Merge remote-tracking branch 'upstream/develop' into eq

.travis.yml

@@ -42,7 +42,7 @@ install: true
 
 before_script:
   - if [[ ! -e $HOME/nndc_hdf5/cross_sections.xml ]]; then
-      wget https://anl.box.com/shared/static/6pwyfjnufam0sb96kqwwrve6vdn8m7u4.xz -O - | tar -C $HOME -xvJ;
+      wget https://anl.box.com/shared/static/dqkwdl7o4lauo91h3mgrn9qno6a3c8mp.xz -O - | tar -C $HOME -xvJ;
     fi
   - export OPENMC_CROSS_SECTIONS=$HOME/nndc_hdf5/cross_sections.xml
 

data/get_nndc_data.py

@@ -151,5 +151,6 @@ if not response or response.lower().startswith('y'):
     env = os.environ.copy()
     env['PYTHONPATH'] = os.path.join(cwd, '..')
 
-    subprocess.call(['../scripts/openmc-ace-to-hdf5', '-d', 'nndc_hdf5']
+    subprocess.call(['../scripts/openmc-ace-to-hdf5', '-d', 'nndc_hdf5',
+                     '--fission_energy_release', 'fission_Q_data_endfb71.h5']
                     + ace_files, env=env)

docs/source/conf.py

@@ -28,6 +28,9 @@ MOCK_MODULES = ['numpy', 'numpy.polynomial', 'numpy.polynomial.polynomial',
                 'h5py', 'pandas', 'opencg']
 sys.modules.update((mod_name, MagicMock()) for mod_name in MOCK_MODULES)
 
+import numpy as np
+np.polynomial.Polynomial = MagicMock
+
 
 # If extensions (or modules to document with autodoc) are in another directory,
 # add these directories to sys.path here. If the directory is relative to the

docs/source/io_formats/fission_energy.rst

@@ -0,0 +1,53 @@
+.. _usersguide_fission_energy:
+
+==================================
+Fission Energy Release File Format
+==================================
+
+This file is a compact HDF5 representation of the ENDF MT=1, MF=458 data (see
+ENDF-102_ for details).  It gives the information needed to compute the energy
+carried away from fission reactions by each reaction product (e.g. fragment
+nuclei, neutrons) which depends on the incident neutron energy.  OpenMC is
+distributed with one of these files under
+data/fission_Q_data_endfb71.h5.  More files of this format can be created from
+ENDF files with the
+``openmc.data.write_compact_458_library`` function.  They can be read with the
+``openmc.data.FissionEnergyRelease.from_compact_hdf5`` class method.
+
+:Attributes: - **comment** (*char[]*) -- An optional text comment
+             - **component order** (*char[][]*) -- An array of strings
+               specifying the order each reaction product occurs in the data
+               arrays.  The components use the 2-3 letter abbreviations
+               specified in ENDF-102 e.g. EFR for fission fragments and ENP for
+               prompt neutrons.
+
+**/<nuclide name>/**
+    Nuclides are named by concatenating their atomic symbol and mass number. For
+    example, 'U235' or 'Pu239'.  Metastable nuclides are appended with an
+    '_m' and their metastable number.  For example, 'Am242_m1'
+
+:Datasets:
+          - **data** (*double[][][]*) -- The energy release coefficients.  The
+             first axis indexes the component type.  The second axis specifies
+             values or uncertainties.  The third axis indexes the polynomial
+             order.  If the data uses the Sher-Beck format, then the last axis
+             will have a length of one and ENDF-102 should be consulted for
+             energy dependence.  Otherwise, the data uses the Madland format
+             which is a polynomial of incident energy.
+
+             For example, if 'EFR' is given first in the **component order**
+             attribute and the data uses the Madland format, then the energy
+             released in the form of fission fragments at an incident energy
+             :math:`E` is given by
+
+             .. math::
+                \text{data}[0, 0, 0] + \text{data}[0, 0, 1] \cdot E
+                + \text{data}[0, 0, 2] \cdot E^2 + \ldots
+              
+             And its uncertainty is
+
+             .. math::
+                \text{data}[0, 1, 0] + \text{data}[0, 1, 1] \cdot E
+                + \text{data}[0, 1, 2] \cdot E^2 + \ldots
+
+.. _ENDF-102: http://www.nndc.bnl.gov/endfdocs/ENDF-102-2012.pdf

docs/source/io_formats/index.rst

@@ -15,6 +15,7 @@ Data Files
    nuclear_data
    mgxs_library
    data_wmp
+   fission_energy
 
 ------------
 Output Files

docs/source/io_formats/nuclear_data.rst

@@ -55,6 +55,36 @@ Incident Neutron Data
    from fission. It is formatted as a reaction product, described in
    :ref:`product`.
 
+**/<nuclide name>/fission_energy_release/**
+
+:Datasets: - **fragments** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of fragments as a function of incident
+             neutron energy.
+           - **prompt_neutrons** (:ref:`polynomial <1d_polynomial>` or
+             :ref:`tabulated <1d_tabulated>`) -- Energy released in the form of
+             prompt neutrons as a function of incident neutron energy.
+           - **delayed_neutrons** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of delayed neutrons as a function of incident
+             neutron energy.
+           - **prompt_photons** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of prompt photons as a function of incident
+             neutron energy.
+           - **delayed_photons** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of delayed photons as a function of incident
+             neutron energy.
+           - **betas** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of betas as a function of incident
+             neutron energy.
+           - **neutrinos** (:ref:`polynomial <1d_polynomial>`) -- Energy
+             released in the form of neutrinos as a function of incident
+             neutron energy.
+           - **q_prompt** (:ref:`polynomial <1d_polynomial>` or
+             :ref:`tabulated <1d_tabulated>`) -- The prompt fission Q-value
+             (fragments + prompt neutrons + prompt photons - incident energy)
+           - **q_recoverable** (:ref:`polynomial <1d_polynomial>` or
+             :ref:`tabulated <1d_tabulated>`) -- The recoverable fission Q-value
+             (Q_prompt + delayed neutrons + delayed photons + betas)
+
 -------------------------------
 Thermal Neutron Scattering Data
 -------------------------------
@@ -142,17 +172,19 @@ Tabulated
 :Object type: Dataset
 :Datatype: *double[2][]*
 :Description: x-values are listed first followed by corresponding y-values
-:Attributes: - **type** (*char[]*) -- 'tabulated'
+:Attributes: - **type** (*char[]*) -- 'Tabulated1D'
              - **breakpoints** (*int[]*) -- Region breakpoints
              - **interpolation** (*int[]*) -- Region interpolation codes
 
+.. _1d_polynomial:
+
 Polynomial
 ----------
 
 :Object type: Dataset
 :Datatype: *double[]*
 :Description: Polynomial coefficients listed in order of increasing power
-:Attributes: - **type** (*char[]*) -- 'polynomial'
+:Attributes: - **type** (*char[]*) -- 'Polynomial'
 
 Coherent elastic scattering
 ---------------------------

docs/source/pythonapi/index.rst

@@ -27,6 +27,8 @@ Example Jupyter Notebooks
     examples/mgxs-part-ii
     examples/mgxs-part-iii
     examples/mgxs-part-iv
+    examples/mdgxs-part-i
+    examples/mdgxs-part-ii
     examples/nuclear-data
 
 ------------------------------------
@@ -284,6 +286,19 @@ Multi-group Cross Sections
     openmc.mgxs.TotalXS
     openmc.mgxs.TransportXS
 
+Multi-delayed-group Cross Sections
+----------------------------------
+
+.. autosummary::
+    :toctree: generated
+    :nosignatures:
+    :template: myclassinherit.rst
+
+    openmc.mgxs.MDGXS
+    openmc.mgxs.ChiDelayed
+    openmc.mgxs.DelayedNuFissionXS
+    openmc.mgxs.Beta
+
 Multi-group Cross Section Libraries
 -----------------------------------
 
@@ -348,6 +363,7 @@ Core Classes
     openmc.data.Tabulated1D
     openmc.data.ThermalScattering
     openmc.data.CoherentElastic
+    openmc.data.FissionEnergyRelease
 
 Angle-Energy Distributions
 --------------------------
@@ -381,21 +397,22 @@ Classes
 +++++++
 
 .. autosummary::
-   :toctree: generated
-   :nosignatures:
-   :template: myclass.rst
+    :toctree: generated
+    :nosignatures:
+    :template: myclass.rst
 
-   openmc.data.ace.Library
-   openmc.data.ace.Table
+    openmc.data.ace.Library
+    openmc.data.ace.Table
 
 Functions
 +++++++++
 
 .. autosummary::
-   :toctree: generated
-   :nosignatures:
+    :toctree: generated
+    :nosignatures:
 
-   openmc.data.ace.ascii_to_binary
+    openmc.data.ace.ascii_to_binary
+    openmc.data.write_compact_458_library
 
 .. _Jupyter: https://jupyter.org/
 .. _NumPy: http://www.numpy.org/

docs/source/usersguide/input.rst

@@ -1838,6 +1838,27 @@ The ``<tally>`` element accepts the following sub-elements:
         |                      |:math:`\gamma`-rays are assumed to deposit their   |
         |                      |energy locally. Units are MeV per source particle. |
         +----------------------+---------------------------------------------------+
+        |fission-q-prompt      |The prompt fission energy production rate. This    |
+        |                      |energy comes in the form of fission fragment       |
+        |                      |nuclei, prompt neutrons, and prompt                |
+        |                      |:math:`\gamma`-rays. This value depends on the     |
+        |                      |incident energy and it requires that the nuclear   |
+        |                      |data library contains the optional fission energy  |
+        |                      |release data. Energy is assumed to be deposited    |
+        |                      |locally. Units are MeV per source particle.        |
+        +----------------------+---------------------------------------------------+
+        |fission-q-recoverable |The recoverable fission energy production rate.    |
+        |                      |This energy comes in the form of fission fragment  |
+        |                      |nuclei, prompt and delayed neutrons, prompt and    |
+        |                      |delayed :math:`\gamma`-rays, and delayed           |
+        |                      |:math:`\beta`-rays. This tally differs from the    |
+        |                      |kappa-fission tally in that it is dependent on     |
+        |                      |incident neutron energy and it requires that the   |
+        |                      |nuclear data library contains the optional fission |
+        |                      |energy release data. Energy is assumed to be       |
+        |                      |deposited locally. Units are MeV per source        |
+        |                      |paticle.                                           |
+        +----------------------+---------------------------------------------------+
 
     .. note::
        The ``analog`` estimator is actually identical to the ``collision``

openmc/__init__.py

@@ -13,10 +13,10 @@ from openmc.settings import *
 from openmc.surface import *
 from openmc.universe import *
 from openmc.mesh import *
-from openmc.mgxs_library import *
 from openmc.filter import *
 from openmc.trigger import *
 from openmc.tallies import *
+from openmc.mgxs_library import *
 from openmc.cmfd import *
 from openmc.executor import *
 from openmc.statepoint import *

openmc/data/__init__.py

@@ -14,3 +14,4 @@ from .nbody import *
 from .thermal import *
 from .urr import *
 from .library import *
+from .fission_energy import *

openmc/data/endf_utils.py

@@ -0,0 +1,44 @@
+"""This module contains a few utility functions for reading ENDF_ data. It is by
+no means enough to read an entire ENDF file.  For a more complete ENDF reader,
+see Pyne_.
+
+.. _ENDF: http://www.nndc.bnl.gov/endf
+.. _Pyne: http://www.pyne.io
+
+"""
+
+import re
+
+def read_float(float_string):
+    """Parse ENDF 6E11.0 formatted string into a float."""
+    assert len(float_string) == 11
+    pattern = r'([\s\-]\d+\.\d+)([\+\-]\d+)'
+    return float(re.sub(pattern, r'\1e\2', float_string))
+
+
+def read_CONT_line(line):
+    """Parse 80-column line from ENDF CONT record into floats and ints."""
+    return (read_float(line[0:11]), read_float(line[11:22]), int(line[22:33]),
+            int(line[33:44]), int(line[44:55]), int(line[55:66]),
+            int(line[66:70]), int(line[70:72]), int(line[72:75]),
+            int(line[75:80]))
+
+
+def identify_nuclide(fname):
+    """Read the header of an ENDF file and extract identifying information."""
+    with open(fname, 'r') as fh:
+        # Skip the tape id (TPID).
+        line = fh.readline()
+
+        # Read the first HEAD and CONT info.
+        line = fh.readline()
+        ZA, AW, LRP, LFI, NLIB, NMOD, MAT, MF, MT, NS = read_CONT_line(line)
+        line = fh.readline()
+        ELIS, STA, LIS, LISO, junk, NFOR, MAT, MF, MT, NS = read_CONT_line(line)
+
+    # Return dictionary of the most important identifying information.
+    return {'Z': int(ZA) // 1000,
+            'A': int(ZA) % 1000,
+            'LFI': bool(LFI),
+            'LIS': LIS,
+            'LISO': LISO}

