the root unvierse + # to ensure that lost particles are still caught in this case for univ in broken_dagmc_model.geometry.get_all_universes().values(): if isinstance(univ, openmc.DAGMCUniverse): - broken_dagmc_model.geometry.root_unvierse = univ + broken_dagmc_model.geometry.root_universe = univ break broken_dagmc_model.export_to_xml() with pytest.raises(RuntimeError, match='Maximum number of lost particles has been reached.'): openmc.run() - diff --git a/tests/unit_tests/dagmc/test_model.py b/tests/unit_tests/dagmc/test_model.py index 0de4f6092d..0917f5b237 100644 --- a/tests/unit_tests/dagmc/test_model.py +++ b/tests/unit_tests/dagmc/test_model.py @@ -31,7 +31,7 @@ def model(request): p = Path(request.fspath).parent / "dagmc.h5m" - daguniv = openmc.DAGMCUniverse(p, auto_geom_ids=True) + daguniv = openmc.DAGMCUniverse(p, name='simple-dagmc', auto_geom_ids=True) lattice = openmc.RectLattice() lattice.dimension = [2, 2] @@ -232,6 +232,7 @@ def test_dagmc_xml(model): dagmc_ele = root.find('dagmc_universe') assert dagmc_ele.get('id') == str(dag_univ.id) + assert dagmc_ele.get('name') == str(dag_univ.name) assert dagmc_ele.get('filename') == str(dag_univ.filename) assert dagmc_ele.get('auto_geom_ids') == str(dag_univ.auto_geom_ids).lower() diff --git a/tests/unit_tests/dagmc/test_plot.py b/tests/unit_tests/dagmc/test_plot.py index 62022b2583..6ce1d79a22 100644 --- a/tests/unit_tests/dagmc/test_plot.py +++ b/tests/unit_tests/dagmc/test_plot.py @@ -64,5 +64,8 @@ def test_plotting_geometry_filled_with_dagmc_universe(request): cell2 = openmc.Cell(fill=csg_material, region=+sphere1 & -sphere2) geometry = openmc.Geometry([cell1, cell2]) - geometry.plot() + + # Close plot to avoid warning + import matplotlib.pyplot as plt + plt.close() diff --git a/tests/unit_tests/test_cell.py b/tests/unit_tests/test_cell.py index 95c8249bb3..60b2058186 100644 --- a/tests/unit_tests/test_cell.py +++ b/tests/unit_tests/test_cell.py @@ -126,6 +126,29 @@ def test_temperature(cell_with_lattice): c.temperature = (300., 600., 900.) +def test_densities(cell_with_lattice): + # Make sure density propagates through universes + m = openmc.Material() + s = openmc.XPlane() + c1 = openmc.Cell(fill=m, region=+s) + c2 = openmc.Cell(fill=m, region=-s) + u1 = openmc.Universe(cells=[c1, c2]) + c = openmc.Cell(fill=u1) + + c.density = 1. + assert c1.density == 1. + assert c2.density == 1. + with pytest.raises(ValueError): + c.density = -1. + c.density = None + assert c1.density == None + assert c2.density == None + + # distributed density + cells, _, _, _ = cell_with_lattice + c = cells[0] + c.density = (1., 2., 3.) + def test_rotation(): u = openmc.Universe() c = openmc.Cell(fill=u) diff --git a/tests/unit_tests/test_collision_track.py b/tests/unit_tests/test_collision_track.py new file mode 100644 index 0000000000..9bc6a8c15f --- /dev/null +++ b/tests/unit_tests/test_collision_track.py @@ -0,0 +1,127 @@ +"""Test the 'collision_track' setting used to store particle information +during specified collision conditions in a file for a given simulation.""" + +import openmc +import pytest +import h5py +import numpy as np + +from tests.testing_harness import CollisionTrackTestHarness as ctt + + +@pytest.fixture(scope="module") +def geometry(): + """Simple hydrogen sphere geometry""" + openmc.reset_auto_ids() + material = openmc.Material(name="H1") + material.add_element("H", 1.0) + sphere = openmc.Sphere(r=1.0, boundary_type="vacuum") + cell = openmc.Cell(region=-sphere, fill=material) + return openmc.Geometry([cell]) + + +@pytest.mark.parametrize( + "parameter", + [ + {"max_collisions": 200}, + {"max_collisions": 200, "reactions": ["(n,disappear)"]}, + {"max_collisions": 200, "cell_ids": [1]}, + {"max_collisions": 200, "material_ids": [1]}, + {"max_collisions": 200, "universe_ids": [1]}, + {"max_collisions": 200, "nuclides": ["H1"]}, + {"max_collisions": 200, "deposited_E_threshold": 200000.0}, + {"max_collisions": 200, "mcpl": True} + + ], +) +def test_xml_serialization(parameter, run_in_tmpdir): + """Check that the different use cases can be written and read in XML.""" + settings = openmc.Settings() + settings.collision_track = parameter + settings.export_to_xml() + + read_settings = openmc.Settings.from_xml() + assert read_settings.collision_track == parameter + + +@pytest.fixture(scope="module") +def model(): + """Simple hydrogen sphere divided in two hemispheres + by a z-plane to form 2 cells.""" + openmc.reset_auto_ids() + model = openmc.Model() + + # Material + material = openmc.Material(name="H1") + material.add_element("H", 1.0) + + # Geometry + radius = 1.0 + sphere = openmc.Sphere(r=radius, boundary_type="reflective") + plane = openmc.ZPlane(0.0) + cell_1 = openmc.Cell(region=-sphere & -plane, fill=material, cell_id=1) + cell_2 = openmc.Cell(region=-sphere & +plane, fill=material, cell_id=2) + root = openmc.Universe(cells=[cell_1, cell_2]) + model.geometry = openmc.Geometry(root) + + # Settings + model.settings = openmc.Settings() + model.settings.run_mode = "fixed source" + model.settings.particles = 1 + model.settings.batches = 1 + model.settings.seed = 2 + + bounds = [-radius, -radius, -radius, radius, radius, radius] + distribution = openmc.stats.Box(bounds[:3], bounds[3:]) + model.settings.source = openmc.IndependentSource(space=distribution) + + return model + + +def test_particle_location(run_in_tmpdir, model): + """Test the location of particles with respected to the "cell_ids" + and the location x, y, z of the particle itself. the upper sphere will + have positive z component and the bottom sphere a negative z compnent. + + """ + model.settings.collision_track = { + "max_collisions": 200, + "reactions": ["elastic"], + "cell_ids": [1, 2] + } + model.run() + + with h5py.File("collision_track.h5", "r") as f: + source = f["collision_track_bank"] + + assert len(source) == 60 + + # We want to verify that the collisions happenening are in the right cells + # and the position of the particle is either positive or negative relative + # to the z plane. In this case, we track the position of the particle + # relative to the cell_id already set. + for point in source: + if point['cell_id'] == 1: + assert point['r'][2] < 0.0 # z component negative + elif point['cell_id'] == 2: + assert point["r"][2] > 0.0 # z component positive + else: + assert False + + +def test_format_similarity(run_in_tmpdir, model): + model.settings.collision_track = {"max_collisions": 200, "reactions": ['elastic'], + "cell_ids": [1, 2], "mcpl": False} + model.run() + data_h5 = ctt._return_collision_track_data('collision_track.h5') + + model.settings.collision_track["mcpl"] = True + model.run() + data_mcpl = ctt._return_collision_track_data('collision_track.mcpl') + + assert len(data_h5) == 60 + assert len(data_mcpl) == 60 + + np.testing.assert_allclose(data_h5, data_mcpl, rtol=1e-05) + # tolerance not that low due to the strings that is saved in MCPL, + # not enough precision! diff --git a/tests/unit_tests/test_d1s.py b/tests/unit_tests/test_d1s.py index 9410f2da2e..8f3b62f400 100644 --- a/tests/unit_tests/test_d1s.py +++ b/tests/unit_tests/test_d1s.py @@ -120,6 +120,13 @@ def test_apply_time_correction(run_in_tmpdir): tally = sp.tallies[tally.id] flux = tally.mean.flatten() + # Copy attributes from original tally + tally_filters = list(tally.filters) + tally_sum = tally.sum.copy() + tally_sum_sq = tally.sum_sq.copy() + tally_mean = tally.mean.copy() + tally_std_dev = tally.std_dev.copy() + # Apply TCF and make sure results are consistent result = d1s.apply_time_correction(tally, factors, sum_nuclides=False) tcf = np.array([factors[nuc][-1] for nuc in nuclides]) @@ -129,6 +136,13 @@ def test_apply_time_correction(run_in_tmpdir): result_summed = d1s.apply_time_correction(tally, factors) assert result_summed.mean.flatten()[0] == pytest.approx(result.mean.sum()) + # Make sure original tally is unchanged + assert tally.filters == tally_filters + assert np.all(tally.sum == tally_sum) + assert np.all(tally.sum_sq == tally_sum_sq) + assert np.all(tally.mean == tally_mean) + assert np.all(tally.std_dev == tally_std_dev) + # Make sure various tally methods work result.get_values() result_summed.get_values() diff --git a/tests/unit_tests/test_deplete_activation.py b/tests/unit_tests/test_deplete_activation.py index 6afea8c9f9..eace1976ef 100644 --- a/tests/unit_tests/test_deplete_activation.py +++ b/tests/unit_tests/test_deplete_activation.py @@ -45,10 +45,11 @@ ENERGIES = np.logspace(log10(1e-5), log10(2e7), 100) @pytest.mark.parametrize("reaction_rate_mode,reaction_rate_opts,tolerance", [ ("direct", {}, 1e-5), - ("flux", {'energies': ENERGIES}, 0.01), + ("flux", {'energies': ENERGIES}, 0.1), ("flux", {'energies': ENERGIES, 'reactions': ['(n,gamma)']}, 1e-5), ("flux", {'energies': ENERGIES, 'reactions': ['(n,gamma)'], 'nuclides': ['W186', 'H3']}, 1e-2), ]) +@pytest.mark.flaky(reruns=1) def test_activation(run_in_tmpdir, model, reaction_rate_mode, reaction_rate_opts, tolerance): # Determine (n.gamma) reaction rate using initial run sp = model.run() @@ -61,11 +62,10 @@ def test_activation(run_in_tmpdir, model, reaction_rate_mode, reaction_rate_opts w186 = openmc.deplete.Nuclide('W186') w186.add_reaction('(n,gamma)', None, 0.0, 1.0) chain.add_nuclide(w186) - chain.export_to_xml('test_chain.xml') # Create transport operator op = openmc.deplete.CoupledOperator( - model, 'test_chain.xml', + model, chain, normalization_mode="source-rate", reaction_rate_mode=reaction_rate_mode, reaction_rate_opts=reaction_rate_opts, diff --git a/tests/unit_tests/test_deplete_continue.py b/tests/unit_tests/test_deplete_continue.py index 637c9d5e44..1b6eac2384 100644 --- a/tests/unit_tests/test_deplete_continue.py +++ b/tests/unit_tests/test_deplete_continue.py @@ -17,7 +17,7 @@ def test_continue(run_in_tmpdir): operator = dummy_operator.DummyOperator() # initial depletion - bundle.solver(operator, [1.0, 2.0], [1.0, 2.0]).integrate() + bundle.solver(operator, [1.0, 2.0], [1.0, 2.0]).integrate(write_rates=True) # set up continue run prev_res = openmc.deplete.Results(operator.output_dir / "depletion_results.h5") @@ -25,7 +25,7 @@ def test_continue(run_in_tmpdir): # if continue run happens, test passes bundle.solver(operator, [1.0, 2.0, 3.0, 4.0], [1.0, 2.0, 3.0, 4.0], - continue_timesteps=True).integrate() + continue_timesteps=True).integrate(write_rates=True) final_res = openmc.deplete.Results(operator.output_dir / "depletion_results.h5") @@ -42,7 +42,7 @@ def test_continue_continue(run_in_tmpdir): operator = dummy_operator.DummyOperator() # initial depletion - bundle.solver(operator, [1.0, 2.0], [1.0, 2.0]).integrate() + bundle.solver(operator, [1.0, 2.0], [1.0, 2.0]).integrate(write_rates=True) # set up continue run prev_res = openmc.deplete.Results(operator.output_dir / "depletion_results.h5") @@ -50,7 +50,7 @@ def test_continue_continue(run_in_tmpdir): # first continue run bundle.solver(operator, [1.0, 2.0, 3.0, 4.0], [1.0, 2.0, 3.0, 4.0], - continue_timesteps=True).integrate() + continue_timesteps=True).integrate(write_rates=True) prev_res = openmc.deplete.Results(operator.output_dir / "depletion_results.h5") # second continue run diff --git a/tests/unit_tests/test_deplete_integrator.py b/tests/unit_tests/test_deplete_integrator.py index b1d2cb950e..6463eaa208 100644 --- a/tests/unit_tests/test_deplete_integrator.py +++ b/tests/unit_tests/test_deplete_integrator.py @@ -10,6 +10,7 @@ import copy from random import uniform from unittest.mock import MagicMock +import h5py import numpy as np from uncertainties import ufloat import pytest @@ -38,8 +39,6 @@ INTEGRATORS = [ def test_results_save(run_in_tmpdir): """Test data save module""" - stages = 3 - rng = np.random.RandomState(comm.rank) # Mock geometry @@ -63,31 +62,22 @@ def test_results_save(run_in_tmpdir): op.get_results_info.return_value = ( vol_dict, nuc_list, burn_list, full_burn_list) - # Construct x - x1 = [] - x2 = [] + # Construct end-of-step concentrations + x1 = [rng.random(2), rng.random(2)] + x2 = [rng.random(2), rng.random(2)] - for i in range(stages): - x1.append([rng.random(2), rng.random(2)]) - x2.append([rng.random(2), rng.random(2)]) - - # Construct r + # Construct reaction rates r1 = ReactionRates(burn_list, ["na", "nb"], ["ra", "rb"]) r1[:] = rng.random((2, 2, 2)) + rate1 = copy.deepcopy(r1) - rate1 = [] - rate2 = [] + r2 = ReactionRates(burn_list, ["na", "nb"], ["ra", "rb"]) + r2[:] = rng.random((2, 2, 2)) + rate2 = copy.deepcopy(r2) - for i in range(stages): - rate1.append(copy.deepcopy(r1)) - r1[:] = rng.random((2, 2, 2)) - rate2.append(copy.deepcopy(r1)) - r1[:] = rng.random((2, 2, 2)) - - # Create global terms - # Col 0: eig, Col 1: uncertainty - eigvl1 = rng.random((stages, 2)) - eigvl2 = rng.random((stages, 2)) + # Create global terms (eigenvalue and uncertainty) + eigvl1 = rng.random(2) + eigvl2 = rng.random(2) eigvl1 = comm.bcast(eigvl1, root=0) eigvl2 = comm.bcast(eigvl2, root=0) @@ -95,29 +85,35 @@ def test_results_save(run_in_tmpdir): t1 = [0.0, 1.0] t2 = [1.0, 2.0] - op_result1 = [OperatorResult(ufloat(*k), rates) - for k, rates in zip(eigvl1, rate1)] - op_result2 = [OperatorResult(ufloat(*k), rates) - for k, rates in zip(eigvl2, rate2)] + op_result1 = OperatorResult(ufloat(*eigvl1), rate1) + op_result2 = OperatorResult(ufloat(*eigvl2), rate2) # saves within a subdirectory - StepResult.save(op, x1, op_result1, t1, 0, 0, path='out/put/depletion.h5') + StepResult.save( + op, + x1, + op_result1, + t1, + 0, + 0, + write_rates=True, + path='out/put/depletion.h5' + ) res = Results('out/put/depletion.h5') # saves with default filename - StepResult.save(op, x1, op_result1, t1, 0, 0) - StepResult.save(op, x2, op_result2, t2, 0, 1) + StepResult.save(op, x1, op_result1, t1, 0, 0, write_rates=True) + StepResult.save(op, x2, op_result2, t2, 0, 1, write_rates=True) # Load the files res = Results("depletion_results.h5") - for i in range(stages): - for mat_i, mat in enumerate(burn_list): - for nuc_i, nuc in enumerate(nuc_list): - assert res[0][i, mat, nuc] == x1[i][mat_i][nuc_i] - assert res[1][i, mat, nuc] == x2[i][mat_i][nuc_i] - np.testing.assert_array_equal(res[0].rates[i], rate1[i]) - np.testing.assert_array_equal(res[1].rates[i], rate2[i]) + for mat_i, mat in enumerate(burn_list): + for nuc_i, nuc in enumerate(nuc_list): + assert res[0][mat, nuc] == x1[mat_i][nuc_i] + assert res[1][mat, nuc] == x2[mat_i][nuc_i] + np.testing.assert_array_equal(res[0].rates, rate1) + np.testing.assert_array_equal(res[1].rates, rate2) np.testing.assert_array_equal(res[0].k, eigvl1) np.testing.assert_array_equal(res[0].time, t1) @@ -126,6 +122,31 @@ def test_results_save(run_in_tmpdir): np.testing.assert_array_equal(res[1].time, t2) +def test_results_save_without_rates(run_in_tmpdir): + """StepResult.save skips reaction-rate datasets by default""" + + op = MagicMock() + op.prev_res = None + vol_dict = {"0": 1.0} + nuc_list = ["na"] + burn_list = ["0"] + op.get_results_info.return_value = (vol_dict, nuc_list, burn_list, burn_list) + + x = [np.array([1.0])] + rates = ReactionRates(burn_list, nuc_list, ["ra"]) + rates[:] = np.array([[[2.0]]]) + op_result = OperatorResult(ufloat(1.0, 0.1), rates) + + StepResult.save(op, x, op_result, [0.0, 1.0], 0.0, 0) + + with h5py.File('depletion_results.h5', 'r') as handle: + assert 'reaction rates' not in handle + assert 'reactions' not in handle + + res = Results('depletion_results.h5') + assert res[0].rates.size == 0 + + def test_bad_integrator_inputs(): """Test failure modes for Integrator inputs""" diff --git a/tests/unit_tests/test_deplete_microxs.py b/tests/unit_tests/test_deplete_microxs.py index 073b3f162d..5762a8511b 100644 --- a/tests/unit_tests/test_deplete_microxs.py +++ b/tests/unit_tests/test_deplete_microxs.py @@ -111,3 +111,16 @@ def test_multigroup_flux_same(): energies=energies, multigroup_flux=flux, chain_file=chain_file) assert microxs_4g.data == pytest.approx(microxs_2g.data) + + +def test_microxs_zero_flux(): + chain_file = Path(__file__).parents[1] / 'chain_simple.xml' + + # Generate micro XS based on zero flux + energies = [0., 6.25e-1, 5.53e3, 8.21e5, 2.e7] + flux = [0.0, 0.0, 0.0, 0.0] + microxs = MicroXS.from_multigroup_flux( + energies=energies, multigroup_flux=flux, chain_file=chain_file) + + # All microscopic cross sections should be zero + assert np.all(microxs.data == 0.0) diff --git a/tests/unit_tests/test_deplete_restart.py b/tests/unit_tests/test_deplete_restart.py index e8bfc062a0..1cbff30a5f 100644 --- a/tests/unit_tests/test_deplete_restart.py +++ b/tests/unit_tests/test_deplete_restart.py @@ -21,7 +21,7 @@ def test_restart_predictor_cecm(run_in_tmpdir): # Perform simulation using the predictor algorithm dt = [0.75] power = 1.0 - openmc.deplete.PredictorIntegrator(op, dt, power).integrate() + openmc.deplete.PredictorIntegrator(op, dt, power).integrate(write_rates=True) # Load the files prev_res = openmc.deplete.Results(op.output_dir / "depletion_results.h5") @@ -30,10 +30,6 @@ def test_restart_predictor_cecm(run_in_tmpdir): op = dummy_operator.DummyOperator(prev_res) op.output_dir = output_dir - # check ValueError is raised, indicating previous and current stages - with pytest.raises(ValueError, match="incompatible.* 1.*2"): - openmc.deplete.CECMIntegrator(op, dt, power) - def test_restart_cecm_predictor(run_in_tmpdir): """Integral regression test of integrator algorithm using CE/CM for the @@ -47,7 +43,7 @@ def test_restart_cecm_predictor(run_in_tmpdir): dt = [0.75] power = 1.0 cecm = openmc.deplete.CECMIntegrator(op, dt, power) - cecm.integrate() + cecm.integrate(write_rates=True) # Load the files prev_res = openmc.deplete.Results(op.output_dir / "depletion_results.h5") @@ -56,10 +52,6 @@ def test_restart_cecm_predictor(run_in_tmpdir): op = dummy_operator.DummyOperator(prev_res) op.output_dir = output_dir - # check ValueError is raised, indicating previous and current stages - with pytest.raises(ValueError, match="incompatible.* 2.*1"): - openmc.deplete.PredictorIntegrator(op, dt, power) - @pytest.mark.parametrize("scheme", dummy_operator.SCHEMES) def test_restart(run_in_tmpdir, scheme): @@ -70,7 +62,7 @@ def test_restart(run_in_tmpdir, scheme): operator = dummy_operator.DummyOperator() # take first step - bundle.solver(operator, [0.75], 1.0).integrate() + bundle.solver(operator, [0.75], 1.0).integrate(write_rates=True) # restart prev_res = openmc.deplete.Results( diff --git a/tests/unit_tests/test_deplete_resultslist.py b/tests/unit_tests/test_deplete_resultslist.py index 308eccf7bb..9a4699a4fd 100644 --- a/tests/unit_tests/test_deplete_resultslist.py +++ b/tests/unit_tests/test_deplete_resultslist.py @@ -21,14 +21,14 @@ def test_get_activity(res): t_ref = np.array([0.0, 1296000.0, 2592000.0, 3888000.0]) a_ref = np.array( - [1.25167956e+06, 3.71938527e+11, 4.43264300e+11, 3.55547176e+11]) + [1.25167956e+06, 3.69842310e+11, 3.70099291e+11, 3.53629755e+11]) np.testing.assert_allclose(t, t_ref) np.testing.assert_allclose(a, a_ref) # Check by_nuclide a_xe135_ref = np.array( - [2.106574218e+05, 1.227519888e+11, 1.177491828e+11, 1.031986176e+11]) + [2.10657422e+05, 1.12825236e+11, 1.09055177e+11, 1.07491257e+11]) t_nuc, a_nuc = res.get_activity("1", by_nuclide=True) a_xe135 = np.array([a_nuc_i["Xe135"] for a_nuc_i in a_nuc]) @@ -43,7 +43,7 @@ def test_get_atoms(res): t_ref = np.array([0.0, 1296000.0, 2592000.0, 3888000.0]) n_ref = np.array( - [6.67473282e+08, 3.88942731e+14, 3.73091215e+14, 3.26987387e+14]) + [6.67473282e+08, 3.57489567e+14, 3.45544042e+14, 3.40588723e+14]) np.testing.assert_allclose(t, t_ref) np.testing.assert_allclose(n, n_ref) @@ -71,7 +71,7 @@ def test_get_decay_heat(res): t_ref = np.array([0.0, 1296000.0, 2592000.0, 3888000.0]) dh_ref = np.array( - [1.27933813e-09, 5.85347232e-03, 7.38773010e-03, 5.79954067e-03]) + [1.27933813e-09, 5.95370258e-03, 6.01335600e-03, 5.69831173e-03]) t, dh = res.get_decay_heat("1") @@ -80,7 +80,7 @@ def test_get_decay_heat(res): # Check by nuclide dh_xe135_ref = np.array( - [1.27933813e-09, 7.45481920e-04, 7.15099509e-04, 6.26732849e-04]) + [1.27933813e-09, 6.85196014e-04, 6.62300168e-04, 6.52802366e-04]) t_nuc, dh_nuc = res.get_decay_heat("1", by_nuclide=True) dh_nuc_xe135 = np.array([dh_nuc_i["Xe135"] for dh_nuc_i in dh_nuc]) @@ -95,7 +95,7 @@ def test_get_mass(res): t_ref = np.array([0.0, 1296000.0, 2592000.0, 3888000.0]) n_ref = np.array( - [6.67473282e+08, 3.88942731e+14, 3.73091215e+14, 3.26987387e+14]) + [6.67473282e+08, 3.57489567e+14, 3.45544042e+14, 3.40588723e+14]) # Get g n_ref *= openmc.data.atomic_mass('Xe135') / openmc.data.AVOGADRO @@ -123,8 +123,8 @@ def test_get_reaction_rate(res): t, r = res.get_reaction_rate("1", "Xe135", "(n,gamma)") t_ref = [0.0, 1296000.0, 2592000.0, 3888000.0] - n_ref = [6.67473282e+08, 3.88942731e+14, 3.73091215e+14, 3.26987387e+14] - xs_ref = [2.53336104e-05, 4.21747011e-05, 3.48616127e-05, 3.61775563e-05] + n_ref = [6.67473282e+08, 3.57489567e+14, 3.45544042e+14, 3.40588723e+14] + xs_ref = [3.10220818e-05, 3.36754072e-05, 3.12740350e-05, 3.86717693e-05] np.testing.assert_allclose(t, t_ref) np.testing.assert_allclose(r, np.array(n_ref) * xs_ref) @@ -136,8 +136,8 @@ def test_get_keff(res): t_min, k = res.get_keff(time_units='min') t_ref = [0.0, 1296000.0, 2592000.0, 3888000.0] - k_ref = [1.1596402556, 1.1914183335, 1.2292570871, 1.1797030302] - u_ref = [0.0270680649, 0.0219163444, 0.024268508 , 0.0221401194] + k_ref = [1.1773089172, 1.2231748584, 1.1611455694, 1.1714783649] + u_ref = [0.0384666252, 0.0311915665, 0.0226370102, 0.0315964732] np.testing.assert_allclose(t, t_ref) np.testing.assert_allclose(t_min * 60, t_ref) diff --git a/tests/unit_tests/test_deplete_transfer_rates.py