openmc/data/fission_energy.py

@@ -0,0 +1,592 @@
+from collections import Callable
+from copy import deepcopy
+import sys
+
+import h5py
+import numpy as np
+
+from .data import ATOMIC_SYMBOL
+from .endf_utils import read_float, read_CONT_line, identify_nuclide
+from .function import Function1D, Tabulated1D, Polynomial, Sum
+import openmc.checkvalue as cv
+
+if sys.version_info[0] >= 3:
+    basestring = str
+
+
+def _extract_458_data(filename):
+    """Read an ENDF file and extract the MF=1, MT=458 values.
+
+    Parameters
+    ----------
+    filename : str
+        Path to and ENDF file
+
+    Returns
+    -------
+    value : dict of str to list of float
+        Dictionary that gives lists of coefficients for each energy component.
+        The keys are the 2-3 letter strings used in ENDF-102, e.g. 'EFR' and
+        'ET'.  The list will have a length of 1 for Sher-Beck data, more for
+        polynomial data.
+    uncertainty : dict of str to list of float
+        A dictionary with the same format as above.  This is probably a
+        one-standard deviation value, but that is not specified explicitly in
+        ENDF-102.  Also, some evaluations will give zero uncertainty.  Use with
+        caution.
+
+    """
+    ident = identify_nuclide(filename)
+
+    if not ident['LFI']:
+        # This nuclide isn't fissionable.
+        return None
+
+    # Extract the MF=1, MT=458 section.
+    lines = []
+    with open(filename, 'r') as fh:
+        line = fh.readline()
+        while line != '':
+            if line[70:75] == ' 1458':
+                lines.append(line)
+            line = fh.readline()
+
+    if len(lines) == 0:
+        # No 458 data here.
+        return None
+
+    # Read the number of coefficients in this LIST record.
+    NPL = read_CONT_line(lines[1])[4]
+
+    # Parse the ENDF LIST into an array.
+    data = []
+    for i in range(NPL):
+        row, column = divmod(i, 6)
+        data.append(read_float(lines[2 + row][11*column:11*(column+1)]))
+
+    # Declare the coefficient names and the order they are given in.  The LIST
+    # contains a value followed immediately by an uncertainty for each of these
+    # components, times the polynomial order + 1.
+    labels = ('EFR', 'ENP', 'END', 'EGP', 'EGD', 'EB', 'ENU', 'ER', 'ET')
+
+    # Associate each set of values and uncertainties with its label.
+    value = {}
+    uncertainty = {}
+    for i, label in enumerate(labels):
+        value[label] = data[2*i::18]
+        uncertainty[label] = data[2*i + 1::18]
+
+    # In ENDF/B-7.1, data for 2nd-order coefficients were mistakenly not
+    # converted from MeV to eV.  Check for this error and fix it if present.
+    n_coeffs = len(value['EFR'])
+    if n_coeffs == 3:  # Only check 2nd-order data.
+        # Check each energy component for the error.  If a 1 MeV neutron
+        # causes a change of more than 100 MeV, we know something is wrong.
+        error_present = False
+        for coeffs in value.values():
+            second_order = coeffs[2]
+            if abs(second_order) * 1e12 > 1e8:
+                error_present = True
+                break
+
+        # If we found the error, reduce all 2nd-order coeffs by 10**6.
+        if error_present:
+            for coeffs in value.values(): coeffs[2] *= 1e-6
+            for coeffs in uncertainty.values(): coeffs[2] *= 1e-6
+
+    # Convert eV to MeV.
+    for coeffs in value.values():
+        for i in range(len(coeffs)):
+            coeffs[i] *= 10**(-6 + 6*i)
+    for coeffs in uncertainty.values():
+        for i in range(len(coeffs)):
+            coeffs[i] *= 10**(-6 + 6*i)
+
+    return value, uncertainty
+
+
+def write_compact_458_library(endf_files, output_name='fission_Q_data.h5',
+                              comment=None, verbose=False):
+    """Read ENDF files, strip the MF=1 MT=458 data and write to small HDF5.
+
+    Parameters
+    ----------
+    endf_files : Collection of str
+        Strings giving the paths to the ENDF files that will be parsed for data.
+    output_name : str
+        Name of the output HDF5 file.  Default is 'fission_Q_data.h5'.
+    comment : str
+        Comment to write in the output HDF5 file.  Defaults to no comment.
+    verbose : bool
+        If True, print the name of each isomer as it is read.  Defaults to
+        False.
+
+    """
+    # Open the output file.
+    out = h5py.File(output_name, 'w', libver='latest')
+
+    # Write comments, if given.  This commented out comment is the one used for
+    # the library distributed with OpenMC.
+    #comment = ('This data is extracted from ENDF/B-VII.1 library.  Thanks '
+    #           'evaluators, for all your hard work :)  Citation:  '
+    #           'M. B. Chadwick, M. Herman, P. Oblozinsky, '
+    #           'M. E. Dunn, Y. Danon, A. C. Kahler, D. L. Smith, '
+    #           'B. Pritychenko, G. Arbanas, R. Arcilla, R. Brewer, '
+    #           'D. A. Brown, R. Capote, A. D. Carlson, Y. S. Cho, H. Derrien, '
+    #           'K. Guber, G. M. Hale, S. Hoblit, S. Holloway, T. D. Johnson, '
+    #           'T. Kawano, B. C. Kiedrowski, H. Kim, S. Kunieda, '
+    #           'N. M. Larson, L. Leal, J. P. Lestone, R. C. Little, '
+    #           'E. A. McCutchan, R. E. MacFarlane, M. MacInnes, '
+    #           'C. M. Mattoon, R. D. McKnight, S. F. Mughabghab, '
+    #           'G. P. A. Nobre, G. Palmiotti, A. Palumbo, M. T. Pigni, '
+    #           'V. G. Pronyaev, R. O. Sayer, A. A. Sonzogni, N. C. Summers, '
+    #           'P. Talou, I. J. Thompson, A. Trkov, R. L. Vogt, '
+    #           'S. C. van der Marck, A. Wallner, M. C. White, D. Wiarda, '
+    #           'and P. G. Young. ENDF/B-VII.1 nuclear data for science and '
+    #           'technology: Cross sections, covariances, fission product '
+    #           'yields and decay data", Nuclear Data Sheets, '
+    #           '112(12):2887-2996 (2011).')
+    if comment is not None:
+        out.attrs['comment'] = np.string_(comment)
+
+    # Declare the order of the components.  Use fixed-length numpy strings
+    # because they work well with h5py.
+    labels = np.array(('EFR', 'ENP', 'END', 'EGP', 'EGD', 'EB', 'ENU', 'ER',
+                       'ET'), dtype='S3')
+    out.attrs['component order'] = labels
+
+    # Iterate over the given files.
+    if verbose: print('Reading ENDF files:')
+    for fname in endf_files:
+        if verbose: print(fname)
+
+        ident = identify_nuclide(fname)
+
+        # Skip non-fissionable nuclides.
+        if not ident['LFI']: continue
+
+        # Get the important bits.
+        data = _extract_458_data(fname)
+        if data is None: continue
+        value, uncertainty = data
+
+        # Make a group for this isomer.
+        name = ATOMIC_SYMBOL[ident['Z']] + str(ident['A'])
+        if ident['LISO'] != 0:
+            name += '_m' + str(ident['LISO'])
+        nuclide_group = out.create_group(name)
+
+        # Write all the coefficients into one array.  The first dimension gives
+        # the component (e.g. fragments or prompt neutrons); the second switches
+        # between value and uncertainty; the third gives the polynomial order.
+        n_coeffs = len(value['EFR'])
+        data_out = np.zeros((len(labels), 2, n_coeffs))
+        for i, label in enumerate(labels):
+            data_out[i, 0, :] = value[label.decode()]
+            data_out[i, 1, :] = uncertainty[label.decode()]
+        nuclide_group.create_dataset('data', data=data_out)
+
+    out.close()
+
+
+class FissionEnergyRelease(object):
+    """Energy relased by fission reactions.
+
+    Energy is carried away from fission reactions by many different particles.
+    The attributes of this class specify how much energy is released in the form
+    of fission fragments, neutrons, photons, etc.  Each component is also (in
+    general) a function of the incident neutron energy.
+
+    Following a fission reaction, most of the energy release is carried by the
+    daughter nuclei fragments.  These fragments accelerate apart from the
+    Coulomb force on the time scale of ~10^-20 s [1].  Those fragments emit
+    prompt neutrons between ~10^-18 and ~10^-13 s after scission (although some
+    prompt neutrons may come directly from the scission point) [1].  Prompt
+    photons follow with a time scale of ~10^-14 to ~10^-7 s [1].  The fission
+    products then emit delayed neutrons with half lives between 0.1 and 100 s.
+    The remaining fission energy comes from beta decays of the fission products
+    which release beta particles, photons, and neutrinos (that escape the
+    reactor and do not produce usable heat).
+
+    Use the class methods to instantiate this class from an HDF5 or ENDF
+    dataset.  The :meth:`FissionEnergyRelease.from_hdf5` method builds this
+    class from the usual OpenMC HDF5 data files.
+    :meth:`FissionEnergyRelease.from_endf` uses ENDF-formatted data.
+    :meth:`FissionEnergyRelease.from_compact_hdf5` uses a different HDF5 format
+    that is meant to be compact and store the exact same data as the ENDF
+    format.  Files with this format can be generated with the
+    :func:`openmc.data.write_compact_458_library` function.
+
+    References
+    ----------
+    [1] D. G. Madland, "Total prompt energy release in the neutron-induced
+    fission of ^235U, ^238U, and ^239Pu", Nuclear Physics A 772:113--137 (2006).
+    <http://dx.doi.org/10.1016/j.nuclphysa.2006.03.013>
+
+    Attributes
+    ----------
+    fragments : Callable
+        Function that accepts incident neutron energy value(s) and returns the
+        kinetic energy of the fission daughter nuclides (after prompt neutron
+        emission).
+    prompt_neutrons : Callable
+        Function of energy that returns the kinetic energy of prompt fission
+        neutrons.
+    delayed_neutrons : Callable
+        Function of energy that returns the kinetic energy of delayed neutrons
+        emitted from fission products.
+    prompt_photons : Callable
+        Function of energy that returns the kinetic energy of prompt fission
+        photons.
+    delayed_photons : Callable
+        Function of energy that returns the kinetic energy of delayed photons.
+    betas : Callable
+        Function of energy that returns the kinetic energy of delayed beta
+        particles.
+    neutrinos : Callable
+        Function of energy that returns the kinetic energy of neutrinos.
+    recoverable : Callable
+        Function of energy that returns the kinetic energy of all products that
+        can be absorbed in the reactor (all of the energy except for the
+        neutrinos).
+    total : Callable
+        Function of energy that returns the kinetic energy of all products.
+    q_prompt : Callable
+        Function of energy that returns the prompt fission Q-value (fragments +
+        prompt neutrons + prompt photons - incident neutron energy).
+    q_recoverable : Callable
+        Function of energy that returns the recoverable fission Q-value
+        (total release - neutrinos - incident neutron energy).  This value is
+        sometimes referred to as the pseudo-Q-value.
+    q_total : Callable
+        Function of energy that returns the total fission Q-value (total release
+        - incident neutron energy).
+
+    """
+    def __init__(self):
+        self._fragments = None
+        self._prompt_neutrons = None
+        self._delayed_neutrons = None
+        self._prompt_photons = None
+        self._delayed_photons = None
+        self._betas = None
+        self._neutrinos = None
+
+    @property
+    def fragments(self):
+        return self._fragments
+
+    @property
+    def prompt_neutrons(self):
+        return self._prompt_neutrons
+
+    @property
+    def delayed_neutrons(self):
+        return self._delayed_neutrons
+
+    @property
+    def prompt_photons(self):
+        return self._prompt_photons
+
+    @property
+    def delayed_photons(self):
+        return self._delayed_photons
+
+    @property
+    def betas(self):
+        return self._betas
+
+    @property
+    def neutrinos(self):
+        return self._neutrinos
+
+    @property
+    def recoverable(self):
+        return Sum([self.fragments, self.prompt_neutrons, self.delayed_neutrons,
+                    self.prompt_photons, self.delayed_photons, self.betas])
+
+    @property
+    def total(self):
+        return Sum([self.fragments, self.prompt_neutrons, self.delayed_neutrons,
+                    self.prompt_photons, self.delayed_photons, self.betas,
+                    self.neutrinos])
+
+    @property
+    def q_prompt(self):
+        return Sum([self.fragments, self.prompt_neutrons, self.prompt_photons,
+                    lambda E: -E])
+
+    @property
+    def q_recoverable(self):
+        return Sum([self.recoverable, lambda E: -E])
+
+    @property
+    def q_total(self):
+        return Sum([self.total, lambda E: -E])
+
+    @fragments.setter
+    def fragments(self, energy_release):
+        cv.check_type('fragments', energy_release, Callable)
+        self._fragments = energy_release
+
+    @prompt_neutrons.setter
+    def prompt_neutrons(self, energy_release):
+        cv.check_type('prompt_neutrons', energy_release, Callable)
+        self._prompt_neutrons = energy_release
+
+    @delayed_neutrons.setter
+    def delayed_neutrons(self, energy_release):
+        cv.check_type('delayed_neutrons', energy_release, Callable)
+        self._delayed_neutrons = energy_release
+
+    @prompt_photons.setter
+    def prompt_photons(self, energy_release):
+        cv.check_type('prompt_photons', energy_release, Callable)
+        self._prompt_photons = energy_release
+
+    @delayed_photons.setter
+    def delayed_photons(self, energy_release):
+        cv.check_type('delayed_photons', energy_release, Callable)
+        self._delayed_photons = energy_release
+
+    @betas.setter
+    def betas(self, energy_release):
+        cv.check_type('betas', energy_release, Callable)
+        self._betas = energy_release
+
+    @neutrinos.setter
+    def neutrinos(self, energy_release):
+        cv.check_type('neutrinos', energy_release, Callable)
+        self._neutrinos = energy_release
+
+    @classmethod
+    def _from_dictionary(cls, energy_release, incident_neutron):
+        """Generate fission energy release data from a dictionary.
+
+        Parameters
+        ----------
+        energy_release : dict of str to list of float
+            Dictionary that gives lists of coefficients for each energy
+            component.  The keys are the 2-3 letter strings used in ENDF-102,
+            e.g. 'EFR' and 'ET'.  The list will have a length of 1 for Sher-Beck
+            data, more for polynomial data.
+
+        incident_neutron : openmc.data.IncidentNeutron
+            Corresponding incident neutron dataset
+
+        Returns
+        -------
+        openmc.data.FissionEnergyRelease
+            Fission energy release data
+
+        """
+        out = cls()
+
+        # How many coefficients are given for each component?  If we only find
+        # one value for each, then we need to use the Sher-Beck formula for
+        # energy dependence.  Otherwise, it is a polynomial.
+        n_coeffs = len(energy_release['EFR'])
+        if n_coeffs > 1:
+            out.fragments = Polynomial(energy_release['EFR'])
+            out.prompt_neutrons = Polynomial(energy_release['ENP'])
+            out.delayed_neutrons = Polynomial(energy_release['END'])
+            out.prompt_photons = Polynomial(energy_release['EGP'])
+            out.delayed_photons = Polynomial(energy_release['EGD'])
+            out.betas = Polynomial(energy_release['EB'])
+            out.neutrinos = Polynomial(energy_release['ENU'])
+        else:
+            # EFR and ENP are energy independent.  Use 0-order polynomials to
+            # make a constant function.  The energy-dependence of END is
+            # unspecified in ENDF-102 so assume it is independent.
+            out.fragments = Polynomial((energy_release['EFR'][0]))
+            out.prompt_photons = Polynomial((energy_release['EGP'][0]))
+            out.delayed_neutrons = Polynomial((energy_release['END'][0]))
+
+            # EDP, EB, and ENU are linear.
+            out.delayed_photons = Polynomial((energy_release['EGD'][0], -0.075))
+            out.betas = Polynomial((energy_release['EB'][0], -0.075))
+            out.neutrinos = Polynomial((energy_release['ENU'][0], -0.105))
+
+            # Prompt neutrons require nu-data.  It is not clear from ENDF-102
+            # whether prompt or total nu value should be used, but the delayed
+            # neutron fraction is so small that the difference is negligible.
+            # MT=18 (n, fission) might not be available so try MT=19 (n, f) as
+            # well.
+            if 18 in incident_neutron.reactions:
+                nu_prompt = [p for p in incident_neutron[18].products
+                             if p.particle == 'neutron'
+                             and p.emission_mode == 'prompt']
+            elif 19 in incident_neutron.reactions:
+                nu_prompt = [p for p in incident_neutron[19].products
+                             if p.particle == 'neutron'
+                             and p.emission_mode == 'prompt']
+            else:
+                raise ValueError('IncidentNeutron data has no fission '
+                                 'reaction.')
+            if len(nu_prompt) == 0:
+                raise ValueError('Nu data is needed to compute fission energy '
+                                 'release with the Sher-Beck format.')
+            if len(nu_prompt) > 1:
+                raise ValueError('Ambiguous prompt value.')
+            if not isinstance(nu_prompt[0].yield_, Tabulated1D):
+                raise TypeError('Sher-Beck fission energy release currently '
+                                'only supports Tabulated1D nu data.')
+            ENP = deepcopy(nu_prompt[0].yield_)
+            ENP.y = (energy_release['ENP'] + 1.307 * ENP.x
+                     - 8.07 * (ENP.y - ENP.y[0]))
+            out.prompt_neutrons = ENP
+
+        return out
+
+    @classmethod
+    def from_endf(cls, filename, incident_neutron):
+        """Generate fission energy release data from an ENDF file.
+
+        Parameters
+        ----------
+        filename : str
+            Name of the ENDF file containing fission energy release data
+
+        incident_neutron : openmc.data.IncidentNeutron
+            Corresponding incident neutron dataset
+
+        Returns
+        -------
+        openmc.data.FissionEnergyRelease
+            Fission energy release data
+
+        """
+
+        # Check to make sure this ENDF file matches the expected isomer.
+        ident = identify_nuclide(filename)
+        if ident['Z'] != incident_neutron.atomic_number:
+            raise ValueError('The atomic number of the ENDF evaluation does '
+                             'not match the given IncidentNeutron.')
+        if ident['A'] != incident_neutron.mass_number:
+            raise ValueError('The atomic mass of the ENDF evaluation does '
+                             'not match the given IncidentNeutron.')
+        if ident['LISO'] != incident_neutron.metastable:
+            raise ValueError('The metastable state of the ENDF evaluation does '
+                             'not match the given IncidentNeutron.')
+        if not ident['LFI']:
+            raise ValueError('The ENDF evaluation is not fissionable.')
+
+        # Read the 458 data from the ENDF file.
+        value, uncertainty = _extract_458_data(filename)
+
+        # Build the object.
+        return cls._from_dictionary(value, incident_neutron)
+
+    @classmethod
+    def from_hdf5(cls, group):
+        """Generate fission energy release data from an HDF5 group.
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to read from
+
+        Returns
+        -------
+        openmc.data.FissionEnergyRelease
+            Fission energy release data
+
+        """
+
+        obj = cls()
+
+        obj.fragments = Function1D.from_hdf5(group['fragments'])
+        obj.prompt_neutrons = Function1D.from_hdf5(group['prompt_neutrons'])
+        obj.delayed_neutrons = Function1D.from_hdf5(group['delayed_neutrons'])
+        obj.prompt_photons = Function1D.from_hdf5(group['prompt_photons'])
+        obj.delayed_photons = Function1D.from_hdf5(group['delayed_photons'])
+        obj.betas = Function1D.from_hdf5(group['betas'])
+        obj.neutrinos = Function1D.from_hdf5(group['neutrinos'])
+
+        return obj
+
+    @classmethod
+    def from_compact_hdf5(cls, fname, incident_neutron):
+        """Generate fission energy release data from a small HDF5 library.
+
+        Parameters
+        ----------
+        fname : str
+            Path to an HDF5 file containing fission energy release data.  This
+            file should have been generated form the
+            :func:`openmc.data.write_compact_458_library` function.
+
+        incident_neutron : openmc.data.IncidentNeutron
+            Corresponding incident neutron dataset
+
+        Returns
+        -------
+        openmc.data.FissionEnergyRelease or None
+            Fission energy release data for the given nuclide if it is present
+            in the data file
+
+        """
+
+        fin = h5py.File(fname, 'r')
+
+        components = [s.decode() for s in fin.attrs['component order']]
+
+        nuclide_name = ATOMIC_SYMBOL[incident_neutron.atomic_number]
+        nuclide_name += str(incident_neutron.mass_number)
+        if incident_neutron.metastable != 0:
+            nuclide_name += '_m' + str(incident_neutron.metastable)
+
+        if nuclide_name not in fin: return None
+
+        data = {c: fin[nuclide_name + '/data'][i, 0, :]
+                for i, c in enumerate(components)}
+
+        return cls._from_dictionary(data, incident_neutron)
+
+    def to_hdf5(self, group):
+        """Write energy release data to an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to write to
+
+        """
+
+        self.fragments.to_hdf5(group, 'fragments')
+        self.prompt_neutrons.to_hdf5(group, 'prompt_neutrons')
+        self.delayed_neutrons.to_hdf5(group, 'delayed_neutrons')
+        self.prompt_photons.to_hdf5(group, 'prompt_photons')
+        self.delayed_photons.to_hdf5(group, 'delayed_photons')
+        self.betas.to_hdf5(group, 'betas')
+        self.neutrinos.to_hdf5(group, 'neutrinos')
+        
+        if isinstance(self.prompt_neutrons, Polynomial):
+            # Add the polynomials for the relevant components together. Use a
+            # Polynomial((0.0, -1.0)) to subtract incident energy.
+            q_prompt = (self.fragments + self.prompt_neutrons +
+                        self.prompt_photons + Polynomial((0.0, -1.0)))
+            q_prompt.to_hdf5(group, 'q_prompt')
+            q_recoverable = (self.fragments + self.prompt_neutrons +
+                             self.delayed_neutrons + self.prompt_photons +
+                             self.delayed_photons + self.betas +
+                             Polynomial((0.0, -1.0)))
+            q_recoverable.to_hdf5(group, 'q_recoverable')
+
+        elif isinstance(self.prompt_neutrons, Tabulated1D):
+            # Make a Tabulated1D and evaluate the polynomial components at the
+            # table x points to get new y points.  Subtract x from y to remove
+            # incident energy.
+            q_prompt = deepcopy(self.prompt_neutrons)
+            q_prompt.y += self.fragments(q_prompt.x)
+            q_prompt.y += self.prompt_photons(q_prompt.x)
+            q_prompt.y -= q_prompt.x
+            q_prompt.to_hdf5(group, 'q_prompt')
+            q_recoverable = q_prompt
+            q_recoverable.y += self.delayed_neutrons(q_recoverable.x)
+            q_recoverable.y += self.delayed_photons(q_recoverable.x)
+            q_recoverable.y += self.betas(q_recoverable.x)
+            q_recoverable.to_hdf5(group, 'q_recoverable')
+
+        else:
+            raise ValueError('Unrecognized energy release format')

openmc/data/function.py

@@ -1,3 +1,4 @@
+from abc import ABCMeta, abstractmethod
 from collections import Iterable, Callable
 from numbers import Real, Integral
 
@@ -9,7 +10,51 @@ INTERPOLATION_SCHEME = {1: 'histogram', 2: 'linear-linear', 3: 'linear-log',
                         4: 'log-linear', 5: 'log-log'}
 
 
-class Tabulated1D(object):
+class Function1D(object):
+    """A function of one independent variable with HDF5 support."""
+
+    __metaclass__ = ABCMeta
+
+    @abstractmethod
+    def __call__(self): pass
+
+    @abstractmethod
+    def to_hdf5(self, group, name='xy'):
+        """Write function to an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to write to
+        name : str
+            Name of the dataset to create
+
+        """
+        pass
+
+    @classmethod
+    def from_hdf5(cls, dataset):
+        """Generate function from an HDF5 dataset
+
+        Parameters
+        ----------
+        dataset : h5py.Dataset
+            Dataset to read from
+
+        Returns
+        -------
+        openmc.data.Function1D
+            Function read from dataset
+
+        """
+        for subclass in cls.__subclasses__():
+            if dataset.attrs['type'].decode() == subclass.__name__:
+                return subclass.from_hdf5(dataset)
+        raise ValueError("Unrecognized Function1D class: '"
+                         + dataset.attrs['type'].decode() + "'")
+
+
+class Tabulated1D(Function1D):
     """A one-dimensional tabulated function.
 