b/tests/unit_tests/test_deplete_transfer_rates.py index a3228e9fb7..a6dcb2b276 100644 --- a/tests/unit_tests/test_deplete_transfer_rates.py +++ b/tests/unit_tests/test_deplete_transfer_rates.py @@ -198,3 +198,35 @@ def test_transfer(run_in_tmpdir, model): # Ensure number of atoms equal transfer decay assert atoms[1] == pytest.approx(atoms[0]*exp(-transfer_rate*3600*24)) assert atoms[2] == pytest.approx(atoms[1]*exp(-transfer_rate*3600*24)) + +@pytest.mark.parametrize("case_name, buffer, ox", [ + ('redox', {'Gd157':1}, {'Gd': 3, 'U': 4}), + ('buffer_invalid', {'Gd158':1}, {'Gd': 3, 'U': 4}), + ('elm_invalid', {'Gd157':1}, {'Gb': 3, 'U': 4}), + ]) +def test_redox(case_name, buffer, ox, model): + op = CoupledOperator(model, CHAIN_PATH) + number_of_timesteps = 2 + transfer = TransferRates(op, model.materials, number_of_timesteps) + + # Test by Openmc material, material name and material id + material, dest_material, dest_material2 = [m for m in model.materials + if m.depletable] + for material_input in [material, material.name, material.id]: + for dest_material_input in [dest_material, dest_material.name, + dest_material.id]: + + if case_name == 'buffer_invalid': + with pytest.raises(ValueError, match='Gd158 is not a valid ' + 'nuclide.'): + transfer.set_redox(material_input, buffer, ox) + + elif case_name == 'elm_invalid': + with pytest.raises(ValueError, match='Gb is not a valid ' + 'element.'): + transfer.set_redox(material_input, buffer, ox) + else: + transfer.set_redox(material_input, buffer, ox) + mat_id = transfer._get_material_id(material_input) + assert transfer.redox[mat_id][0] == buffer + assert transfer.redox[mat_id][1] == ox diff --git a/tests/unit_tests/test_filter_distribcell.py b/tests/unit_tests/test_filter_distribcell.py new file mode 100644 index 0000000000..d5734a2c07 --- /dev/null +++ b/tests/unit_tests/test_filter_distribcell.py @@ -0,0 +1,53 @@ +import openmc +import pandas as pd + + +def test_distribcell_filter_apply_tally_results(run_in_tmpdir): + # Reset IDs to ensure consistent paths + openmc.reset_auto_ids() + + mat = openmc.Material() + mat.add_nuclide("U235", 1.0) + mat.set_density("g/cm3", 1.0) + + # Define 2x2 lattice with a cylinder in each universe + cyl = openmc.ZCylinder(r=1.0) + cell1 = openmc.Cell(fill=mat, region=-cyl) + cell2 = openmc.Cell(fill=None, region=+cyl) + univ = openmc.Universe(cells=[cell1, cell2]) + lattice = openmc.RectLattice() + lattice.lower_left = (-3.0, -3.0) + lattice.pitch = (3.0, 3.0) + lattice.universes = [[univ, univ], [univ, univ]] + box = openmc.model.RectangularPrism(6., 6., boundary_type='reflective') + root_cell = openmc.Cell(region=-box, fill=lattice) + geometry = openmc.Geometry([root_cell]) + + # Create model and add tally with distribcell filter + model = openmc.Model(geometry) + model.settings.batches = 10 + model.settings.particles = 1000 + tally = openmc.Tally() + distribcell_filter = openmc.DistribcellFilter(cell1) + tally.filters = [distribcell_filter] + tally.scores = ['flux'] + model.tallies = [tally] + + # Run OpenMC and apply tally results + model.run(apply_tally_results=True) + + # Check that mean and standard deviation are available on tally + assert tally.mean.shape == (4, 1, 1) + assert tally.std_dev.shape == (4, 1, 1) + + # Make sure paths attribute on filter is correct + assert distribcell_filter.paths == [ + 'u3->c3->l2(0,0)->u1->c1', + 'u3->c3->l2(1,0)->u1->c1', + 'u3->c3->l2(0,1)->u1->c1', + 'u3->c3->l2(1,1)->u1->c1', + ] + + # Check that we can get a DataFrame from the tally + df = tally.get_pandas_dataframe() + assert isinstance(df, pd.DataFrame) diff --git a/tests/unit_tests/test_ifp.py b/tests/unit_tests/test_ifp.py index 8d0fd98010..e527f16246 100644 --- a/tests/unit_tests/test_ifp.py +++ b/tests/unit_tests/test_ifp.py @@ -47,3 +47,42 @@ def test_exceptions(options, error, run_in_tmpdir, geometry): tallies = openmc.Tallies([tally]) model = openmc.Model(geometry=geometry, settings=settings, tallies=tallies) model.run() + + +@pytest.mark.parametrize( + "num_groups, use_auto_tallies", + [ + (None, True), + (None, False), + (6, True), + (6, False), + ], +) +def test_get_kinetics_parameters(run_in_tmpdir, geometry, num_groups, use_auto_tallies): + # Create basic model + model = openmc.Model(geometry=geometry) + model.settings.particles = 1000 + model.settings.batches = 20 + model.settings.inactive = 5 + model.settings.ifp_n_generation = 5 + + # Add IFP tallies either via the convenience method or manually + if use_auto_tallies: + model.add_kinetics_parameters_tallies(num_groups=num_groups) + else: + for score in ["ifp-time-numerator", "ifp-beta-numerator", "ifp-denominator"]: + tally = openmc.Tally() + tally.scores = [score] + if score == "ifp-beta-numerator" and num_groups is not None: + tally.filters = [openmc.DelayedGroupFilter(list(range(1, num_groups + 1)))] + model.tallies.append(tally) + + # Run and get kinetics parameters + sp_file = model.run() + with openmc.StatePoint(sp_file) as sp: + params = sp.get_kinetics_parameters() + assert isinstance(params, openmc.KineticsParameters) + assert params.generation_time is not None + assert params.beta_effective is not None + if num_groups is not None: + assert len(params.beta_effective) == num_groups diff --git a/tests/unit_tests/test_lib.py b/tests/unit_tests/test_lib.py index 8ab35335fc..eb4dc3dce6 100644 --- a/tests/unit_tests/test_lib.py +++ b/tests/unit_tests/test_lib.py @@ -159,6 +159,34 @@ def test_properties_temperature(lib_init): assert cell.get_temperature() == pytest.approx(200.0) +def test_cell_density(lib_init): + cell = openmc.lib.cells[1] + print('density', cell.get_density()) + orig_density = cell.get_density() + try: + cell.set_density(1.5, 0) + assert cell.get_density(0) == pytest.approx(1.5) + cell.set_density(2.0) + assert cell.get_density() == pytest.approx(2.0) + finally: + cell.set_density(orig_density) + + +def test_properties_cell_density(lib_init): + # Cell density should be 2.0 from above test + cell = openmc.lib.cells[1] + orig_density = cell.get_density() + + # Export properties and change density + openmc.lib.export_properties('properties.h5') + cell.set_density(3.0) + assert cell.get_density() == pytest.approx(3.0) + + # Import properties and check that density is restored + openmc.lib.import_properties('properties.h5') + assert cell.get_density() == pytest.approx(orig_density) + + def test_new_cell(lib_init): with pytest.raises(exc.AllocationError): openmc.lib.Cell(1) @@ -468,9 +496,6 @@ def test_set_n_batches(lib_run): for i in range(7): openmc.lib.next_batch() - # Setting n_batches less than current_batch should raise error - with pytest.raises(exc.InvalidArgumentError): - settings.set_batches(6) # n_batches should stay the same assert settings.get_batches() == 10 diff --git a/tests/unit_tests/test_material.py b/tests/unit_tests/test_material.py index 2e37242720..764c98d41a 100644 --- a/tests/unit_tests/test_material.py +++ b/tests/unit_tests/test_material.py @@ -481,6 +481,7 @@ def test_borated_water(): # Test the density override m = openmc.model.borated_water(975, 566.5, 15.51, density=0.9) assert m.density == pytest.approx(0.9, 1e-3) + assert m.temperature == pytest.approx(566.5) def test_from_xml(run_in_tmpdir): @@ -767,3 +768,54 @@ def test_mean_free_path(): mat2.add_nuclide('Pb208', 1.0) mat2.set_density('g/cm3', 11.34) assert mat2.mean_free_path(energy=14e6) == pytest.approx(5.65, abs=1e-2) + + +def test_material_from_constructor(): + # Test that components and percent_type work in the constructor + components = { + 'Li': {'percent': 0.5, 'enrichment': 60.0, 'enrichment_target': 'Li7'}, + 'O16': 1.0, + 'Be': 0.5 + } + mat = openmc.Material( + material_id=123, + name="test-mat", + components=components, + percent_type="ao" + ) + # Check that nuclides were added + nuclide_names = [nuc.name for nuc in mat.nuclides] + assert 'O16' in nuclide_names + assert 'Be9' in nuclide_names + assert 'Li7' in nuclide_names + assert 'Li6' in nuclide_names + assert mat.id == 123 + assert mat.name == "test-mat" + + mat1 = openmc.Material( + **{ + "material_id": 1, + "name": "neutron_star", + "density": 1e17, + "density_units": "kg/m3", + } + ) + assert mat1.id == 1 + assert mat1.name == "neutron_star" + assert mat1._density == 1e17 + assert mat1._density_units == "kg/m3" + assert mat1.nuclides == [] + + mat2 = openmc.Material( + material_id=42, + name="plasma", + temperature=None, + density=1e-7, + density_units="g/cm3", + ) + assert mat2.id == 42 + assert mat2.name == "plasma" + assert mat2.temperature is None + assert mat2.density == 1e-7 + assert mat2.density_units == "g/cm3" + assert mat2.nuclides == [] diff --git a/tests/unit_tests/test_mesh.py b/tests/unit_tests/test_mesh.py index 67ca4028e0..9aca8b5965 100644 --- a/tests/unit_tests/test_mesh.py +++ b/tests/unit_tests/test_mesh.py @@ -2,11 +2,14 @@ from math import pi from tempfile import TemporaryDirectory from pathlib import Path +import h5py import numpy as np +from scipy.stats import chi2 import pytest import openmc import openmc.lib from openmc.utility_funcs import change_directory +from uncertainties.unumpy import uarray, nominal_values, std_devs @pytest.mark.parametrize("val_left,val_right", [(0, 0), (-1., -1.), (2.0, 2)]) @@ -481,9 +484,77 @@ def test_umesh(run_in_tmpdir, simple_umesh, export_type): np.testing.assert_almost_equal(mean, ref_data) # attempt to apply a dataset with an improper size to a VTK write - with pytest.raises(ValueError, match='Cannot apply dataset "mean"') as e: + with pytest.raises(ValueError, match='Cannot apply dataset "mean"'): simple_umesh.write_data_to_vtk(datasets={'mean': ref_data[:-2]}, filename=filename) + +@pytest.mark.skipif(not openmc.lib._dagmc_enabled(), reason="DAGMC not enabled.") +def test_write_vtkhdf(request, run_in_tmpdir): + """Performs a minimal UnstructuredMesh simulation, reads in the resulting + statepoint file and writes the mesh data to vtk and vtkhdf files. It is + necessary to read in the unstructured mesh from a statepoint file to ensure + it has all the required attributes + """ + model = openmc.Model() + + surf1 = openmc.Sphere(r=1000.0, boundary_type="vacuum") + cell1 = openmc.Cell(region=-surf1) + model.geometry = openmc.Geometry([cell1]) + + umesh = openmc.UnstructuredMesh( + request.path.parent / "test_mesh_dagmc_tets.vtk", + "moab", + mesh_id = 1 + ) + mesh_filter = openmc.MeshFilter(umesh) + + # Create flux mesh tally to score alpha production + mesh_tally = openmc.Tally(name="test_tally") + mesh_tally.filters = [mesh_filter] + mesh_tally.scores = ["flux"] + + model.tallies = [mesh_tally] + + model.settings.run_mode = "fixed source" + model.settings.batches = 2 + model.settings.particles = 10 + + statepoint_file = model.run() + + with openmc.StatePoint(statepoint_file) as statepoint: + my_tally = statepoint.get_tally(name="test_tally") + + umesh_from_sp = statepoint.meshes[umesh.id] + + datasets={ + "mean": my_tally.mean.flatten(), + "std_dev": my_tally.std_dev.flatten() + } + + umesh_from_sp.write_data_to_vtk(datasets=datasets, filename="test_mesh.vtkhdf") + umesh_from_sp.write_data_to_vtk(datasets=datasets, filename="test_mesh.vtk") + + with pytest.raises(ValueError, match="Unsupported file extension"): + # Supported file extensions are vtk or vtkhdf, not hdf5, so this should raise an error + umesh_from_sp.write_data_to_vtk( + datasets=datasets, + filename="test_mesh.hdf5", + ) + with pytest.raises(ValueError, match="Cannot apply dataset"): + # The shape of the data should match the shape of the mesh, so this should raise an error + umesh_from_sp.write_data_to_vtk( + datasets={'incorrectly_shaped_data': np.array(([1,2,3]))}, + filename="test_mesh_incorrect_shape.vtkhdf", + ) + + assert Path("test_mesh.vtk").exists() + assert Path("test_mesh.vtkhdf").exists() + + # just ensure we can open the file without error + with h5py.File("test_mesh.vtkhdf", "r"): + ... + + def test_mesh_get_homogenized_materials(): """Test the get_homogenized_materials method""" # Simple model with 1 cm of Fe56 next to 1 cm of H1 @@ -620,6 +691,33 @@ def test_mesh_material_volumes_serialize(): assert new_volumes.by_element(3) == [(2, 1.0)] +def test_mesh_material_volumes_boundary_conditions(sphere_model): + """Test the material volumes method using a regular mesh + that overlaps with a vacuum boundary condition.""" + + mesh = openmc.SphericalMesh.from_domain(sphere_model.geometry, dimension=(1, 1, 1)) + # extend mesh beyond the outer sphere surface to test rays crossing the boundary condition + mesh.r_grid[-1] += 5.0 + + # add a new cell to the modelthat occupies the outside of the sphere + sphere_surfaces = list(filter(lambda s: isinstance(s, openmc.Sphere), + sphere_model.geometry.get_all_surfaces().values())) + outer_cell = openmc.Cell(region=+sphere_surfaces[0]) + sphere_model.geometry.root_universe.add_cell(outer_cell) + + volumes = mesh.material_volumes(sphere_model, (0, 100, 100)) + sphere_volume = 4/3*np.pi*25**3 + mats = sphere_model.materials + expected_volumes = [(mats[0].id, 0.25*sphere_volume), + (mats[1].id, 0.25*sphere_volume), + (mats[2].id, 0.5*sphere_volume), + (None, 4/3*np.pi*mesh.r_grid[-1]**3 - sphere_volume)] + + for evaluated, expected in zip(volumes.by_element(0), expected_volumes): + assert evaluated[0] == expected[0] + assert evaluated[1] == pytest.approx(expected[1], rel=1e-2) + + def test_raytrace_mesh_infinite_loop(run_in_tmpdir): # Create a model with one large spherical cell sphere = openmc.Sphere(r=100, boundary_type='vacuum') @@ -651,3 +749,82 @@ def test_raytrace_mesh_infinite_loop(run_in_tmpdir): # Run the model; this should not cause an infinite loop model.run() + + +def test_filter_time_mesh(run_in_tmpdir): + """Test combination of TimeFilter and MeshFilter""" + + # Define material + mat = openmc.Material() + mat.add_nuclide('Fe56', 1.0) + mat.set_density('g/cm3', 7.8) + + # Define geometry + surf_Z1 = openmc.XPlane(x0=-1e10, boundary_type="reflective") + surf_Z2 = openmc.XPlane(x0=1e10, boundary_type="reflective") + cell_F = openmc.Cell(fill=mat, region=+surf_Z1 & -surf_Z2) + model = openmc.Model() + model.geometry = openmc.Geometry([cell_F]) + + # Define settings + model.settings.run_mode = "fixed source" + model.settings.particles = 1000 + model.settings.batches = 20 + model.settings.output = {"tallies": False} + model.settings.cutoff = {"time_neutron": 1e-7} + + # Define tallies + + # Create a mesh filter that can be used in a tally + mesh = openmc.RegularMesh() + mesh.dimension = (21, 1, 1) + mesh.lower_left = (-20.5, -1e10, -1e10) + mesh.upper_right = (20.5, 1e10, 1e10) + time_grid = np.linspace(0.0, 1e-7, 21) + + mesh_filter = openmc.MeshFilter(mesh) + time_filter = openmc.TimeFilter(time_grid) + + # Now use the mesh filter in a tally and indicate what scores are desired + tally1 = openmc.Tally(name="collision") + tally1.estimator = "collision" + tally1.filters = [time_filter, mesh_filter] + tally1.scores = ["flux"] + tally2 = openmc.Tally(name="tracklength") + tally2.estimator = "tracklength" + tally2.filters = [time_filter, mesh_filter] + tally2.scores = ["flux"] + model.tallies = openmc.Tallies([tally1, tally2]) + + # Run and post-process + model.run(apply_tally_results=True) + + # Get radial flux distribution + flux_collision = tally1.mean.ravel() + flux_collision_unc = tally1.std_dev.ravel() + flux_tracklength = tally2.mean.ravel() + flux_tracklength_unc = tally2.std_dev.ravel() + + # Construct arrays with uncertainties + collision = uarray(flux_collision, flux_collision_unc) + tracklength = uarray(flux_tracklength, flux_tracklength_unc) + delta = collision - tracklength + + # Compute differences and standard deviations + diff = nominal_values(delta) + std_dev = std_devs(delta) + + # Exclude zero-uncertainty bins + mask = std_dev > 0.0 + dof = int(np.sum(mask)) + + # Global chi-square consistency test between collision and tracklength + # estimators. Target false positive rate ~1e-4 (1 in 10,000) + z = diff[mask] / std_dev[mask] + chi2_stat = np.sum(z * z) + alpha = 1.0e-4 + crit = chi2.ppf(1 - alpha, dof) + assert chi2_stat < crit, ( + f"Collision vs tracklength tallies disagree: chi2={chi2_stat:.2f} " + f">= {crit=:.2f} ({dof=}, {alpha=})" + ) diff --git a/tests/unit_tests/test_mesh_dagmc_tets.vtk b/tests/unit_tests/test_mesh_dagmc_tets.vtk new file mode 120000 index 0000000000..9f7000175d --- /dev/null +++ b/tests/unit_tests/test_mesh_dagmc_tets.vtk @@ -0,0 +1 @@ +../regression_tests/unstructured_mesh/test_mesh_dagmc_tets.vtk \ No newline at end of file diff --git a/tests/unit_tests/test_model.py b/tests/unit_tests/test_model.py index 6e4dec00ff..d553af53c7 100644 --- a/tests/unit_tests/test_model.py +++ b/tests/unit_tests/test_model.py @@ -73,13 +73,13 @@ def pin_model_attributes(): tal.scores = ['flux', 'fission'] tals.append(tal) - plot1 = openmc.Plot(plot_id=1) + plot1 = openmc.SlicePlot(plot_id=1) plot1.origin = (0., 0., 0.) plot1.width = (pitch, pitch) plot1.pixels = (300, 300) plot1.color_by = 'material' plot1.filename = 'test' - plot2 = openmc.Plot(plot_id=2) + plot2 = openmc.SlicePlot(plot_id=2) plot2.origin = (0., 0., 0.) plot2.width = (pitch, pitch) plot2.pixels = (300, 300) @@ -251,10 +251,11 @@ def test_import_properties(run_in_tmpdir, mpi_intracomm): model = openmc.examples.pwr_pin_cell() model.init_lib(output=False, intracomm=mpi_intracomm) - # Change fuel temperature and density and export properties + # Change cell fuel temperature, density, material density and export properties cell = openmc.lib.cells[1] cell.set_temperature(600.0) cell.fill.set_density(5.0, 'g/cm3') + cell.set_density(10.0) openmc.lib.export_properties(output=False) # Import properties to existing model @@ -264,9 +265,11 @@ def test_import_properties(run_in_tmpdir, mpi_intracomm): # First python cell = model.geometry.get_all_cells()[1] assert cell.temperature == [600.0] + assert cell.density == [pytest.approx(10.0, 1e-5)] assert cell.fill.get_mass_density() == pytest.approx(5.0) # Now C assert openmc.lib.cells[1].get_temperature() == 600. + assert openmc.lib.cells[1].get_density() == pytest.approx(10.0, 1e-5) assert openmc.lib.materials[1].get_density('g/cm3') == pytest.approx(5.0) # Clear the C API @@ -283,6 +286,7 @@ def test_import_properties(run_in_tmpdir, mpi_intracomm): ) cell = model_with_properties.geometry.get_all_cells()[1] assert cell.temperature == [600.0] + assert cell.density == [pytest.approx(10.0, 1e-5)] assert cell.fill.get_mass_density() == pytest.approx(5.0) @@ -650,6 +654,10 @@ def test_model_plot(): test_mask = (image_data == white) | (image_data == red) assert np.all(test_mask), "Colors other than white or red found in overlap plot image" + # Close plots to avoid warning + import matplotlib.pyplot as plt + plt.close('all') + def test_model_id_map_initialization(run_in_tmpdir): model = openmc.examples.pwr_assembly() @@ -893,6 +901,33 @@ def test_id_map_aligned_model(): assert tr_instance == 3, f"Expected cell instance 3 at top-right corner, got {tr_instance}" assert tr_material == 5, f"Expected material ID 5 at top-right corner, got {tr_material}" + +def test_id_map_model_with_overlaps(): + """Test id_map with a model that has overlaps and color_overlaps option""" + surface1 = openmc.Sphere(r=50, boundary_type="vacuum") + surface2 = openmc.Sphere(r=30) + cell1 = openmc.Cell(region=-surface1) + cell2 = openmc.Cell(region=-surface2) + geometry = openmc.Geometry([cell1, cell2]) + settings = openmc.Settings() + model = openmc.Model(geometry=geometry, settings=settings) + id_slice = model.id_map( + pixels=(10, 10), + basis='xy', + origin=(0, 0, 0), + width=(100, 100), + ) + assert -3 not in id_slice # -3 indicates overlap region + id_slice = model.id_map( + pixels=(10, 10), + basis='xy', + origin=(0, 0, 0), + width=(100, 100), + color_overlaps=True, # enables id_map to return -3 for overlaps + ) + assert -3 in id_slice + + def test_setter_from_list(): mat = openmc.Material() model = openmc.Model(materials=[mat]) @@ -902,6 +937,62 @@ def test_setter_from_list(): model = openmc.Model(tallies=[tally]) assert isinstance(model.tallies, openmc.Tallies) - plot = openmc.Plot() + plot = openmc.SlicePlot() model = openmc.Model(plots=[plot]) assert isinstance(model.plots, openmc.Plots) + + +def test_keff_search(run_in_tmpdir): + """Test the Model.keff_search method""" + + # Create model of a sphere of U235 + mat = openmc.Material() + mat.set_density('g/cm3', 18.9) + mat.add_nuclide('U235', 1.0) + sphere = openmc.Sphere(r=10.0, boundary_type='vacuum') + cell = openmc.Cell(fill=mat, region=-sphere) + geometry = openmc.Geometry([cell]) + settings = openmc.Settings(particles=1000, inactive=10, batches=30) + model = openmc.Model(geometry=geometry, settings=settings) + + # Define function to modify sphere radius + def modify_radius(radius): + sphere.r = radius + + # Perform keff search + k_tol = 4e-3 + sigma_final = 2e-3 + result = model.keff_search( + func=modify_radius, + x0=6.0, + x1=9.0, + k_tol=k_tol, + sigma_final=sigma_final, + output=True, + ) + + final_keff = result.means[-1] + 1.0 # Add back target since means are (keff - target) + final_sigma = result.stdevs[-1] + + # Check for convergence and that tolerances are met + assert result.converged, "keff_search did not converge" + assert abs(final_keff - 1.0) <= k_tol, \ + f"Final keff {final_keff:.5f} not within k_tol {k_tol}" + assert final_sigma <= sigma_final, \ + f"Final uncertainty {final_sigma:.5f} exceeds sigma_final {sigma_final}" + + # Check type of result + assert isinstance(result, openmc.model.SearchResult) + + # Check that we have function evaluation history + assert len(result.parameters) >= 2 + assert len(result.means) == len(result.parameters) + assert