     This class mirrors the TAB1 type from the ENDF-6 format. A tabulated
@@ -251,7 +296,7 @@ class Tabulated1D(object):
         """
         dataset = group.create_dataset(name, data=np.vstack(
             [self.x, self.y]))
-        dataset.attrs['type'] = np.string_('tab1')
+        dataset.attrs['type'] = np.string_(type(self).__name__)
         dataset.attrs['breakpoints'] = self.breakpoints
         dataset.attrs['interpolation'] = self.interpolation
 
@@ -270,6 +315,10 @@ class Tabulated1D(object):
             Function read from dataset
 
         """
+        if dataset.attrs['type'].decode() != cls.__name__:
+            raise ValueError("Expected an HDF5 attribute 'type' equal to '"
+                             + cls.__name__ + "'")
+
         x = dataset.value[0, :]
         y = dataset.value[1, :]
         breakpoints = dataset.attrs['breakpoints']
@@ -316,6 +365,42 @@ class Tabulated1D(object):
         return Tabulated1D(x, y, breakpoints, interpolation)
 
 
+class Polynomial(np.polynomial.Polynomial, Function1D):
+    def to_hdf5(self, group, name='xy'):
+        """Write polynomial function to an HDF5 group
+
+        Parameters
+        ----------
+        group : h5py.Group
+            HDF5 group to write to
+        name : str
+            Name of the dataset to create
+
+        """
+        dataset = group.create_dataset(name, data=self.coef)
+        dataset.attrs['type'] = np.string_(type(self).__name__)
+
+    @classmethod
+    def from_hdf5(cls, dataset):
+        """Generate function from an HDF5 dataset
+
+        Parameters
+        ----------
+        dataset : h5py.Dataset
+            Dataset to read from
+
+        Returns
+        -------
+        openmc.data.Function1D
+            Function read from dataset
+
+        """
+        if dataset.attrs['type'].decode() != cls.__name__:
+            raise ValueError("Expected an HDF5 attribute 'type' equal to '"
+                             + cls.__name__ + "'")
+        return cls(dataset.value)
+
+
 class Sum(object):
     """Sum of multiple functions.
 

openmc/data/neutron.py

@@ -9,6 +9,7 @@ import h5py
 
 from .data import ATOMIC_SYMBOL, SUM_RULES
 from .ace import Table, get_table
+from .fission_energy import FissionEnergyRelease
 from .function import Tabulated1D, Sum
 from .product import Product
 from .reaction import Reaction, _get_photon_products
@@ -51,6 +52,9 @@ class IncidentNeutron(object):
         Atomic weight ratio of the target nuclide.
     energy : numpy.ndarray
         The energy values (MeV) at which reaction cross-sections are tabulated.
+    fission_energy : None or openmc.data.FissionEnergyRelease
+        The energy released by fission, tabulated by component (e.g. prompt
+        neutrons or beta particles) and dependent on incident neutron energy
     mass_number : int
         Number of nucleons in the nucleus
     metastable : int
@@ -81,6 +85,7 @@ class IncidentNeutron(object):
         self.temperature = temperature
 
         self._energy = None
+        self._fission_energy = None
         self.reactions = OrderedDict()
         self.summed_reactions = OrderedDict()
         self.urr = None
@@ -126,6 +131,10 @@ class IncidentNeutron(object):
     def energy(self):
         return self._energy
 
+    @property
+    def fission_energy(self):
+        return self._fission_energy
+
     @property
     def temperature(self):
         return self._temperature
@@ -186,6 +195,12 @@ class IncidentNeutron(object):
         cv.check_type('energy grid', energy, Iterable, Real)
         self._energy = energy
 
+    @fission_energy.setter
+    def fission_energy(self, fission_energy):
+        cv.check_type('fission energy release', fission_energy,
+                      FissionEnergyRelease)
+        self._fission_energy = fission_energy
+
     @reactions.setter
     def reactions(self, reactions):
         cv.check_type('reactions', reactions, Mapping)
@@ -276,6 +291,11 @@ class IncidentNeutron(object):
             urr_group = g.create_group('urr')
             self.urr.to_hdf5(urr_group)
 
+        # Write fission energy release data
+        if self.fission_energy is not None:
+            fer_group = g.create_group('fission_energy_release')
+            self.fission_energy.to_hdf5(fer_group)
+
         f.close()
 
     @classmethod
@@ -342,6 +362,11 @@ class IncidentNeutron(object):
             urr_group = group['urr']
             data.urr = ProbabilityTables.from_hdf5(urr_group)
 
+        # Read fission energy release data
+        if 'fission_energy_release' in group:
+            fer_group = group['fission_energy_release']
+            data.fission_energy = FissionEnergyRelease.from_hdf5(fer_group)
+
         return data
 
     @classmethod

openmc/data/product.py

@@ -3,10 +3,9 @@ from numbers import Real
 import sys
 
 import numpy as np
-from numpy.polynomial.polynomial import Polynomial
 
 import openmc.checkvalue as cv
-from .function import Tabulated1D
+from .function import Tabulated1D, Polynomial, Function1D
 from .angle_energy import AngleEnergy
 
 if sys.version_info[0] >= 3:
@@ -36,7 +35,7 @@ class Product(object):
         yield represents particles from prompt and delayed sources.
     particle : str
         What particle the reaction product is.
-    yield_ : float or openmc.data.Tabulated1D or numpy.polynomial.Polynomial
+    yield_ : openmc.data.Function1D
         Yield of secondary particle in the reaction.
 
     """
@@ -47,7 +46,7 @@ class Product(object):
         self.emission_mode = 'prompt'
         self.distribution = []
         self.applicability = []
-        self.yield_ = 1
+        self.yield_ = Polynomial((1,))  # 0-order polynomial i.e. a constant
 
     def __eq__(self, other):
         if not isinstance(other, type(self)):
@@ -133,8 +132,7 @@ class Product(object):
 
     @yield_.setter
     def yield_(self, yield_):
-        cv.check_type('product yield', yield_,
-                      (Real, Tabulated1D, Polynomial))
+        cv.check_type('product yield', yield_, Function1D)
         self._yield = yield_
 
     def to_hdf5(self, group):
@@ -152,16 +150,7 @@ class Product(object):
             group.attrs['decay_rate'] = self.decay_rate
 
         # Write yield
-        if isinstance(self.yield_, Tabulated1D):
-            self.yield_.to_hdf5(group, 'yield')
-            dset = group['yield']
-            dset.attrs['type'] = np.string_('tabulated')
-        elif isinstance(self.yield_, Polynomial):
-            dset = group.create_dataset('yield', data=self.yield_.coef)
-            dset.attrs['type'] = np.string_('polynomial')
-        else:
-            dset = group.create_dataset('yield', data=float(self.yield_))
-            dset.attrs['type'] = np.string_('constant')
+        self.yield_.to_hdf5(group, 'yield')
 
         # Write applicability/distribution
         group.attrs['n_distribution'] = len(self.distribution)
@@ -194,13 +183,7 @@ class Product(object):
             p.decay_rate = group.attrs['decay_rate']
 
         # Read yield
-        yield_type = group['yield'].attrs['type'].decode()
-        if yield_type == 'constant':
-            p.yield_ = group['yield'].value
-        elif yield_type == 'polynomial':
-            p.yield_ = Polynomial(group['yield'].value)
-        elif yield_type == 'tabulated':
-            p.yield_ = Tabulated1D.from_hdf5(group['yield'])
+        p.yield_ = Function1D.from_hdf5(group['yield'])
 
         # Read applicability/distribution
         n_distribution = group.attrs['n_distribution']

openmc/data/reaction.py

@@ -5,13 +5,12 @@ from numbers import Real
 from warnings import warn
 
 import numpy as np
-from numpy.polynomial import Polynomial
 
 import openmc.checkvalue as cv
 from openmc.stats import Uniform
 from .angle_distribution import AngleDistribution
 from .angle_energy import AngleEnergy
-from .function import Tabulated1D
+from .function import Tabulated1D, Polynomial
 from .data import REACTION_NAME
 from .product import Product
 from .uncorrelated import UncorrelatedAngleEnergy
@@ -465,7 +464,8 @@ class Reaction(object):
                         idx = ace.jxs[11] + abs(ty) - 101
                         yield_ = Tabulated1D.from_ace(ace, idx)
                     else:
-                        yield_ = abs(ty)
+                        # 0-order polynomial i.e. a constant
+                        yield_ = Polynomial((abs(ty),))
 
                     neutron = Product('neutron')
                     neutron.yield_ = yield_

openmc/filter.py

@@ -777,6 +777,18 @@ class Filter(object):
             df.loc[:, self.type + ' low'] = lo_bins
             df.loc[:, self.type + ' high'] = hi_bins
 
+        elif self.type == 'surface':
+            filter_bins = np.repeat(self.bins, self.stride)
+            tile_factor = data_size / len(filter_bins)
+            filter_bins = np.tile(filter_bins, tile_factor)
+            filter_bins = [x if x != 1 else 'x-min' for x in filter_bins]
+            filter_bins = [x if x != 2 else 'x-max' for x in filter_bins]
+            filter_bins = [x if x != 3 else 'y-min' for x in filter_bins]
+            filter_bins = [x if x != 4 else 'y-max' for x in filter_bins]
+            filter_bins = [x if x != 5 else 'z-min' for x in filter_bins]
+            filter_bins = [x if x != 6 else 'z-max' for x in filter_bins]
+            df = pd.concat([df, pd.DataFrame({self.type : filter_bins})])
+
         # universe, material, surface, cell, and cellborn filters
         else:
             filter_bins = np.repeat(self.bins, self.stride)

openmc/mgxs/__init__.py

@@ -1,3 +1,4 @@
 from openmc.mgxs.groups import EnergyGroups
 from openmc.mgxs.library import Library
 from openmc.mgxs.mgxs import *
+from openmc.mgxs.mdgxs import *

openmc/mgxs/library.py

@@ -11,6 +11,7 @@ import numpy as np
 import openmc
 import openmc.mgxs
 import openmc.checkvalue as cv
+from openmc.tallies import ESTIMATOR_TYPES
 
 
 if sys.version_info[0] >= 3:
@@ -18,17 +19,18 @@ if sys.version_info[0] >= 3:
 
 
 class Library(object):
-    """A multi-group cross section library for some energy group structure.
+    """A multi-energy-group and multi-delayed-group cross section library for
+    some energy group structure.
 
     This class can be used for both OpenMC input generation and tally data
     post-processing to compute spatially-homogenized and energy-integrated
     multi-group cross sections for deterministic neutronics calculations.
 
-    This class helps automate the generation of MGXS objects for some energy
-    group structure and domain type. The Library serves as a collection for
-    MGXS objects with routines to automate the initialization of tallies for
-    input files, the loading of tally data from statepoint files, data storage,
-    energy group condensation and more.
+    This class helps automate the generation of MGXS and MDGXS objects for some
+    energy group structure and domain type. The Library serves as a collection
+    for MGXS and MDGXS objects with routines to automate the initialization of
+    tallies for input files, the loading of tally data from statepoint files,
+    data storage, energy group condensation and more.
 
     Parameters
     ----------
@@ -39,7 +41,7 @@ class Library(object):
     mgxs_types : Iterable of str
         The types of cross sections in the library (e.g., ['total', 'scatter'])
     name : str, optional
-        Name of the multi-group cross section. library Used as a label to
+        Name of the multi-group cross section library. Used as a label to
         identify tallies in OpenMC 'tallies.xml' file.
 
     Attributes
@@ -64,6 +66,11 @@ class Library(object):
         The highest legendre moment in the scattering matrices (default is 0)
     energy_groups : openmc.mgxs.EnergyGroups
         Energy group structure for energy condensation
+    delayed_groups : list of int
+        Delayed groups to filter out the xs
+    estimator : str or None
+        The tally estimator used to compute multi-group cross sections. If None,
+        the default for each MGXS type is used.
     tally_trigger : openmc.Trigger
         An (optional) tally precision trigger given to each tally used to
         compute the cross section
@@ -95,6 +102,7 @@ class Library(object):
         self._domain_type = None
         self._domains = 'all'
         self._energy_groups = None
+        self._delayed_groups = None
         self._correction = 'P0'
         self._legendre_order = 0
         self._tally_trigger = None
@@ -102,6 +110,7 @@ class Library(object):
         self._sp_filename = None
         self._keff = None
         self._sparse = False
+        self._estimator = None
 
         self.name = name
         self.openmc_geometry = openmc_geometry
@@ -126,6 +135,7 @@ class Library(object):
             clone._correction = self.correction
             clone._legendre_order = self.legendre_order
             clone._energy_groups = copy.deepcopy(self.energy_groups, memo)
+            clone._delayed_groups = copy.deepcopy(self.delayed_groups, memo)
             clone._tally_trigger = copy.deepcopy(self.tally_trigger, memo)
             clone._all_mgxs = copy.deepcopy(self.all_mgxs)
             clone._sp_filename = self._sp_filename
@@ -194,6 +204,10 @@ class Library(object):
     def energy_groups(self):
         return self._energy_groups
 
+    @property
+    def delayed_groups(self):
+        return self._delayed_groups
+
     @property
     def correction(self):
         return self._correction
@@ -206,10 +220,21 @@ class Library(object):
     def tally_trigger(self):
         return self._tally_trigger
 
+    @property
+    def estimator(self):
+        return self._estimator
+
     @property
     def num_groups(self):
         return self.energy_groups.num_groups
 
+    @property
+    def num_delayed_groups(self):
+        if self.delayed_groups == None:
+            return 0
+        else:
+            return len(self.delayed_groups)
+
     @property
     def all_mgxs(self):
         return self._all_mgxs
@@ -239,22 +264,33 @@ class Library(object):
 
     @mgxs_types.setter
     def mgxs_types(self, mgxs_types):
+        all_mgxs_types = openmc.mgxs.MGXS_TYPES + openmc.mgxs.MDGXS_TYPES
         if mgxs_types == 'all':
-            self._mgxs_types = openmc.mgxs.MGXS_TYPES
+            self._mgxs_types = all_mgxs_types
         else:
             cv.check_iterable_type('mgxs_types', mgxs_types, basestring)
             for mgxs_type in mgxs_types:
-                cv.check_value('mgxs_type', mgxs_type, openmc.mgxs.MGXS_TYPES)
+                cv.check_value('mgxs_type', mgxs_type, all_mgxs_types)
             self._mgxs_types = mgxs_types
 
     @by_nuclide.setter
     def by_nuclide(self, by_nuclide):
         cv.check_type('by_nuclide', by_nuclide, bool)
+
+        if by_nuclide == True and self.domain_type == 'mesh':
+            raise ValueError('Unable to create MGXS library by nuclide with '
+                             'mesh domain')
+
         self._by_nuclide = by_nuclide
 
     @domain_type.setter
     def domain_type(self, domain_type):
         cv.check_value('domain type', domain_type, openmc.mgxs.DOMAIN_TYPES)
+
+        if self.by_nuclide == True and domain_type == 'mesh':
+            raise ValueError('Unable to create MGXS library by nuclide with '
+                             'mesh domain')
+
         self._domain_type = domain_type
 
     @domains.setter
@@ -298,6 +334,23 @@ class Library(object):
         cv.check_type('energy groups', energy_groups, openmc.mgxs.EnergyGroups)
         self._energy_groups = energy_groups
 
+    @delayed_groups.setter
+    def delayed_groups(self, delayed_groups):
+
+        if delayed_groups != None:
+
+            cv.check_type('delayed groups', delayed_groups, list, int)
+            cv.check_greater_than('num delayed groups', len(delayed_groups), 0)
+
+            # Check that the groups are within [1, MAX_DELAYED_GROUPS]
+            for group in delayed_groups:
+                cv.check_greater_than('delayed group', group, 0)
+                cv.check_less_than('delayed group', group,
+                                   openmc.mgxs.MAX_DELAYED_GROUPS,
+                                   equality=True)
+
+            self._delayed_groups = delayed_groups
+
     @correction.setter
     def correction(self, correction):
         cv.check_value('correction', correction, ('P0', None))
@@ -327,6 +380,11 @@ class Library(object):
         cv.check_type('tally trigger', tally_trigger, openmc.Trigger)
         self._tally_trigger = tally_trigger
 
+    @estimator.setter
+    def estimator(self, estimator):
+        cv.check_value('estimator', estimator, ESTIMATOR_TYPES)
+        self._estimator = estimator
+
     @sparse.setter
     def sparse(self, sparse):
         """Convert tally data from NumPy arrays to SciPy list of lists (LIL)
@@ -363,14 +421,23 @@ class Library(object):
         for domain in self.domains:
             self.all_mgxs[domain.id] = OrderedDict()
             for mgxs_type in self.mgxs_types:
-                mgxs = openmc.mgxs.MGXS.get_mgxs(mgxs_type, name=self.name)
+                if mgxs_type in openmc.mgxs.MDGXS_TYPES:
+                    mgxs = openmc.mgxs.MDGXS.get_mgxs(mgxs_type, name=self.name)
+                else:
+                    mgxs = openmc.mgxs.MGXS.get_mgxs(mgxs_type, name=self.name)
+
                 mgxs.domain = domain
                 mgxs.domain_type = self.domain_type
                 mgxs.energy_groups = self.energy_groups
                 mgxs.by_nuclide = self.by_nuclide
+                if self.estimator is not None:
+                    mgxs.estimator = self.estimator
+
+                if mgxs_type in openmc.mgxs.MDGXS_TYPES:
+                    mgxs.delayed_groups = self.delayed_groups
 
                 # If a tally trigger was specified, add it to the MGXS
-                if self.tally_trigger:
+                if self.tally_trigger is not None:
                     mgxs.tally_trigger = self.tally_trigger
 
                 # Specify whether to use a transport ('P0') correction
@@ -460,7 +527,7 @@ class Library(object):
         ----------
         domain : Material or Cell or Universe or Integral
             The material, cell, or universe object of interest (or its ID)
-        mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi', 'chi-prompt', 'inverse-velocity', 'prompt-nu-fission'}
+        mgxs_type : {'total', 'transport', 'nu-transport', 'absorption', 'capture', 'fission', 'nu-fission', 'kappa-fission', 'scatter', 'nu-scatter', 'scatter matrix', 'nu-scatter matrix', 'multiplicity matrix', 'nu-fission matrix', chi', 'chi-prompt', 'inverse-velocity', 'prompt-nu-fission', 'delayed-nu-fission', 'chi-delayed', 'beta'}
             The type of multi-group cross section object to return
 
         Returns
@@ -763,7 +830,7 @@ class Library(object):
 
         Parameters
         ----------
-        domain : openmc.Material or openmc.Cell or openmc.Universe
+        domain : openmc.Material or openmc.Cell or openmc.Universe or openmc.Mesh
             The domain for spatial homogenization
         xsdata_name : str
             Name to apply to the "xsdata" entry produced by this method
@@ -811,7 +878,7 @@ class Library(object):
         """
 
         cv.check_type('domain', domain, (openmc.Material, openmc.Cell,
-                                         openmc.Cell))
+                                         openmc.Cell, openmc.Mesh))
         cv.check_type('xsdata_name', xsdata_name, basestring)
         cv.check_type('nuclide', nuclide, basestring)
         cv.check_value('xs_type', xs_type, ['macro', 'micro'])

openmc/mgxs/mgxs.py

@@ -13,6 +13,7 @@ import numpy as np
 
 import openmc
 import openmc.checkvalue as cv
+from openmc.tallies import ESTIMATOR_TYPES
 from openmc.mgxs import EnergyGroups
 
 if sys.version_info[0] >= 3:
@@ -39,7 +40,6 @@ MGXS_TYPES = ['total',
               'inverse-velocity',
               'prompt-nu-fission']
 
-
 # Supported domain types
 DOMAIN_TYPES = ['cell',
                 'distribcell',
@@ -102,7 +102,7 @@ class MGXS(object):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section
@@ -144,11 +144,11 @@ class MGXS(object):
 
     def __init__(self, domain=None, domain_type=None,
                  energy_groups=None, by_nuclide=False, name=''):
-
         self._name = ''
         self._rxn_type = None
         self._by_nuclide = None
         self._nuclides = None
+        self._estimator = 'tracklength'
         self._domain = None
         self._domain_type = None
         self._energy_groups = None
@@ -160,6 +160,7 @@ class MGXS(object):
         self._loaded_sp = False
         self._derived = False
         self._hdf5_key = None
+        self._valid_estimators = ESTIMATOR_TYPES
 
         self.name = name
         self.by_nuclide = by_nuclide
@@ -250,7 +251,7 @@ class MGXS(object):
 
     @property
     def estimator(self):
-        return 'tracklength'
+        return self._estimator
 
     @property
     def tallies(self):
@@ -368,6 +369,11 @@ class MGXS(object):
         cv.check_iterable_type('nuclides', nuclides, basestring)
         self._nuclides = nuclides
 
+    @estimator.setter
+    def estimator(self, estimator):
+        cv.check_value('estimator', estimator, self._valid_estimators)
+        self._estimator = estimator
+
     @domain.setter
     def domain(self, domain):
         cv.check_type('domain', domain, _DOMAINS)
@@ -722,11 +728,13 @@ class MGXS(object):
 
     def get_xs(self, groups='all', subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               value='mean', **kwargs):
+               value='mean', squeeze=True, **kwargs):
         r"""Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        cross section data data for one or more energy groups and subdomains.
+        This method constructs a 3D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups (2nd dimension), and nuclides
+        (3rd dimension).
 
         Parameters
         ----------
@@ -748,6 +756,9 @@ class MGXS(object):
             Defaults to 'increasing'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -817,25 +828,29 @@ class MGXS(object):
             if value == 'mean' or value == 'std_dev':
                 xs /= densities[np.newaxis, :, np.newaxis]
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        if groups == 'all':
+            num_groups = self.num_groups
+        else:
+            num_groups = len(groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / num_groups)
+        new_shape = (num_subdomains, num_groups) + xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if groups == 'all':
-                num_groups = self.num_groups
-            else:
-                num_groups = len(groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] / num_groups)
-            new_shape = (num_subdomains, num_groups) + xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, :]
 
-        # Eliminate trivial dimensions
-        xs = np.squeeze(xs)
-        xs = np.atleast_1d(xs)
+        if squeeze:
+            xs = np.squeeze(xs)
+            xs = np.atleast_1d(xs)
+
         return xs
 
     def get_condensed_xs(self, coarse_groups):
@@ -1348,8 +1363,6 @@ class MGXS(object):
                 std_dev = self.get_xs(subdomains=[subdomain], nuclides=[nuclide],
                                       xs_type=xs_type, value='std_dev',
                                       row_column=row_column)
-                average = average.squeeze()
-                std_dev = std_dev.squeeze()
 
                 # Add MGXS results data to the HDF5 group
                 nuclide_group.require_dataset('average', dtype=np.float64,
@@ -1515,15 +1528,14 @@ class MGXS(object):
         if 'energy low [MeV]' in df and 'energyout low [MeV]' in df:
             df.rename(columns={'energy low [MeV]': 'group in'},
                       inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
-            in_groups = np.repeat(in_groups, df.shape[0] / in_groups.size)
+            in_groups = np.tile(all_groups, int(self.num_subdomains))
+            in_groups = np.repeat(in_groups, int(df.shape[0] / in_groups.size))
             df['group in'] = in_groups
             del df['energy high [MeV]']
 
             df.rename(columns={'energyout low [MeV]': 'group out'},
                       inplace=True)
-            out_groups = np.repeat(all_groups, self.xs_tally.num_scores)
-            out_groups = np.tile(out_groups, df.shape[0] / out_groups.size)
+            out_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group out'] = out_groups
             del df['energyout high [MeV]']
             columns = ['group in', 'group out']
@@ -1531,14 +1543,14 @@ class MGXS(object):
         elif 'energyout low [MeV]' in df:
             df.rename(columns={'energyout low [MeV]': 'group out'},
                       inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
+            in_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group out'] = in_groups
             del df['energyout high [MeV]']
             columns = ['group out']
 
         elif 'energy low [MeV]' in df:
             df.rename(columns={'energy low [MeV]': 'group in'}, inplace=True)
-            in_groups = np.tile(all_groups, self.num_subdomains)
+            in_groups = np.tile(all_groups, int(df.shape[0] / all_groups.size))
             df['group in'] = in_groups
             del df['energy high [MeV]']
             columns = ['group in']
@@ -1569,6 +1581,7 @@ class MGXS(object):
                                (mesh_str, 'z')] + columns, inplace=True)
         else:
             df.sort_values(by=[self.domain_type] + columns, inplace=True)
+
         return df
 
     def get_units(self, xs_type='macro'):
@@ -1643,7 +1656,7 @@ class MatrixMGXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section
@@ -1692,18 +1705,16 @@ class MatrixMGXS(MGXS):
 
         return [[energy], [energy, energyout]]
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     def get_xs(self, in_groups='all', out_groups='all',
                subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               row_column='inout', value='mean', **kwargs):
+               row_column='inout', value='mean', squeeze=True, **kwargs):
         """Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        matrix data for one or more energy groups and subdomains.
+        This method constructs a 4D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups in (2nd dimension), energy groups out
+        (3rd dimension), and nuclides (4th dimension).
 