len(result.stdevs) == len(result.parameters) + assert len(result.batches) == len(result.parameters) + + # Check that function_calls property works + assert result.function_calls == len(result.parameters) + + # Check that total_batches property works + assert result.total_batches == sum(result.batches) + assert result.total_batches > 0 diff --git a/tests/unit_tests/test_no_reduce.py b/tests/unit_tests/test_no_reduce.py new file mode 100644 index 0000000000..00ddb5a959 --- /dev/null +++ b/tests/unit_tests/test_no_reduce.py @@ -0,0 +1,40 @@ +"""Test the settings.no_reduce feature to ensure tallies are correctly +reduced across MPI processes.""" + +import openmc +import pytest + +from tests.testing_harness import config + + +@pytest.mark.parametrize('no_reduce', [True, False]) +def test_no_reduce(no_reduce, run_in_tmpdir): + """Test that tally results are correct with and without no_reduce.""" + + # Create simple sphere model with vacuum + model = openmc.Model() + sphere = openmc.Sphere(r=1.0, boundary_type='vacuum') + cell = openmc.Cell(region=-sphere) + model.geometry = openmc.Geometry([cell]) + model.settings.run_mode = 'fixed source' + model.settings.batches = 10 + model.settings.particles = 100 + model.settings.source = openmc.IndependentSource(space=openmc.stats.Point()) + model.settings.no_reduce = no_reduce + + # Tally: surface current on vacuum boundary + surf_filter = openmc.SurfaceFilter(sphere) + tally = openmc.Tally() + tally.filters = [surf_filter] + tally.scores = ['current'] + model.tallies = [tally] + + # Run OpenMC with proper MPI arguments if needed + kwargs = {'apply_tally_results': True, 'openmc_exec': config['exe']} + if config['mpi']: + kwargs['mpi_args'] = [config['mpiexec'], '-n', config['mpi_np']] + model.run(**kwargs) + + # The tally should be ~1.0 (every particle crosses the surface once) + tally_mean = tally.mean.flatten()[0] + assert tally_mean == pytest.approx(1.0) diff --git a/tests/unit_tests/test_pathlike_simple.py b/tests/unit_tests/test_pathlike_simple.py new file mode 100644 index 0000000000..e0116bf01c --- /dev/null +++ b/tests/unit_tests/test_pathlike_simple.py @@ -0,0 +1,46 @@ +"""Simple test for PathLike filename support""" + +from pathlib import Path + +import pytest +import openmc +from openmc.checkvalue import check_type, PathLike + + +def test_pathlike_type_checking(): + """Test that PathLike type checking works correctly""" + + # Test with string (should work) + check_type('filename', 'test.txt', PathLike) + + # Test with Path object (should work) + path_obj = Path('test.txt') + check_type('filename', path_obj, PathLike) + + # Test with Path object containing subdirectories (should work) + path_with_subdir = Path('subdir') / 'test.txt' + check_type('filename', path_with_subdir, PathLike) + + # Test with invalid type (should raise TypeError) + with pytest.raises(TypeError): + check_type('filename', 123, PathLike) + + +def test_plot_filename_pathlike(): + """Test that plot filename accepts Path objects""" + + plot = openmc.Plot() + + # Test with string (should still work) + plot.filename = "test_plot" + assert plot.filename == "test_plot" + + # Test with Path object + path_obj = Path("test_plot_path") + plot.filename = path_obj + assert plot.filename == path_obj + + # Test with Path object containing subdirectories + path_with_subdir = Path("subdir") / "test_plot" + plot.filename = path_with_subdir + assert plot.filename == path_with_subdir diff --git a/tests/unit_tests/test_plots.py b/tests/unit_tests/test_plots.py index fad574ee69..98a93e44b5 100644 --- a/tests/unit_tests/test_plots.py +++ b/tests/unit_tests/test_plots.py @@ -9,12 +9,11 @@ from openmc.plots import _SVG_COLORS @pytest.fixture(scope='module') def myplot(): - plot = openmc.Plot(name='myplot') + plot = openmc.SlicePlot(name='myplot') plot.width = (100., 100.) plot.origin = (2., 3., -10.) plot.pixels = (500, 500) plot.filename = './not-a-dir/myplot' - plot.type = 'slice' plot.basis = 'yz' plot.background = 'black' plot.background = (0, 0, 0) @@ -80,8 +79,7 @@ def test_voxel_plot(run_in_tmpdir): geometry.export_to_xml() materials = openmc.Materials() materials.export_to_xml() - vox_plot = openmc.Plot() - vox_plot.type = 'voxel' + vox_plot = openmc.VoxelPlot() vox_plot.id = 12 vox_plot.width = (1500., 1500., 1500.) vox_plot.pixels = (200, 200, 200) @@ -97,8 +95,9 @@ def test_voxel_plot(run_in_tmpdir): assert Path('h5_voxel_plot.h5').is_file() assert Path('another_test_voxel_plot.vti').is_file() - slice_plot = openmc.Plot() - with pytest.raises(ValueError): + # SlicePlot should not have to_vtk method + slice_plot = openmc.SlicePlot() + with pytest.raises(AttributeError): slice_plot.to_vtk('shimmy.vti') @@ -153,14 +152,14 @@ def test_from_geometry(): geom = openmc.Geometry(univ) for basis in ('xy', 'yz', 'xz'): - plot = openmc.Plot.from_geometry(geom, basis) + plot = openmc.SlicePlot.from_geometry(geom, basis) assert plot.origin == pytest.approx((0., 0., 0.)) assert plot.width == pytest.approx((width, width)) assert plot.basis == basis def test_highlight_domains(): - plot = openmc.Plot() + plot = openmc.SlicePlot() plot.color_by = 'material' plots = openmc.Plots([plot]) @@ -179,8 +178,8 @@ def test_xml_element(myplot): assert elem.find('pixels') is not None assert elem.find('background').text == '0 0 0' - newplot = openmc.Plot.from_xml_element(elem) - attributes = ('id', 'color_by', 'filename', 'type', 'basis', 'level', + newplot = openmc.SlicePlot.from_xml_element(elem) + attributes = ('id', 'color_by', 'filename', 'basis', 'level', 'meshlines', 'show_overlaps', 'origin', 'width', 'pixels', 'background', 'mask_background') for attr in attributes: @@ -200,11 +199,11 @@ def test_to_xml_element_proj(myprojectionplot): def test_plots(run_in_tmpdir): - p1 = openmc.Plot(name='plot1') + p1 = openmc.SlicePlot(name='plot1') p1.origin = (5., 5., 5.) p1.colors = {10: (255, 100, 0)} p1.mask_components = [2, 4, 6] - p2 = openmc.Plot(name='plot2') + p2 = openmc.SlicePlot(name='plot2') p2.origin = (-3., -3., -3.) plots = openmc.Plots([p1, p2]) assert len(plots) == 2 @@ -213,7 +212,7 @@ def test_plots(run_in_tmpdir): plots = openmc.Plots([p1, p2, p3]) assert len(plots) == 3 - p4 = openmc.Plot(name='plot4') + p4 = openmc.VoxelPlot(name='plot4') plots.append(p4) assert len(plots) == 4 @@ -230,8 +229,7 @@ def test_plots(run_in_tmpdir): def test_voxel_plot_roundtrip(): # Define a voxel plot and create XML element - plot = openmc.Plot(name='my voxel plot') - plot.type = 'voxel' + plot = openmc.VoxelPlot(name='my voxel plot') plot.filename = 'voxel1' plot.pixels = (50, 50, 50) plot.origin = (0., 0., 0.) @@ -243,7 +241,6 @@ def test_voxel_plot_roundtrip(): new_plot = plot.from_xml_element(elem) assert new_plot.name == plot.name assert new_plot.filename == plot.filename - assert new_plot.type == plot.type assert new_plot.pixels == plot.pixels assert new_plot.origin == plot.origin assert new_plot.width == plot.width @@ -288,10 +285,9 @@ def test_phong_plot_roundtrip(): def test_plot_directory(run_in_tmpdir): pwr_pin = openmc.examples.pwr_pin_cell() - # create a standard plot, expected to work - plot = openmc.Plot() + # create a standard slice plot, expected to work + plot = openmc.SlicePlot() plot.filename = 'plot_1' - plot.type = 'slice' plot.pixels = (10, 10) plot.color_by = 'material' plot.width = (100., 100.) diff --git a/tests/unit_tests/test_r2s.py b/tests/unit_tests/test_r2s.py new file mode 100644 index 0000000000..a94f85c8c0 --- /dev/null +++ b/tests/unit_tests/test_r2s.py @@ -0,0 +1,152 @@ +from pathlib import Path + +import pytest +import openmc +from openmc.deplete import Chain, R2SManager + + +@pytest.fixture +def simple_model_and_mesh(tmp_path): + # Define two materials: water and Ni + h2o = openmc.Material() + h2o.add_nuclide("H1", 2.0) + h2o.add_nuclide("O16", 1.0) + h2o.set_density("g/cm3", 1.0) + nickel = openmc.Material() + nickel.add_element("Ni", 1.0) + nickel.set_density("g/cm3", 4.0) + + # Geometry: two half-spaces split by x=0 plane + left = openmc.XPlane(0.0) + x_min = openmc.XPlane(-10.0, boundary_type='vacuum') + x_max = openmc.XPlane(10.0, boundary_type='vacuum') + y_min = openmc.YPlane(-10.0, boundary_type='vacuum') + y_max = openmc.YPlane(10.0, boundary_type='vacuum') + z_min = openmc.ZPlane(-10.0, boundary_type='vacuum') + z_max = openmc.ZPlane(10.0, boundary_type='vacuum') + + c1 = openmc.Cell(fill=h2o, region=+x_min & -left & +y_min & -y_max & +z_min & -z_max) + c2 = openmc.Cell(fill=nickel, region=+left & -x_max & +y_min & -y_max & +z_min & -z_max) + c1.volume = 4000.0 + c2.volume = 4000.0 + geometry = openmc.Geometry([c1, c2]) + + # Simple settings with a point source + settings = openmc.Settings() + settings.batches = 10 + settings.particles = 1000 + settings.run_mode = 'fixed source' + settings.source = openmc.IndependentSource() + model = openmc.Model(geometry, settings=settings) + + mesh = openmc.RegularMesh() + mesh.lower_left = (-10.0, -10.0, -10.0) + mesh.upper_right = (10.0, 10.0, 10.0) + mesh.dimension = (1, 1, 1) + return model, (c1, c2), mesh + + +def test_r2s_mesh_expected_output(simple_model_and_mesh, tmp_path): + model, (c1, c2), mesh = simple_model_and_mesh + + # Use mesh-based domains + r2s = R2SManager(model, mesh) + + # Use custom reduced chain file for Ni + chain = Chain.from_xml(Path(__file__).parents[1] / "chain_ni.xml") + + # Run R2S calculation + outdir = r2s.run( + timesteps=[(1.0, 'd')], + source_rates=[1.0], + photon_time_indices=[1], + output_dir=tmp_path, + chain_file=chain, + ) + + # Check directories and files exist + nt = Path(outdir) / 'neutron_transport' + assert (nt / 'fluxes.npy').exists() + assert (nt / 'micros.h5').exists() + assert (nt / 'mesh_material_volumes.npz').exists() + act = Path(outdir) / 'activation' + assert (act / 'depletion_results.h5').exists() + pt = Path(outdir) / 'photon_transport' + assert (pt / 'tally_ids.json').exists() + assert (pt / 'time_1' / 'statepoint.10.h5').exists() + + # Basic results structure checks + assert len(r2s.results['fluxes']) == 2 + assert len(r2s.results['micros']) == 2 + assert len(r2s.results['mesh_material_volumes']) == 2 + assert len(r2s.results['activation_materials']) == 2 + assert len(r2s.results['depletion_results']) == 2 + + # Check activation materials + amats = r2s.results['activation_materials'] + assert all(m.depletable for m in amats) + # Volumes preserved + assert {m.volume for m in amats} == {c1.volume, c2.volume} + + # Check loading results + r2s_loaded = R2SManager(model, mesh) + r2s_loaded.load_results(outdir) + assert len(r2s_loaded.results['fluxes']) == 2 + assert len(r2s_loaded.results['micros']) == 2 + assert len(r2s_loaded.results['mesh_material_volumes']) == 2 + assert len(r2s_loaded.results['activation_materials']) == 2 + assert len(r2s_loaded.results['depletion_results']) == 2 + + +def test_r2s_cell_expected_output(simple_model_and_mesh, tmp_path): + model, (c1, c2), _ = simple_model_and_mesh + + # Use cell-based domains + r2s = R2SManager(model, [c1, c2]) + + # Use custom reduced chain file for Ni + chain = Chain.from_xml(Path(__file__).parents[1] / "chain_ni.xml") + + # Run R2S calculation + bounding_boxes = {c1.id: c1.bounding_box, c2.id: c2.bounding_box} + outdir = r2s.run( + timesteps=[(1.0, 'd')], + source_rates=[1.0], + photon_time_indices=[1], + output_dir=tmp_path, + bounding_boxes=bounding_boxes, + chain_file=chain + ) + + # Check directories and files exist + nt = Path(outdir) / 'neutron_transport' + assert (nt / 'fluxes.npy').exists() + assert (nt / 'micros.h5').exists() + act = Path(outdir) / 'activation' + assert (act / 'depletion_results.h5').exists() + pt = Path(outdir) / 'photon_transport' + assert (pt / 'tally_ids.json').exists() + assert (pt / 'time_1' / 'statepoint.10.h5').exists() + + # Basic results structure checks + assert len(r2s.results['fluxes']) == 2 + assert len(r2s.results['micros']) == 2 + assert len(r2s.results['activation_materials']) == 2 + assert len(r2s.results['depletion_results']) == 2 + + # Check activation materials + amats = r2s.results['activation_materials'] + assert all(m.depletable for m in amats) + # Names include cell IDs + assert any(f"Cell {c1.id}" in m.name for m in amats) + assert any(f"Cell {c2.id}" in m.name for m in amats) + # Volumes preserved + assert {m.volume for m in amats} == {c1.volume, c2.volume} + + # Check loading results + r2s_loaded = R2SManager(model, [c1, c2]) + r2s_loaded.load_results(outdir) + assert len(r2s_loaded.results['fluxes']) == 2 + assert len(r2s_loaded.results['micros']) == 2 + assert len(r2s_loaded.results['activation_materials']) == 2 + assert len(r2s_loaded.results['depletion_results']) == 2 diff --git a/tests/unit_tests/test_region.py b/tests/unit_tests/test_region.py index cbcd198312..cb9fa171bb 100644 --- a/tests/unit_tests/test_region.py +++ b/tests/unit_tests/test_region.py @@ -248,6 +248,10 @@ def test_plot(): c_before = openmc.Cell() region.plot() + # Close plot to avoid warning + import matplotlib.pyplot as plt + plt.close() + # Ensure that calling plot doesn't affect cell ID space c_after = openmc.Cell() assert c_after.id - 1 == c_before.id diff --git a/tests/unit_tests/test_settings.py b/tests/unit_tests/test_settings.py index 7f202bcdc7..fe618fd2d6 100644 --- a/tests/unit_tests/test_settings.py +++ b/tests/unit_tests/test_settings.py @@ -59,15 +59,28 @@ def test_export_to_xml(run_in_tmpdir): s.electron_treatment = 'led' s.write_initial_source = True s.weight_window_checkpoints = {'surface': True, 'collision': False} + source_region_mesh = openmc.RegularMesh() + source_region_mesh.dimension = [2, 2, 2] + source_region_mesh.lower_left = [-2, -2, -2] + source_region_mesh.upper_right = [2, 2, 2] + root_universe = openmc.Universe() s.random_ray = { 'distance_inactive': 10.0, 'distance_active': 100.0, 'ray_source': openmc.IndependentSource( space=openmc.stats.Box((-1., -1., -1.), (1., 1., 1.)) - ) + ), + 'source_region_meshes': [(source_region_mesh, [root_universe])], + 'volume_estimator': 'hybrid', + 'source_shape': 'linear', + 'volume_normalized_flux_tallies': True, + 'adjoint': False, + 'sample_method': 'halton' } s.max_particle_events = 100 + s.max_secondaries = 1_000_000 s.source_rejection_fraction = 0.01 + s.free_gas_threshold = 800.0 # Make sure exporting XML works s.export_to_xml() @@ -144,4 +157,18 @@ def test_export_to_xml(run_in_tmpdir): assert s.random_ray['distance_active'] == 100.0 assert s.random_ray['ray_source'].space.lower_left == [-1., -1., -1.] assert s.random_ray['ray_source'].space.upper_right == [1., 1., 1.] + assert 'source_region_meshes' in s.random_ray + assert len(s.random_ray['source_region_meshes']) == 1 + mesh_and_domains = s.random_ray['source_region_meshes'][0] + recovered_mesh = mesh_and_domains[0] + assert recovered_mesh.dimension == (2, 2, 2) + assert recovered_mesh.lower_left == [-2., -2., -2.] + assert recovered_mesh.upper_right == [2., 2., 2.] + assert s.random_ray['volume_estimator'] == 'hybrid' + assert s.random_ray['source_shape'] == 'linear' + assert s.random_ray['volume_normalized_flux_tallies'] + assert not s.random_ray['adjoint'] + assert s.random_ray['sample_method'] == 'halton' + assert s.max_secondaries == 1_000_000 assert s.source_rejection_fraction == 0.01 + assert s.free_gas_threshold == 800.0 diff --git a/tests/unit_tests/test_slice_voxel_plots.py b/tests/unit_tests/test_slice_voxel_plots.py new file mode 100644 index 0000000000..48ca31b7a9 --- /dev/null +++ b/tests/unit_tests/test_slice_voxel_plots.py @@ -0,0 +1,273 @@ +"""Tests for SlicePlot and VoxelPlot classes + +This module tests the functionality of the new SlicePlot and VoxelPlot +classes that replace the legacy Plot class. +""" +import warnings + +import pytest +import openmc + + +def test_slice_plot_initialization(): + """Test SlicePlot initialization with defaults""" + plot = openmc.SlicePlot() + assert plot.width == [4.0, 4.0] + assert plot.pixels == [400, 400] + assert plot.basis == 'xy' + assert plot.origin == [0., 0., 0.] + + +def test_slice_plot_width_validation(): + """Test that SlicePlot only accepts 2 values for width""" + plot = openmc.SlicePlot() + + # Should accept 2 values + plot.width = [10.0, 20.0] + assert plot.width == [10.0, 20.0] + + # Should reject 1 value + with pytest.raises(ValueError, match='must be of length "2"'): + plot.width = [10.0] + + # Should reject 3 values + with pytest.raises(ValueError, match='must be of length "2"'): + plot.width = [10.0, 20.0, 30.0] + + +def test_slice_plot_pixels_validation(): + """Test that SlicePlot only accepts 2 values for pixels""" + plot = openmc.SlicePlot() + + # Should accept 2 values + plot.pixels = [100, 200] + assert plot.pixels == [100, 200] + + # Should reject 1 value + with pytest.raises(ValueError, match='must be of length "2"'): + plot.pixels = [100] + + # Should reject 3 values + with pytest.raises(ValueError, match='must be of length "2"'): + plot.pixels = [100, 200, 300] + + +def test_slice_plot_basis(): + """Test that SlicePlot has basis attribute""" + plot = openmc.SlicePlot() + + # Test all valid basis values + for basis in ['xy', 'xz', 'yz']: + plot.basis = basis + assert plot.basis == basis + + # Test invalid basis + with pytest.raises(ValueError): + plot.basis = 'invalid' + + +def test_slice_plot_meshlines(): + """Test that SlicePlot has meshlines attribute""" + plot = openmc.SlicePlot() + + meshlines = { + 'type': 'tally', + 'id': 1, + 'linewidth': 2, + 'color': (255, 0, 0) + } + plot.meshlines = meshlines + assert plot.meshlines == meshlines + + +def test_slice_plot_xml_roundtrip(): + """Test SlicePlot XML serialization and deserialization""" + plot = openmc.SlicePlot(name='test_slice') + plot.width = [15.0, 25.0] + plot.pixels = [150, 250] + plot.basis = 'xz' + plot.origin = [1.0, 2.0, 3.0] + plot.color_by = 'material' + plot.filename = 'test_plot' + + # Convert to XML and back + elem = plot.to_xml_element() + new_plot = openmc.SlicePlot.from_xml_element(elem) + + # Check all attributes preserved + assert new_plot.name == plot.name + assert new_plot.width == pytest.approx(plot.width) + assert new_plot.pixels == tuple(plot.pixels) + assert new_plot.basis == plot.basis + assert new_plot.origin == pytest.approx(plot.origin) + assert new_plot.color_by == plot.color_by + assert new_plot.filename == plot.filename + + +def test_slice_plot_from_geometry(): + """Test creating SlicePlot from geometry""" + # Create simple geometry + s = openmc.Sphere(r=10.0, boundary_type='vacuum') + c = openmc.Cell(region=-s) + univ = openmc.Universe(cells=[c]) + geom = openmc.Geometry(univ) + + # Test all basis options + for basis in ['xy', 'xz', 'yz']: + plot = openmc.SlicePlot.from_geometry(geom, basis=basis) + assert plot.basis == basis + assert plot.width == pytest.approx([20.0, 20.0]) + assert plot.origin == pytest.approx([0.0, 0.0, 0.0]) + + +def test_voxel_plot_initialization(): + """Test VoxelPlot initialization with defaults""" + plot = openmc.VoxelPlot() + assert plot.width == [4.0, 4.0, 4.0] + assert plot.pixels == [400, 400, 400] + assert plot.origin == [0., 0., 0.] + + +def test_voxel_plot_width_validation(): + """Test that VoxelPlot only accepts 3 values for width""" + plot = openmc.VoxelPlot() + + # Should accept 3 values + plot.width = [10.0, 20.0, 30.0] + assert plot.width == [10.0, 20.0, 30.0] + + # Should reject 2 values + with pytest.raises(ValueError, match='must be of length "3"'): + plot.width = [10.0, 20.0] + + # Should reject 1 value + with pytest.raises(ValueError, match='must be of length "3"'): + plot.width = [10.0] + + +def test_voxel_plot_pixels_validation(): + """Test that VoxelPlot only accepts 3 values for pixels""" + plot = openmc.VoxelPlot() + + # Should accept 3 values + plot.pixels = [100, 200, 300] + assert plot.pixels == [100, 200, 300] + + # Should reject 2 values + with pytest.raises(ValueError, match='must be of length "3"'): + plot.pixels = [100, 200] + + # Should reject 1 value + with pytest.raises(ValueError, match='must be of length "3"'): + plot.pixels = [100] + + +def test_voxel_plot_xml_roundtrip(): + """Test VoxelPlot XML serialization and deserialization""" + plot = openmc.VoxelPlot(name='test_voxel') + plot.width = [10.0, 20.0, 30.0] + plot.pixels = [100, 200, 300] + plot.origin = [1.0, 2.0, 3.0] + plot.color_by = 'cell' + plot.filename = 'voxel_plot' + + # Convert to XML and back + elem = plot.to_xml_element() + new_plot = openmc.VoxelPlot.from_xml_element(elem) + + # Check all attributes preserved + assert new_plot.name == plot.name + assert new_plot.width == pytest.approx(plot.width) + assert new_plot.pixels == tuple(plot.pixels) + assert new_plot.origin == pytest.approx(plot.origin) + assert new_plot.color_by == plot.color_by + assert new_plot.filename == plot.filename + + +def test_plot_deprecation_warning(): + """Test that Plot class raises deprecation warning""" + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + openmc.Plot() + + assert len(w) == 1 + assert issubclass(w[0].category, FutureWarning) + assert "deprecated" in str(w[0].message).lower() + + +def test_plot_returns_slice_plot(): + """Test that Plot() returns a SlicePlot instance""" + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + plot = openmc.Plot() + + # Should be an actual SlicePlot instance + assert isinstance(plot, openmc.SlicePlot) + + +def test_plot_type_setter_raises_error(): + """Test that setting plot.type raises a helpful error""" + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + plot = openmc.Plot() + + with pytest.raises(TypeError, match="no longer supported"): + plot.type = 'voxel' + + with pytest.raises(TypeError, match="no longer supported"): + plot.type = 'slice' + + +def test_plot_type_getter_warns(): + """Test that getting plot.type raises a deprecation warning""" + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + plot = openmc.Plot() + + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + plot_type = plot.type + + assert plot_type == 'slice' + assert len(w) == 1 + assert issubclass(w[0].category, FutureWarning) + assert "deprecated" in str(w[0].message).lower() + + +def test_plots_collection_mixed_types(): + """Test Plots collection with different plot types""" + slice_plot = openmc.SlicePlot(name='slice') + voxel_plot = openmc.VoxelPlot(name='voxel') + wireframe_plot = openmc.WireframeRayTracePlot(name='wireframe') + + plots = openmc.Plots([slice_plot, voxel_plot, wireframe_plot]) + + assert len(plots) == 3 + assert isinstance(plots[0], openmc.SlicePlot) + assert isinstance(plots[1], openmc.VoxelPlot) + assert isinstance(plots[2], openmc.WireframeRayTracePlot) + + +def test_plots_collection_xml_roundtrip(run_in_tmpdir): + """Test XML export and import with new plot types""" + s1 = openmc.SlicePlot(name='slice1') + s1.width = [10.0, 20.0] + s1.basis = 'xz' + + v1 = openmc.VoxelPlot(name='voxel1') + v1.width = [10.0, 20.0, 30.0] + + plots = openmc.Plots([s1, v1]) + plots.export_to_xml() + + # Read back + new_plots = openmc.Plots.from_xml() + + assert len(new_plots) == 2 + assert isinstance(new_plots[0], openmc.SlicePlot) + assert isinstance(new_plots[1], openmc.VoxelPlot) + assert new_plots[0].name == 'slice1' + assert new_plots[1].name == 'voxel1' + assert new_plots[0].basis == 'xz' + assert new_plots[0].width == pytest.approx([10.0, 20.0]) + assert new_plots[1].width == pytest.approx([10.0, 20.0, 30.0]) diff --git a/tests/unit_tests/test_statepoint.py b/tests/unit_tests/test_statepoint.py new file mode 100644 index 0000000000..7ffaf7ec2c --- /dev/null +++ b/tests/unit_tests/test_statepoint.py @@ -0,0 +1,65 @@ +import openmc + + +def test_get_tally_filter_type(run_in_tmpdir): + """Test various ways of retrieving tallies from a StatePoint object.""" + + mat = openmc.Material() + mat.add_nuclide("H1", 1.0) + mat.set_density("g/cm3", 10.0) + + sphere = openmc.Sphere(r=10.0, boundary_type="vacuum") + cell = openmc.Cell(fill=mat, region=-sphere) + geometry = openmc.Geometry([cell]) + + settings = openmc.Settings() + settings.particles = 10 + settings.batches = 2 + settings.run_mode = "fixed source" + + reg_mesh = openmc.RegularMesh().from_domain(cell) + tally1 = openmc.Tally(tally_id=1) + mesh_filter = openmc.MeshFilter(reg_mesh) + tally1.filters = [mesh_filter] + tally1.scores = ["flux"] + + tally2 = openmc.Tally(tally_id=2, name="heating tally") + cell_filter = openmc.CellFilter(cell) + tally2.filters = [cell_filter] + tally2.scores = ["heating"] + + tallies = openmc.Tallies([tally1, tally2]) + model = openmc.Model( + geometry=geometry, materials=[mat], settings=settings, tallies=tallies + ) + + sp_filename = model.run() + + sp = openmc.StatePoint(sp_filename) + + tally_found = sp.get_tally(filter_type=openmc.MeshFilter) + assert tally_found.id == 1 + + tally_found = sp.get_tally(filter_type=openmc.CellFilter) + assert tally_found.id == 2 + + tally_found = sp.get_tally(filters=[mesh_filter]) + assert tally_found.id == 1 + + tally_found = sp.get_tally(filters=[cell_filter]) + assert tally_found.id == 2 + + tally_found = sp.get_tally(scores=["heating"]) + assert tally_found.id == 2 + + tally_found = sp.get_tally(name="heating tally") + assert tally_found.id == 2 + + tally_found = sp.get_tally(name=None) + assert tally_found.id == 1 + + tally_found = sp.get_tally(id=1) + assert tally_found.id == 1 + + tally_found = sp.get_tally(id=2) + assert tally_found.id == 2 diff --git a/tests/unit_tests/test_statepoint_batches.py b/tests/unit_tests/test_statepoint_batches.py new file mode 100644 index 0000000000..bf54e18786 --- /dev/null +++ b/tests/unit_tests/test_statepoint_batches.py @@ -0,0 +1,26 @@ +from pathlib import Path + +import openmc + + +def test_statepoint_batches(run_in_tmpdir): + # Create a minimal model + mat = openmc.Material() + mat.add_nuclide('U235', 1.0) + mat.set_density('g/cm3', 4.5) + sphere = openmc.Sphere(r=10.0, boundary_type='vacuum') + cell = openmc.Cell(fill=mat, region=-sphere) + model = openmc.Model() + model.geometry = openmc.Geometry([cell]) + model.settings.batches = 10 + model.settings.inactive = 5 + model.settings.particles = 100 + + # Specify when statepoints should be written + model.settings.statepoint = {'batches': [3, 6, 9]} + + # Run model and ensure that statepoints are created + model.run() + sp_files = ['statepoint.03.h5', 'statepoint.06.h5', 'statepoint.09.h5'] + for f in sp_files: + assert Path(f).is_file() diff --git a/tests/unit_tests/test_stats.py b/tests/unit_tests/test_stats.py index 386181f34d..998d4b984c 100644 --- a/tests/unit_tests/test_stats.py +++ b/tests/unit_tests/test_stats.py @@ -16,6 +16,7 @@ def assert_sample_mean(samples, expected_mean): assert np.abs(expected_mean - samples.mean()) < 4*std_dev +@pytest.mark.flaky(reruns=1) def test_discrete(): x = [0.0, 1.0, 10.0] p = [0.3, 0.2, 0.5] @@ -104,6 +105,7 @@ def test_clip_discrete(): d.clip(5) +@pytest.mark.flaky(reruns=1) def test_uniform(): a, b = 10.0, 20.0 d = openmc.stats.Uniform(a, b) @@ -127,6 +129,7 @@ def test_uniform(): assert_sample_mean(samples, exp_mean) +@pytest.mark.flaky(reruns=1) def test_powerlaw(): a, b, n = 10.0, 100.0, 2.0 d = openmc.stats.PowerLaw(a, b, n) @@ -148,6 +151,7 @@ def test_powerlaw(): assert_sample_mean(samples, exp_mean) +@pytest.mark.flaky(reruns=1) def test_maxwell(): theta = 1.2895e6 d = openmc.stats.Maxwell(theta) @@ -171,6 +175,7 @@ def test_maxwell(): assert samples_2.mean() != samples.mean() +@pytest.mark.flaky(reruns=1) def test_watt(): a, b = 0.965e6, 2.29e-6 d = openmc.stats.Watt(a, b) @@ -194,6 +199,7 @@ def test_watt(): assert_sample_mean(samples, exp_mean) +@pytest.mark.flaky(reruns=1) def test_tabular(): # test linear-linear sampling x = np.array([0.0, 5.0, 7.0, 10.0]) @@ -270,6 +276,7 @@ def test_legendre(): d.to_xml_element('distribution') +@pytest.mark.flaky(reruns=1) def test_mixture(): d1 = openmc.stats.Uniform(0, 5) d2 = openmc.stats.Uniform(3, 7) @@ -425,6 +432,7 @@ def test_point(): assert d.xyz == pytest.approx(p) +@pytest.mark.flaky(reruns=1) def test_normal(): mean = 10.0 std_dev = 2.0 @@ -444,6 +452,7 @@ def test_normal(): assert_sample_mean(samples, mean) +@pytest.mark.flaky(reruns=1) def test_muir(): mean = 10.0 mass = 5.0 @@ -463,6 +472,7 @@ def test_muir(): assert_sample_mean(samples, mean) +@pytest.mark.flaky(reruns=1) def test_combine_distributions(): # Combine two discrete (same data as in test_merge_discrete) x1 = [0.0, 1.0, 10.0] @@ -506,3 +516,33 @@ def test_combine_distributions(): # uncertainty of the expected value samples = combined.sample(10_000) assert_sample_mean(samples, 0.25) + +def test_reference_vwu_projection(): + """When a non-orthogonal vector is provided, the setter should project out + any component along reference_uvw so the stored vector is orthogonal. + """ + pa = openmc.stats.PolarAzimuthal() # default reference_uvw == (0, 0, 1) + + # Provide a vector that is not orthogonal to (0,0,1) + pa.reference_vwu = (2.0, 0.5, 0.3) + + reference_v = np.asarray(pa.reference_vwu) + reference_u = np.asarray(pa.reference_uvw) + + # reference_v should be orthogonal to reference_u + assert abs(np.dot(reference_v, reference_u)) < 1e-6 + + +def test_reference_vwu_normalization(): + """When a non-normalized vector is provided, the setter should normalize + the projected vector to unit length. + """ + pa = openmc.stats.PolarAzimuthal() # default reference_uvw == (0, 0, 1) + + # Provide a vector that is neither orthogonal to (0,0,1) nor unit-length + pa.reference_vwu = (2.0, 0.5, 0.3) + + reference_v = np.asarray(pa.reference_vwu) + + # reference_v should be unit length + assert np.isclose(np.linalg.norm(reference_v), 1.0, atol=1e-12) diff --git a/tests/unit_tests/test_tallies.py b/tests/unit_tests/test_tallies.py index c38f067d58..7b1bf0a2fe 100644 --- a/tests/unit_tests/test_tallies.py +++ b/tests/unit_tests/test_tallies.py @@ -1,6 +1,8 @@ +from math import sqrt import numpy as np import pytest import openmc +import scipy.stats as sps def test_xml_roundtrip(run_in_tmpdir): @@ -163,3 +165,214 @@ def test_tally_application(sphere_model, run_in_tmpdir): assert (sp_tally.std_dev == tally.std_dev).all() assert (sp_tally.mean == tally.mean).all() assert sp_tally.nuclides == tally.nuclides + +def _tally_from_data(x, *, higher_moments=True, normality=True): + t = openmc.Tally() + t.scores = ["flux"] # 1 score + t.nuclides = [openmc.Nuclide("H1")] # 1 nuclide + t._sp_filename = "dummy.h5" # mark "results available" + t._results_read = True # don't try to read from disk + t._num_realizations = int(len(x)) # n + t.higher_moments = bool(higher_moments) + + x = np.asarray(x, dtype=float) + # (num_filter_bins=1, num_nuclides=1, num_scores=1) -> (1,1,1) arrays + t._sum = np.array([[[np.sum(x)]]], dtype=float) + t._sum_sq = np.array([[[np.sum(x**2)]]], dtype=float) + if higher_moments: + t._sum_third = np.array([[[np.sum(x**3)]]], dtype=float) + t._sum_fourth = np.array([[[np.sum(x**4)]]], dtype=float) + return t + +@pytest.mark.parametrize( + "x, skew_true, kurt_true", + [ # Rademacher distribution + (np.array([1.0, -1.0] * 200), 0.0, 1.0), + # Two-point {0,3} with p(0)=3/4, p(3)=1/4 + (np.concatenate([np.zeros(600), np.full(200, 3.0)]), 2.0 / sqrt(3.0), 7.0 / 3.0), + # Bernoulli distribution + (np.concatenate([np.ones(300), np.zeros(700)]), (1 - 2 * 0.3) / sqrt(0.3 * 0.7), (1 - 3 * 0.3 + 3 * 0.3**2) / (0.3 * 0.7)), + ], +) +def test_b1_b2_analytical_against_tally(x, skew_true, kurt_true): + t = _tally_from_data(x, higher_moments=True, normality=False) + + g1 = t.skew(bias=True)[0, 0, 0] + b2 = t.kurtosis(bias=True, fisher=False)[0, 0, 0] + + assert np.isclose(g1, skew_true, rtol=0, atol=1e-12) + assert np.isclose(b2, kurt_true, rtol=0, atol=1e-12) + +@pytest.mark.parametrize( + "draw, skew_true, kurt_true", + [(lambda rng, n: rng.normal(0, 1, n), 0.0, 3.0), # Normal + (lambda rng, n: rng.random(n), 0.0, 1.8), # Uniform(0,1) + (lambda rng, n: rng.exponential(1.0, n), 2.0, 9.0), # Exp(1) + (lambda rng, n: (rng.random(n) < 0.3).astype(float), + (1 - 2 * 0.3) / sqrt(0.3 * 0.7), + (1 - 3 * 0.3 + 3 * 0.3**2) / (0.3 * 0.7),),],) + +def test_b1_b2_scipy_and_theory(draw, skew_true, kurt_true): + rng = np.random.default_rng(12345) + N = 200_000 + x = draw(rng, N) + + # Tally outputs + t = _tally_from_data(x, higher_moments=True, normality=False) + g1_t = t.skew(bias=True)[0, 0, 0] + b2_t = t.kurtosis(bias=True, fisher=False)[0, 0, 0] + + # SciPy (population, bias=True to match population-moment style) + skew_sp = sps.skew(x, bias=True) + kurt_sp = sps.kurtosis(x, fisher=False, bias=True) + + # Compare to SciPy numerically + assert np.isclose(g1_t, skew_sp, rtol=0, atol=5e-3) + assert np.isclose(b2_t, kurt_sp, rtol=0, atol=5e-3) + + # Compare to analytical targets with size-dependent tolerances + tol_skew = 0.02 if abs(skew_true) < 0.5 else 0.05 + tol_kurt = 0.03 if kurt_true < 4 else 0.1 + assert abs(g1_t - skew_true) < tol_skew + assert abs(b2_t - kurt_true) < tol_kurt + + +def test_kurtosis_bias_fisher_combinations(): + """Test that all combinations of bias and fisher match scipy.stats.kurtosis""" + rng = np.random.default_rng(42) + x = rng.normal(0, 1, 10000) + + t = _tally_from_data(x, higher_moments=True, normality=False) # Test all four combinations + # 1. bias=True, fisher=False (Pearson's kurtosis, b2) + b2_tally = t.kurtosis(bias=True, fisher=False)[0, 0, 0] + b2_scipy = sps.kurtosis(x, fisher=False, bias=True) + assert np.isclose(b2_tally, b2_scipy, rtol=0, atol=1e-10) + assert np.isclose(b2_tally, 3.0, rtol=0.05, atol=0.1) # Should be ~3 for normal + + # 2. bias=True, fisher=True (excess kurtosis, g2) + g2_tally = t.kurtosis(bias=True, fisher=True)[0, 0, 0] + g2_scipy = sps.kurtosis(x, fisher=True, bias=True) + assert np.isclose(g2_tally, g2_scipy, rtol=0, atol=1e-10) + assert np.isclose(g2_tally, 0.0, rtol=0, atol=0.1) # Should be ~0 for normal + assert np.isclose(g2_tally, b2_tally - 3.0, rtol=0, atol=1e-10) # g2 = b2 - 3 + + # 3. bias=False, fisher=True (adjusted excess kurtosis, G2) + G2_tally = t.kurtosis(bias=False, fisher=True)[0, 0, 0] + G2_tally_default = t.kurtosis()[0, 0, 0] # Should be same as default + G2_scipy = sps.kurtosis(x, fisher=True, bias=False) + assert np.isclose(G2_tally, G2_tally_default, rtol=0, atol=1e-10) + assert np.isclose(G2_tally, G2_scipy, rtol=0, atol=1e-10) + assert np.isclose(G2_tally, 0.0, rtol=0, atol=0.1) # Should be ~0 for normal + + # 4. bias=False, fisher=False (adjusted Pearson's kurtosis) + adj_b2_tally = t.kurtosis(bias=False, fisher=False)[0, 0, 0] + adj_b2_scipy = sps.kurtosis(x, fisher=False, bias=False) + assert np.isclose(adj_b2_tally, adj_b2_scipy, rtol=0, atol=1e-10) + assert np.isclose(adj_b2_tally, 3.0, rtol=0.05, atol=0.1) # Should be ~3 for normal + assert np.isclose(adj_b2_tally, G2_tally + 3.0, rtol=0, atol=1e-10) # adj_b2 = G2 + 3 + + +def test_ztests_scipy_comparison(): + rng = np.random.default_rng(987) + x_norm = rng.normal(size=50_000) + x_exp = rng.exponential(size=50_000) + + # -------- Normal dataset (should not reject) -------- + t0 = _tally_from_data(x_norm, higher_moments=True, normality=True) + Zb1_0, p_skew_0 = t0.skewtest(alternative="two-sided") + Zb2_0, p_kurt_0 = t0.kurtosistest(alternative="two-sided") + K2_0, p_omni_0 = t0.normaltest(alternative="two-sided") + + Zb1_0 = Zb1_0.ravel()[0] + p_skew_0 = p_skew_0.ravel()[0] + Zb2_0 = Zb2_0.ravel()[0] + p_kurt_0 = p_kurt_0.ravel()[0] + K2_0 = K2_0.ravel()[0] + p_omni_0 = p_omni_0.ravel()[0] + + z_skew_sp0, p_skew_sp0 = sps.skewtest(x_norm) + z_kurt_sp0, p_kurt_sp0 = sps.kurtosistest(x_norm) + k2_sp0, p_omni_sp0 = sps.normaltest(x_norm) + + assert np.isclose(Zb1_0, z_skew_sp0, atol=0.15) + assert np.isclose(Zb2_0, z_kurt_sp0, atol=0.15) + assert np.isclose(K2_0, k2_sp0, atol=0.30) + assert np.isclose(p_skew_0, p_skew_sp0, atol=5e-3) + assert np.isclose(p_kurt_0, p_kurt_sp0, atol=5e-3) + assert np.isclose(p_omni_0, p_omni_sp0, atol=5e-3) + + # -------- Exponential dataset (should strongly reject) -------- + t1 = _tally_from_data(x_exp, higher_moments=True, normality=True) + + Zb1_1, p_skew_1 = t1.skewtest(alternative="two-sided") + Zb2_1, p_kurt_1 = t1.kurtosistest(alternative="two-sided") + K2_1, p_omni_1 = t1.normaltest(alternative="two-sided") + + Zb1_1 = Zb1_1.ravel()[0] + p_skew_1 = p_skew_1.ravel()[0] + Zb2_1 = Zb2_1.ravel()[0] + p_kurt_1 = p_kurt_1.ravel()[0] + K2_1 = K2_1.ravel()[0] + p_omni_1 = p_omni_1.ravel()[0] + + z_skew_sp1, p_skew_sp1 = sps.skewtest(x_exp) + z_kurt_sp1, p_kurt_sp1 = sps.kurtosistest(x_exp) + k2_sp1, p_omni_sp1 = sps.normaltest(x_exp) + + # Both pipelines should reject very strongly + assert p_skew_1 < 1e-6 and p_skew_sp1 < 1e-6 + assert p_kurt_1 < 1e-6 and p_kurt_sp1 < 1e-6 + assert p_omni_1 < 1e-6 and p_omni_sp1 < 1e-6 + + # Right-skewed and heavy-tailed → large positive Z-statistics + assert Zb1_1 > 30 and z_skew_sp1 > 30 + assert Zb2_1 > 30 and z_kurt_sp1 > 30 + assert K2_1 > 2000 and k2_sp1 > 2000 + +def test_vov_stochastic(sphere_model, run_in_tmpdir): + tally = openmc.Tally(name="test tally") + ef = openmc.EnergyFilter([0.0, 0.1, 1.0, 10.0e6]) + mesh = openmc.RegularMesh.from_domain(sphere_model.geometry, (2, 2, 2)) + mf = openmc.MeshFilter(mesh) + tally.filters = [ef, mf] + tally.scores = ["flux", "absorption", "fission", "scatter"] + tally.higher_moments = True + sphere_model.tallies = [tally] + + sp_file = sphere_model.run(apply_tally_results=True) + + assert tally._mean is None + assert tally._std_dev is None + assert tally._sum is None + assert tally._sum_sq is None + assert tally._sum_third is None + assert tally._sum_fourth is None + assert tally._num_realizations == 0 + assert tally._sp_filename == sp_file + + with openmc.StatePoint(sp_file) as sp: + assert tally in sp.tallies.values() + sp_tally = sp.tallies[tally.id] + + assert np.all(sp_tally.std_dev == tally.std_dev) + assert np.all(sp_tally.mean == tally.mean) + assert np.all(sp_tally.vov == tally.vov) + assert sp_tally.nuclides == tally.nuclides + + n = sp_tally.num_realizations + mean = sp_tally.mean + sum_ = sp_tally._sum + sum_sq = sp_tally._sum_sq + sum_third = sp_tally._sum_third + sum_fourth = sp_tally._sum_fourth + + expected_vov = np.zeros_like(mean) + nonzero = np.abs(mean) > 0 + + num = (sum_fourth - (4.0*sum_third*sum_)/n + (6.0*sum_sq*sum_**2)/(n**2) + - (3.0*sum_**4)/(n**3)) + den = (sum_sq - (1.0/n)*sum_**2)**2 + + expected_vov[nonzero] = num[nonzero]/den[nonzero] - 1.0/n + + assert np.allclose(expected_vov, sp_tally.vov, rtol=1e-7, atol=0.0) diff --git a/tests/unit_tests/test_universe.py b/tests/unit_tests/test_universe.py index 46d4ec3f73..efe8552a64 100644 --- a/tests/unit_tests/test_universe.py +++ b/tests/unit_tests/test_universe.py @@ -99,6 +99,10 @@ def test_plot(run_in_tmpdir, sphere_model): pixels=100, ) + # Close plots to avoid warning + import matplotlib.pyplot as plt + plt.close('all') + def test_get_nuclides(uo2): c = openmc.Cell(fill=uo2) diff --git a/tests/unit_tests/weightwindows/dagmc/__init__.py b/tests/unit_tests/weightwindows/dagmc/__init__.py new file mode 100644 index 0000000000..e69de29bb2 diff --git a/tests/unit_tests/weightwindows/dagmc/nested_shell_geometry.h5m b/tests/unit_tests/weightwindows/dagmc/nested_shell_geometry.h5m new file mode 100644 index 0000000000..af1d5563d9 Binary files /dev/null and b/tests/unit_tests/weightwindows/dagmc/nested_shell_geometry.h5m differ diff --git a/tests/unit_tests/weightwindows/dagmc/test.py b/tests/unit_tests/weightwindows/dagmc/test.py new file mode 100644 index 0000000000..ed01a93ed3 --- /dev/null +++ b/tests/unit_tests/weightwindows/dagmc/test.py @@ -0,0 +1,98 @@ +import pytest + +import openmc +import openmc.lib + +pytestmark = pytest.mark.skipif( + not openmc.lib._dagmc_enabled(), + reason="DAGMC CAD geometry is not enabled.", +) + + +def test_dagmc_weight_windows_near_boundary(run_in_tmpdir, request): + """Ensure splitting near a boundary doesn't lose particles due to + a stale DAGMC history on the particle object.""" + + # DAGMC model overview: + # * Three nested cubes; innermost cube contains a fusion neutron source. + # * Two outer cubes filled with tungsten. Weight windows defined on a mesh + # cause particles to split moving outward. + # Outer cubes are similar in size (outer slightly larger) so particles + # frequently cross the problem boundary immediately after splitting. No lost + # particles are allowed to the correct DAGMC history after splitting is used. + model = openmc.Model() + + dagmc_file = request.path.parent / 'nested_shell_geometry.h5m' + dagmc_univ = openmc.DAGMCUniverse(dagmc_file) + model.geometry = openmc.Geometry(dagmc_univ) + + tungsten = openmc.Material(name='shell') + tungsten.add_element('W', 1.0) + tungsten.set_density('g/cm3', 7.8) + materials = openmc.Materials([tungsten]) + model.materials = materials + + settings = openmc.Settings() + settings.output = {'tallies': False, 'summary': False} + + source = openmc.IndependentSource() + source.space = openmc.stats.Point((0.0, 0.0, 0.0)) + source.angle = openmc.stats.Isotropic() + source.energy = openmc.stats.Discrete([14.1e6], [1.0]) + settings.source = source + + settings.batches = 2 + settings.particles = 500 + settings.run_mode = 'fixed source' + settings.survival_biasing = False + settings.max_lost_particles = 1 + settings.max_history_splits = 10_000_000 + + settings.weight_window_checkpoints = { + 'surface': True, + 'collision': True, + } + + mesh = openmc.RegularMesh() + mesh.lower_left = (-60.0, -60.0, -60.0) + mesh.upper_right = (60.0, 60.0, 60.0) + mesh.dimension = (24, 1, 1) + + weight_windows_lower = [ + 0.030750733294361156, + 0.056110505674355333, + 0.08187875047968339, + 0.1101743496347699, + 0.13982370013053508, + 0.17443799246829372, + 0.21576286623367483, + 0.26416659508033646, + 0.318574932646899, + 0.3804031702117963, + 0.42899359749256355, + 0.4954283294279403, + 0.49999999999999994, + 0.43432341070872266, + 0.38302303850488206, + 0.32148375935490886, + 0.2637416945702018, + 0.21498369367288853, + 0.17163611765361744, + 0.13832102142074995, + 0.10717772257151495, + 0.07986176041282561, + 0.05499644859408233, + 0.03058023506703803, + ] + + weight_windows = openmc.WeightWindows( + mesh, + lower_ww_bounds=weight_windows_lower, + upper_bound_ratio=5.0, + ) + weight_windows.max_lower_bound_ratio = 1.0 + settings.weight_windows = weight_windows + settings.weight_windows_on = True + model.settings = settings + + model.run() \ No newline at end of file diff --git a/tests/unit_tests/weightwindows/test_wwinp_reader.py b/tests/unit_tests/weightwindows/test_wwinp_reader.py index 28548a4486..637463bb2e 100644 --- a/tests/unit_tests/weightwindows/test_wwinp_reader.py +++ b/tests/unit_tests/weightwindows/test_wwinp_reader.py @@ -140,4 +140,4 @@ def test_wwinp_reader_failures(wwinp_data, request): filename, expected_failure = wwinp_data with pytest.raises(expected_failure): - _ = openmc.wwinp_to_wws(request.node.path.parent / filename) + _ = openmc.WeightWindowsList.from_wwinp(request.node.path.parent / filename) diff --git a/tools/ci/gha-script.sh b/tools/ci/gha-script.sh index c0f754c32c..b40238ffb5 100755 --- a/tools/ci/gha-script.sh +++ b/tools/ci/gha-script.sh @@ -15,4 +15,7 @@ if [[ $EVENT == 'y' ]]; then fi # Run unit tests and then regression tests -pytest --cov=openmc -v $args tests/unit_tests tests/regression_tests +pytest -v $args \ + tests/test_matplotlib_import.py \ + tests/unit_tests \ + tests/regression_tests