         Parameters
         ----------
@@ -1732,6 +1743,9 @@ class MatrixMGXS(MGXS):
             Defaults to 'inout'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -1803,8 +1817,6 @@ class MatrixMGXS(MGXS):
                                           filter_bins=filter_bins,
                                           nuclides=query_nuclides, value=value)
 
-        xs = np.nan_to_num(xs)
-
         # Divide by atom number densities for microscopic cross sections
         if xs_type == 'micro':
             if self.by_nuclide:
@@ -1814,33 +1826,36 @@ class MatrixMGXS(MGXS):
             if value == 'mean' or value == 'std_dev':
                 xs /= densities[np.newaxis, :, np.newaxis]
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        if in_groups == 'all':
+            num_in_groups = self.num_groups
+        else:
+            num_in_groups = len(in_groups)
+
+        if out_groups == 'all':
+            num_out_groups = self.num_groups
+        else:
+            num_out_groups = len(out_groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
+        new_shape = (num_subdomains, num_in_groups, num_out_groups)
+        new_shape += xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
+        # Transpose the matrix if requested by user
+        if row_column == 'outin':
+            xs = np.swapaxes(xs, 1, 2)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if in_groups == 'all':
-                num_in_groups = self.num_groups
-            else:
-                num_in_groups = len(in_groups)
-            if out_groups == 'all':
-                num_out_groups = self.num_groups
-            else:
-                num_out_groups = len(out_groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] /
-                                 (num_in_groups * num_out_groups))
-            new_shape = (num_subdomains, num_in_groups, num_out_groups)
-            new_shape += xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Transpose the matrix if requested by user
-            if row_column == 'outin':
-                xs = np.swapaxes(xs, 1, 2)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_2d(xs)
 
@@ -2072,7 +2087,7 @@ class TotalXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2190,7 +2205,7 @@ class TransportXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2233,6 +2248,8 @@ class TransportXS(MGXS):
         super(TransportXS, self).__init__(domain, domain_type,
                                           groups, by_nuclide, name)
         self._rxn_type = 'transport'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -2245,10 +2262,6 @@ class TransportXS(MGXS):
         energyout_filter = openmc.Filter('energyout', group_edges)
         return [[energy_filter], [energy_filter], [energyout_filter]]
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     @property
     def rxn_rate_tally(self):
         if self._rxn_rate_tally is None:
@@ -2320,7 +2333,7 @@ class NuTransportXS(TransportXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2441,7 +2454,7 @@ class AbsorptionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2458,7 +2471,8 @@ class AbsorptionXS(MGXS):
         The number of subdomains is unity for 'material', 'cell' and 'universe'
         domain types. This is equal to the number of cell instances
         for 'distribcell' domain types (it is equal to unity prior to loading
-        tally data from a statepoint file).
+        tally data from a statepoint file) and the number of mesh cells for
+        'mesh' domain types.
     num_nuclides : int
         The number of nuclides for which the multi-group cross section is
         being tracked. This is unity if the by_nuclide attribute is False.
@@ -2557,7 +2571,7 @@ class CaptureXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2679,7 +2693,7 @@ class FissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2790,7 +2804,7 @@ class NuFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -2834,7 +2848,6 @@ class NuFissionXS(MGXS):
                                           groups, by_nuclide, name)
         self._rxn_type = 'nu-fission'
 
-
 class KappaFissionXS(MGXS):
     r"""A recoverable fission energy production rate multi-group cross section.
 
@@ -2906,7 +2919,7 @@ class KappaFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3019,7 +3032,7 @@ class ScatterXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3134,7 +3147,7 @@ class NuScatterXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3177,10 +3190,8 @@ class NuScatterXS(MGXS):
         super(NuScatterXS, self).__init__(domain, domain_type,
                                           groups, by_nuclide, name)
         self._rxn_type = 'nu-scatter'
-
-    @property
-    def estimator(self):
-        return 'analog'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
 
 class ScatterMatrixXS(MatrixMGXS):
@@ -3268,7 +3279,7 @@ class ScatterMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -3314,6 +3325,8 @@ class ScatterMatrixXS(MatrixMGXS):
         self._correction = 'P0'
         self._legendre_order = 0
         self._hdf5_key = 'scatter matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     def __deepcopy__(self, memo):
         clone = super(ScatterMatrixXS, self).__deepcopy__(memo)
@@ -3517,11 +3530,13 @@ class ScatterMatrixXS(MatrixMGXS):
     def get_xs(self, in_groups='all', out_groups='all',
                subdomains='all', nuclides='all', moment='all',
                xs_type='macro', order_groups='increasing',
-               row_column='inout', value='mean'):
+               row_column='inout', value='mean', squeeze=True):
         r"""Returns an array of multi-group cross sections.
 
-        This method constructs a 2D NumPy array for the requested scattering
-        matrix data data for one or more energy groups and subdomains.
+        This method constructs a 5D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups in (2nd dimension), energy groups out
+        (3rd dimension), nuclides (4th dimension), and moments (5th dimension).
 
         NOTE: The scattering moments are not multiplied by the :math:`(2l+1)/2`
         prefactor in the expansion of the scattering source into Legendre
@@ -3557,6 +3572,9 @@ class ScatterMatrixXS(MatrixMGXS):
             Defaults to 'inout'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -3635,8 +3653,6 @@ class ScatterMatrixXS(MatrixMGXS):
                                           filter_bins=filter_bins,
                                           nuclides=query_nuclides, value=value)
 
-        xs = np.nan_to_num(xs)
-
         # Divide by atom number densities for microscopic cross sections
         if xs_type == 'micro':
             if self.by_nuclide:
@@ -3646,32 +3662,35 @@ class ScatterMatrixXS(MatrixMGXS):
             if value == 'mean' or value == 'std_dev':
                 xs /= densities[np.newaxis, :, np.newaxis]
 
+        # Convert and nans to zero
+        xs = np.nan_to_num(xs)
+
+        if in_groups == 'all':
+            num_in_groups = self.num_groups
+        else:
+            num_in_groups = len(in_groups)
+
+        if out_groups == 'all':
+            num_out_groups = self.num_groups
+        else:
+            num_out_groups = len(out_groups)
+
+        # Reshape tally data array with separate axes for domain and energy
+        num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
+        new_shape = (num_subdomains, num_in_groups, num_out_groups)
+        new_shape += xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
+        # Transpose the scattering matrix if requested by user
+        if row_column == 'outin':
+            xs = np.swapaxes(xs, 1, 2)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-            if in_groups == 'all':
-                num_in_groups = self.num_groups
-            else:
-                num_in_groups = len(in_groups)
-            if out_groups == 'all':
-                num_out_groups = self.num_groups
-            else:
-                num_out_groups = len(out_groups)
-
-            # Reshape tally data array with separate axes for domain and energy
-            num_subdomains = int(xs.shape[0] / (num_in_groups * num_out_groups))
-            new_shape = (num_subdomains, num_in_groups, num_out_groups)
-            new_shape += xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Transpose the scattering matrix if requested by user
-            if row_column == 'outin':
-                xs = np.swapaxes(xs, 1, 2)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_2d(xs)
 
@@ -3728,7 +3747,7 @@ class ScatterMatrixXS(MatrixMGXS):
         if self.legendre_order > 0:
             # Insert a column corresponding to the Legendre moments
             moments = ['P{}'.format(i) for i in range(self.legendre_order+1)]
-            moments = np.tile(moments, df.shape[0] / len(moments))
+            moments = np.tile(moments, int(df.shape[0] / len(moments)))
             df['moment'] = moments
 
             # Place the moment column before the mean column
@@ -3929,7 +3948,7 @@ class NuScatterMatrixXS(ScatterMatrixXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4051,7 +4070,7 @@ class MultiplicityMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4094,6 +4113,8 @@ class MultiplicityMatrixXS(MatrixMGXS):
         super(MultiplicityMatrixXS, self).__init__(domain, domain_type, groups,
                                                    by_nuclide, name)
         self._rxn_type = 'multiplicity matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -4198,7 +4219,7 @@ class NuFissionMatrixXS(MatrixMGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4242,6 +4263,8 @@ class NuFissionMatrixXS(MatrixMGXS):
                                                 groups, by_nuclide, name)
         self._rxn_type = 'nu-fission'
         self._hdf5_key = 'nu-fission matrix'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
 
 class Chi(MGXS):
@@ -4313,7 +4336,7 @@ class Chi(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4355,6 +4378,8 @@ class Chi(MGXS):
                  groups=None, by_nuclide=False, name=''):
         super(Chi, self).__init__(domain, domain_type, groups, by_nuclide, name)
         self._rxn_type = 'chi'
+        self._estimator = 'analog'
+        self._valid_estimators = ['analog']
 
     @property
     def scores(self):
@@ -4372,10 +4397,6 @@ class Chi(MGXS):
     def tally_keys(self):
         return ['nu-fission-in', 'nu-fission-out']
 
-    @property
-    def estimator(self):
-        return 'analog'
-
     @property
     def rxn_rate_tally(self):
         if self._rxn_rate_tally is None:
@@ -4512,11 +4533,13 @@ class Chi(MGXS):
 
     def get_xs(self, groups='all', subdomains='all', nuclides='all',
                xs_type='macro', order_groups='increasing',
-               value='mean', **kwargs):
+               value='mean', squeeze=True, **kwargs):
         """Returns an array of the fission spectrum.
 
-        This method constructs a 2D NumPy array for the requested multi-group
-        cross section data data for one or more energy groups and subdomains.
+        This method constructs a 3D NumPy array for the requested
+        multi-group cross section data for one or more subdomains
+        (1st dimension), energy groups (2nd dimension), and nuclides
+        (3rd dimension).
 
         Parameters
         ----------
@@ -4538,6 +4561,9 @@ class Chi(MGXS):
             Defaults to 'increasing'.
         value : {'mean', 'std_dev', 'rel_err'}
             A string for the type of value to return. Defaults to 'mean'.
+        squeeze : bool
+            A boolean representing whether to eliminate the extra dimensions
+            of the multi-dimensional array to be returned. Defaults to True.
 
         Returns
         -------
@@ -4629,27 +4655,29 @@ class Chi(MGXS):
             xs = self.xs_tally.get_values(filters=filters,
                                           filter_bins=filter_bins, value=value)
 
+        # Eliminate the trivial score dimension
+        xs = np.squeeze(xs, axis=len(xs.shape) - 1)
+        xs = np.nan_to_num(xs)
+
+        # Reshape tally data array with separate axes for domain and energy
+        if groups == 'all':
+            num_groups = self.num_groups
+        else:
+            num_groups = len(groups)
+
+        num_subdomains = int(xs.shape[0] / num_groups)
+        new_shape = (num_subdomains, num_groups) + xs.shape[1:]
+        xs = np.reshape(xs, new_shape)
+
         # Reverse data if user requested increasing energy groups since
         # tally data is stored in order of increasing energies
         if order_groups == 'increasing':
-
-            # Reshape tally data array with separate axes for domain and energy
-            if groups == 'all':
-                num_groups = self.num_groups
-            else:
-                num_groups = len(groups)
-            num_subdomains = int(xs.shape[0] / num_groups)
-            new_shape = (num_subdomains, num_groups) + xs.shape[1:]
-            xs = np.reshape(xs, new_shape)
-
-            # Reverse energies to align with increasing energy groups
             xs = xs[:, ::-1, :]
 
-            # Eliminate trivial dimensions
+        if squeeze:
             xs = np.squeeze(xs)
             xs = np.atleast_1d(xs)
 
-        xs = np.nan_to_num(xs)
         return xs
 
     def get_pandas_dataframe(self, groups='all', nuclides='all',
@@ -4758,7 +4786,7 @@ class ChiPrompt(Chi):
 
        \langle \nu^p \sigma_{f,g' \rightarrow g} \phi \rangle &= \int_{r \in V}
        dr \int_{4\pi} d\Omega' \int_0^\infty dE' \int_{E_g}^{E_{g-1}} dE \;
-       \chi(E) \nu^p \sigma_f (r, E') \psi(r, E', \Omega')\\
+       \chi(E)^p \nu^p \sigma_f (r, E') \psi(r, E', \Omega')\\
        \langle \nu^p \sigma_f \phi \rangle &= \int_{r \in V} dr \int_{4\pi}
        d\Omega' \int_0^\infty dE' \int_0^\infty dE \; \chi(E) \nu^p \sigma_f (r,
        E') \psi(r, E', \Omega') \\
@@ -4803,7 +4831,7 @@ class ChiPrompt(Chi):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : 'analog'
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4918,7 +4946,7 @@ class InverseVelocity(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys
@@ -4935,7 +4963,8 @@ class InverseVelocity(MGXS):
         The number of subdomains is unity for 'material', 'cell' and 'universe'
         domain types. This is equal to the number of cell instances
         for 'distribcell' domain types (it is equal to unity prior to loading
-        tally data from a statepoint file).
+        tally data from a statepoint file) and the number of mesh cells for
+        'mesh' domain types.
     num_nuclides : int
         The number of nuclides for which the multi-group cross section is
         being tracked. This is unity if the by_nuclide attribute is False.
@@ -5052,7 +5081,7 @@ class PromptNuFissionXS(MGXS):
     tally_keys : list of str
         The keys into the tallies dictionary for each tally used to compute
         the multi-group cross section
-    estimator : {'tracklength', 'analog'}
+    estimator : {'tracklength', 'collision', 'analog'}
         The tally estimator used to compute the multi-group cross section
     tallies : collections.OrderedDict
         OpenMC tallies needed to compute the multi-group cross section. The keys

openmc/statepoint.py

@@ -701,7 +701,7 @@ class StatePoint(object):
                 if tally_filter.type == 'surface':
                     surface_ids = []
                     for bin in tally_filter.bins:
-                        surface_ids.append(summary.surfaces[bin].id)
+                        surface_ids.append(bin)
                     tally_filter.bins = surface_ids
 
                 if tally_filter.type in ['cell', 'distribcell']:

openmc/tallies.py

@@ -40,6 +40,9 @@ _SCORE_CLASSES = (basestring, CrossScore, AggregateScore)
 _NUCLIDE_CLASSES = (basestring, Nuclide, CrossNuclide, AggregateNuclide)
 _FILTER_CLASSES = (Filter, CrossFilter, AggregateFilter)
 
+# Valid types of estimators
+ESTIMATOR_TYPES = ['tracklength', 'collision', 'analog']
+
 
 def reset_auto_tally_id():
     """Reset counter for auto-generated tally IDs."""
@@ -387,8 +390,7 @@ class Tally(object):
 
     @estimator.setter
     def estimator(self, estimator):
-        cv.check_value('estimator', estimator,
-                       ['analog', 'tracklength', 'collision'])
+        cv.check_value('estimator', estimator, ESTIMATOR_TYPES)
         self._estimator = estimator
 
     @triggers.setter
@@ -795,6 +797,9 @@ class Tally(object):
             else:
                 no_scores_match = False
 
+            if score == 'current' and score not in self.scores:
+                return False
+
         # Nuclides cannot be specified on 'flux' scores
         if 'flux' in self.scores or 'flux' in other.scores:
             if self.nuclides != other.nuclides:
@@ -2197,8 +2202,8 @@ class Tally(object):
 
         """
 
-        cv.check_type('filter1', filter1, (Filter, CrossFilter, AggregateFilter))
-        cv.check_type('filter2', filter2, (Filter, CrossFilter, AggregateFilter))
+        cv.check_type('filter1', filter1, _FILTER_CLASSES)
+        cv.check_type('filter2', filter2, _FILTER_CLASSES)
 
         # Check that the filters exist in the tally and are not the same
         if filter1 == filter2:
@@ -2280,8 +2285,8 @@ class Tally(object):
                   'since it does not contain any results.'.format(self.id)
             raise ValueError(msg)
 
-        cv.check_type('nuclide1', nuclide1, Nuclide)
-        cv.check_type('nuclide2', nuclide2, Nuclide)
+        cv.check_type('nuclide1', nuclide1, _NUCLIDE_CLASSES)
+        cv.check_type('nuclide2', nuclide2, _NUCLIDE_CLASSES)
 
         # Check that the nuclides exist in the tally and are not the same
         if nuclide1 == nuclide2:
@@ -3318,7 +3323,7 @@ class Tally(object):
 
         """
 
-        cv.check_type('new_filter', new_filter, Filter)
+        cv.check_type('new_filter', new_filter, _FILTER_CLASSES)
 
         if new_filter in self.filters:
             msg = 'Unable to diagonalize Tally ID="{0}" which already ' \

scripts/openmc-ace-to-hdf5

@@ -25,6 +25,13 @@ follows the NNDC data convention (1000*Z + A + 300 + 100*m), or the MCNP data
 convention (essentially the same as NNDC, except that the first metastable state
 of Am242 is 95242 and the ground state is 95642).
 
+The optional --fission_energy_release argument will accept an HDF5 file
+containing a library of fission energy release (ENDF MF=1 MT=458) data. A
+library built from ENDF/B-VII.1 data is released with OpenMC and can be found at
+openmc/data/fission_Q_data_endb71.h5. This data is necessary for
+'fission-q-prompt' and 'fission-q-recoverable' tallies, but is not needed
+otherwise.
+
 """
 
 class CustomFormatter(argparse.ArgumentDefaultsHelpFormatter,
@@ -47,6 +54,8 @@ parser.add_argument('--xsdir', help='MCNP xsdir file that lists '
                     'ACE libraries')
 parser.add_argument('--xsdata', help='Serpent xsdata file that lists '
                     'ACE libraries')
+parser.add_argument('--fission_energy_release', help='HDF5 file containing '
+                    'fission energy release data')
 args = parser.parse_args()
 
 if not os.path.isdir(args.destination):
@@ -124,7 +133,16 @@ for filename in ace_libraries:
             except Exception as e:
                 print('Failed to convert {}: {}'.format(table.name, e))
                 continue
-            print('Converting {} (ACE) to {} (HDF5)'.format(table.name, neutron.name))
+
+            # Fission energy release data, if available
+            if args.fission_energy_release is not None:
+                fer = openmc.data.FissionEnergyRelease.from_compact_hdf5(
+                    args.fission_energy_release, neutron)
+                if fer is not None:
+                    neutron.fission_energy = fer
+
+            print('Converting {} (ACE) to {} (HDF5)'.format(table.name,
+                                                            neutron.name))
 
             # Determine filename
             outfile = os.path.join(args.destination,
@@ -137,7 +155,8 @@ for filename in ace_libraries:
         elif table.name.endswith('t'):
             # Thermal scattering data
             thermal = openmc.data.ThermalScattering.from_ace(table)
-            print('Converting {} (ACE) to {} (HDF5)'.format(table.name, thermal.name))
+            print('Converting {} (ACE) to {} (HDF5)'.format(table.name,
+                                                            thermal.name))
 
             # Determine filename
             outfile = os.path.join(args.destination,

src/cmfd_data.F90

@@ -51,9 +51,9 @@ contains
   subroutine compute_xs()
 
     use constants,    only: FILTER_MESH, FILTER_ENERGYIN, FILTER_ENERGYOUT,    &
-                           FILTER_SURFACE, IN_RIGHT, OUT_RIGHT, IN_FRONT,      &
-                           OUT_FRONT, IN_TOP, OUT_TOP, CMFD_NOACCEL, ZERO,     &
-                           ONE, TINY_BIT
+                           FILTER_SURFACE, OUT_LEFT, OUT_RIGHT, OUT_BACK,      &
+                           OUT_FRONT, OUT_BOTTOM, OUT_TOP, CMFD_NOACCEL,       &
+                           ZERO, ONE, TINY_BIT
     use error,        only: fatal_error
     use global,       only: cmfd, n_cmfd_tallies, cmfd_tallies, meshes,&
                            matching_bins
@@ -236,23 +236,33 @@ contains
 
                 ! Left surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i-1, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_RIGHT
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_LEFT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t%stride) + 1 ! outgoing
                 cmfd % current(1,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_RIGHT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(2,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (i > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i-1, j, k /))
+                  matching_bins(i_filter_surf) = OUT_RIGHT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(2,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Right surface
+                if (i < nx) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i+1, j, k /) )
+                  matching_bins(i_filter_surf) = OUT_LEFT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(3,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_RIGHT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(3,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /) )
                 matching_bins(i_filter_surf) = OUT_RIGHT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
@@ -260,23 +270,33 @@ contains
 
                 ! Back surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j-1, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_FRONT
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_BACK
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
                 cmfd % current(5,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_FRONT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(6,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (j > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j-1, k /))
+                  matching_bins(i_filter_surf) = OUT_FRONT
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(6,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Front surface
+                if (j < ny) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j+1, k /))
+                  matching_bins(i_filter_surf) = OUT_BACK
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(7,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_FRONT
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(7,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /))
                 matching_bins(i_filter_surf) = OUT_FRONT
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
@@ -284,23 +304,33 @@ contains
 
                 ! Bottom surface
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k-1 /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_TOP
+                     (/ i, j, k /))
+                matching_bins(i_filter_surf) = OUT_BOTTOM
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing
                 cmfd % current(9,h,i,j,k) = t % results(1,score_index) % sum
-                matching_bins(i_filter_surf) = OUT_TOP
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(10,h,i,j,k) = t % results(1,score_index) % sum
+
+                if (k > 1) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j, k-1 /))
+                  matching_bins(i_filter_surf) = OUT_TOP
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(10,h,i,j,k) = t % results(1,score_index) % sum
+                end if
 
                 ! Top surface
+                if (k < nz) then
+                  matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
+                       (/ i, j, k+1 /))
+                  matching_bins(i_filter_surf) = OUT_BOTTOM
+                  score_index = sum((matching_bins(1:size(t % filters)) - 1) &
+                       * t % stride) + 1 ! incoming
+                  cmfd % current(11,h,i,j,k) = t % results(1,score_index) % sum
+                end if
+
                 matching_bins(i_filter_mesh) = mesh_indices_to_bin(m, &
-                     (/ i, j, k /) + 1, .true.)
-                matching_bins(i_filter_surf) = IN_TOP
-                score_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                     * t % stride) + 1 ! incoming
-                cmfd % current(11,h,i,j,k) = t % results(1,score_index) % sum
+                     (/ i, j, k /))
                 matching_bins(i_filter_surf) = OUT_TOP
                 score_index = sum((matching_bins(1:size(t % filters)) - 1) &
                      * t % stride) + 1 ! outgoing

src/cmfd_input.F90

@@ -534,10 +534,10 @@ contains
           filt % n_bins = 2 * m % n_dimension
           allocate(filt % surfaces(2 * m % n_dimension))
           if (m % n_dimension == 2) then
-            filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT /)
+            filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT /)
           elseif (m % n_dimension == 3) then
-            filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT, &
-                 IN_TOP, OUT_TOP /)
+            filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT, &
+                 OUT_BOTTOM, OUT_TOP /)
           end if
         end select
         t % find_filter(FILTER_SURFACE) = n_filters

src/constants.F90

@@ -289,7 +289,7 @@ module constants
        EVENT_ABSORB  =  2
 
   ! Tally score type
-  integer, parameter :: N_SCORE_TYPES = 21
+  integer, parameter :: N_SCORE_TYPES = 23
   integer, parameter :: &
        SCORE_FLUX               = -1,  & ! flux
        SCORE_TOTAL              = -2,  & ! total reaction rate
@@ -311,7 +311,9 @@ module constants
        SCORE_EVENTS             = -18, & ! number of events
        SCORE_DELAYED_NU_FISSION = -19, & ! delayed neutron production rate
        SCORE_PROMPT_NU_FISSION  = -20, & ! prompt neutron production rate
-       SCORE_INVERSE_VELOCITY   = -21    ! flux-weighted inverse velocity
+       SCORE_INVERSE_VELOCITY   = -21, & ! flux-weighted inverse velocity
+       SCORE_FISS_Q_PROMPT      = -22, & ! prompt fission Q-value
+       SCORE_FISS_Q_RECOV       = -23    ! recoverable fission Q-value
 
   ! Maximum scattering order supported
   integer, parameter :: MAX_ANG_ORDER = 10
@@ -356,12 +358,12 @@ module constants
 
   ! Tally surface current directions
   integer, parameter :: &
-       IN_RIGHT  = 1,   &
-       OUT_RIGHT = 2,   &
-       IN_FRONT  = 3,   &
-       OUT_FRONT = 4,   &
-       IN_TOP    = 5,   &
-       OUT_TOP   = 6
+       OUT_LEFT   = 1,   &   ! x min
+       OUT_RIGHT  = 2,   &   ! x max
+       OUT_BACK   = 3,   &   ! y min
+       OUT_FRONT  = 4,   &   ! y max
+       OUT_BOTTOM = 5,   &   ! z min
+       OUT_TOP    = 6        ! z max
 
   ! Tally trigger types and threshold
   integer, parameter :: &

src/endf.F90

@@ -14,7 +14,7 @@ contains
   pure function reaction_name(MT) result(string)
 
     integer, intent(in) :: MT
-    character(20)       :: string
+    character(MAX_WORD_LEN) :: string
 
     select case (MT)
     ! Special reactions for tallies
@@ -60,6 +60,10 @@ contains
       string = "events"
     case (SCORE_INVERSE_VELOCITY)
       string = "inverse-velocity"
+    case (SCORE_FISS_Q_PROMPT)
+      string = "fission-q-prompt"
+    case (SCORE_FISS_Q_RECOV)
+      string = "fission-q-recoverable"
 
     ! Normal ENDF-based reactions
     case (TOTAL_XS)

src/endf_header.F90

@@ -30,17 +30,6 @@ module endf_header
     end subroutine function1d_from_hdf5_
   end interface
 
-!===============================================================================
-! CONSTANT1D represents a constant one-dimensional function
-!===============================================================================
-
-  type, extends(Function1D) :: Constant1D
-    real(8) :: y
-  contains
-    procedure :: from_hdf5 => constant1d_from_hdf5
-    procedure :: evaluate => constant1d_evaluate
-  end type Constant1D
-
 !===============================================================================
 ! POLYNOMIAL represents a one-dimensional function expressed as a polynomial
 !===============================================================================
@@ -72,25 +61,6 @@ module endf_header
 
 contains
 
-!===============================================================================
-! Constant1D implementation
-!===============================================================================
-
-  subroutine constant1d_from_hdf5(this, dset_id)
-    class(Constant1D), intent(inout) :: this
-    integer(HID_T),    intent(in)    :: dset_id
-
-    call read_dataset(this % y, dset_id)
-  end subroutine constant1d_from_hdf5
-
-  pure function constant1d_evaluate(this, x) result(y)
-    class(Constant1D), intent(in) :: this
-    real(8),           intent(in) :: x
-    real(8)                       :: y
-
-    y = this % y
-  end function constant1d_evaluate
-
 !===============================================================================
 ! Polynomial implementation
 !===============================================================================

src/input_xml.F90

@@ -3047,18 +3047,18 @@ contains
                    // " specified on tally " // trim(to_str(t % id)))
             end if
 
-            ! Determine number of bins -- this is assuming that the tally is
-            ! a volume tally and not a surface current tally. If it is a
-            ! surface current tally, the number of bins will get reset later
+            ! Determine number of bins
             filt % n_bins = product(m % dimension)
 
             ! Store the index of the mesh
             filt % mesh = i_mesh
           end select
+
           ! Set the filter index in the tally find_filter array
           t % find_filter(FILTER_MESH) = j
 
         case ('energy')
+
           ! Allocate and declare the filter type
           allocate(EnergyFilter::t % filters(j) % obj)
           select type (filt => t % filters(j) % obj)
@@ -3661,6 +3661,10 @@ contains
             t % score_bins(j) = SCORE_KAPPA_FISSION
           case ('inverse-velocity')
             t % score_bins(j) = SCORE_INVERSE_VELOCITY
+          case ('fission-q-prompt')
+            t % score_bins(j) = SCORE_FISS_Q_PROMPT
+          case ('fission-q-recoverable')
+            t % score_bins(j) = SCORE_FISS_Q_RECOV
           case ('current')
             t % score_bins(j) = SCORE_CURRENT
             t % type = TALLY_SURFACE_CURRENT
@@ -3672,10 +3676,6 @@ contains
                    &same tally as surface currents")
             end if
 
-            ! Since the number of bins for the mesh filter was already set
-            ! assuming it was a volume tally, we need to adjust the number
-            ! of bins
-
             ! Get index of mesh filter
             k = t % find_filter(FILTER_MESH)
 
@@ -3685,19 +3685,6 @@ contains
                    &filter.")
             end if
 
-            ! Declare the type of the mesh filter
-            select type(filt => t % filters(k) % obj)
-            type is (MeshFilter)
-
-              ! Get pointer to mesh
-              i_mesh = filt % mesh
-              m => meshes(i_mesh)
-
-              ! We need to increase the dimension by one since we also need
-              ! currents coming into and out of the boundary mesh cells.
-              filt % n_bins = product(m % dimension + 1)
-            end select
-
             ! Copy filters to temporary array
             allocate(filters(size(t % filters) + 1))
             filters(1:size(t % filters)) = t % filters
@@ -3714,10 +3701,10 @@ contains
               filt % n_bins = 2 * m % n_dimension
               allocate(filt % surfaces(2 * m % n_dimension))
               if (m % n_dimension == 2) then
-                filt % surfaces = (/ IN_RIGHT, OUT_RIGHT, IN_FRONT, OUT_FRONT /)
+                filt % surfaces = (/ OUT_LEFT, OUT_RIGHT, OUT_BACK, OUT_FRONT /)
               elseif (m % n_dimension == 3) then
-                filt % surfaces = (/ IN_RIGHT,  OUT_RIGHT, IN_FRONT, OUT_FRONT,&
-                     IN_TOP, OUT_TOP /)
+                filt % surfaces = (/ OUT_LEFT,  OUT_RIGHT, OUT_BACK, OUT_FRONT,&
+                     OUT_BOTTOM, OUT_TOP /)
               end if
             end select
             t % find_filter(FILTER_SURFACE) = size(t % filters)

src/mesh.F90

@@ -93,30 +93,21 @@ contains
 ! use in a TallyObject results array
 !===============================================================================
 
-  pure function mesh_indices_to_bin(m, ijk, surface_current) result(bin)
+  pure function mesh_indices_to_bin(m, ijk) result(bin)
     type(RegularMesh), intent(in) :: m
     integer, intent(in)           :: ijk(:)
-    logical, intent(in), optional :: surface_current
     integer                       :: bin
 
+    integer :: n_x ! number of mesh cells in x direction
     integer :: n_y ! number of mesh cells in y direction
-    integer :: n_z ! number of mesh cells in z direction
 
-    if (present(surface_current)) then
-      n_y = m % dimension(2) + 1
-    else
-      n_y = m % dimension(2)
-    end if
+    n_x = m % dimension(1)
+    n_y = m % dimension(2)
 
     if (m % n_dimension == 2) then
-      bin = (ijk(1) - 1)*n_y + ijk(2)
+      bin = (ijk(2) - 1)*n_x + ijk(1)
     elseif (m % n_dimension == 3) then
-      if (present(surface_current)) then
-        n_z = m % dimension(3) + 1
-      else
-        n_z = m % dimension(3)
-      end if
-      bin = (ijk(1) - 1)*n_y*n_z + (ijk(2) - 1)*n_z + ijk(3)
+      bin = (ijk(3) - 1)*n_y*n_x + (ijk(2) - 1)*n_x + ijk(1)
     end if
 
   end function mesh_indices_to_bin
@@ -131,19 +122,19 @@ contains
     integer, intent(in)           :: bin
     integer, intent(out)          :: ijk(:)
 
+    integer :: n_x ! number of mesh cells in x direction
     integer :: n_y ! number of mesh cells in y direction
-    integer :: n_z ! number of mesh cells in z direction
 
+    n_x = m % dimension(1)
     n_y = m % dimension(2)
 
     if (m % n_dimension == 2) then
-      ijk(1) = (bin - 1)/n_y + 1
-      ijk(2) = mod(bin - 1, n_y) + 1
+      ijk(1) = mod(bin - 1, n_x) + 1
+      ijk(2) = (bin - 1)/n_x + 1
     else if (m % n_dimension == 3) then
-      n_z = m % dimension(3)
-      ijk(1) = (bin - 1)/(n_y*n_z) + 1
-      ijk(2) = mod(bin - 1, n_y*n_z)/n_z + 1
-      ijk(3) = mod(bin - 1, n_z) + 1
+      ijk(1) = mod(bin - 1, n_x) + 1
+      ijk(2) = mod(bin - 1, n_x*n_y)/n_x + 1
+      ijk(3) = (bin - 1)/(n_x*n_y) + 1
     end if
 
   end subroutine bin_to_mesh_indices

src/nuclide_header.F90

@@ -10,7 +10,7 @@ module nuclide_header
   use constants
   use dict_header, only: DictIntInt
   use endf,        only: reaction_name, is_fission, is_disappearance
-  use endf_header, only: Function1D, Constant1D, Polynomial, Tabulated1D
+  use endf_header, only: Function1D, Polynomial, Tabulated1D
   use error,       only: fatal_error, warning
   use hdf5_interface, only: read_attribute, open_group, close_group, &
        open_dataset, read_dataset, close_dataset, get_shape
@@ -88,6 +88,10 @@ module nuclide_header
     type(DictIntInt) :: reaction_index ! map MT values to index in reactions
                                        ! array; used at tally-time
 
+    ! Fission energy release
+    class(Function1D), allocatable :: fission_q_prompt ! prompt neutrons, gammas
+    class(Function1D), allocatable :: fission_q_recov  ! neutrons, gammas, betas
+
   contains
     procedure :: clear => nuclide_clear
     procedure :: print => nuclide_print
@@ -192,6 +196,8 @@ module nuclide_header
     integer(HID_T) :: rxs_group
     integer(HID_T) :: rx_group
     integer(HID_T) :: total_nu
+    integer(HID_T) :: fer_group                 ! fission_energy_release group
+    integer(HID_T) :: fer_dset
     integer(SIZE_T) :: name_len, name_file_len
     integer(HSIZE_T) :: j
     integer(HSIZE_T) :: dims(1)
@@ -251,8 +257,8 @@ module nuclide_header
       call this % urr_data % from_hdf5(urr_group)
 
       ! if the inelastic competition flag indicates that the inelastic cross
-      ! section should be determined from a normal reaction cross section, we need
-      ! to get the index of the reaction
+      ! section should be determined from a normal reaction cross section, we
+      ! need to get the index of the reaction
       if (this % urr_data % inelastic_flag > 0) then
         do i = 1, size(this % reactions)
           if (this % reactions(i) % MT == this % urr_data % inelastic_flag) then
@@ -283,11 +289,9 @@ module nuclide_header
       total_nu = open_dataset(nu_group, 'yield')
       call read_attribute(temp, total_nu, 'type')
       select case (temp)
-      case ('constant')
-        allocate(Constant1D :: this % total_nu)
-      case ('tabulated')
+      case ('Tabulated1D')
         allocate(Tabulated1D :: this % total_nu)
-      case ('polynomial')
+      case ('Polynomial')
         allocate(Polynomial :: this % total_nu)
       end select
       call this % total_nu % from_hdf5(total_nu)
@@ -296,6 +300,43 @@ module nuclide_header
       call close_group(nu_group)
     end if
 
+    ! Read fission energy release data if present
+    call h5ltpath_valid_f(group_id, 'fission_energy_release', .true., exists, &
+                          hdf5_err)
+    if (exists) then
+      fer_group = open_group(group_id, 'fission_energy_release')
+
+      ! Check to see if this is polynomial or tabulated data
+      fer_dset = open_dataset(fer_group, 'q_prompt')
+      call read_attribute(temp, fer_dset, 'type')
+      if (temp == 'Polynomial') then
+        ! Read the prompt Q-value
+        allocate(Polynomial :: this % fission_q_prompt)
+        call this % fission_q_prompt % from_hdf5(fer_dset)
+        call close_dataset(fer_dset)
+
+        ! Read the recoverable energy Q-value
+        allocate(Polynomial :: this % fission_q_recov)
+        fer_dset = open_dataset(fer_group, 'q_recoverable')
+        call this % fission_q_recov % from_hdf5(fer_dset)
+        call close_dataset(fer_dset)
+      else if (temp == 'Tabulated1D') then
+        ! Read the prompt Q-value
+        allocate(Tabulated1D :: this % fission_q_prompt)
+        call this % fission_q_prompt % from_hdf5(fer_dset)
+        call close_dataset(fer_dset)
+
+        ! Read the recoverable energy Q-value
+        allocate(Tabulated1D :: this % fission_q_recov)
+        fer_dset = open_dataset(fer_group, 'q_recoverable')
+        call this % fission_q_recov % from_hdf5(fer_dset)
+        call close_dataset(fer_dset)
+      else
+        call fatal_error('Unrecognized fission energy release format.')
+      end if
+      call close_group(fer_group)
+    end if
+
     ! Create derived cross section data
     call this % create_derived()
 

src/output.F90

@@ -776,6 +776,8 @@ contains
     score_names(abs(SCORE_DELAYED_NU_FISSION)) = "Delayed-Nu-Fission Rate"
     score_names(abs(SCORE_PROMPT_NU_FISSION))  = "Prompt-Nu-Fission Rate"
     score_names(abs(SCORE_INVERSE_VELOCITY))   = "Flux-Weighted Inverse Velocity"
+    score_names(abs(SCORE_FISS_Q_PROMPT))      = "Prompt fission power"
+    score_names(abs(SCORE_FISS_Q_RECOV))       = "Recoverable fission power"
 
     ! Create filename for tally output
     filename = trim(path_output) // "tallies.out"
@@ -1034,8 +1036,8 @@ contains
 
             ! Left Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i-1, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_LEFT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1043,25 +1045,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_RIGHT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Left", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Right Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Right", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_RIGHT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
@@ -1072,8 +1058,8 @@ contains
 
             ! Back Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j-1, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_BACK
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1081,25 +1067,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_FRONT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Back", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Front Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Front", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_FRONT
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
@@ -1110,8 +1080,8 @@ contains
 
             ! Bottom Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k-1 /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+            matching_bins(i_filter_surf) = OUT_BOTTOM
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1
             write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
@@ -1119,25 +1089,9 @@ contains
                  to_str(t % results(1,filter_index) % sum), &
                  trim(to_str(t % results(1,filter_index) % sum_sq))
 
-            matching_bins(i_filter_surf) = OUT_TOP
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Bottom", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
             ! Top Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
-                 * t % stride) + 1
-            write(UNIT=unit_tally, FMT='(5X,A,T35,A,"+/- ",A)') &
-                 "Incoming Current from Top", &
-                 to_str(t % results(1,filter_index) % sum), &
-                 trim(to_str(t % results(1,filter_index) % sum_sq))
-
+                 mesh_indices_to_bin(m, (/ i, j, k /))
             matching_bins(i_filter_surf) = OUT_TOP
             filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                  * t % stride) + 1

src/product_header.F90

@@ -5,7 +5,7 @@ module product_header
   use angleenergy_header, only: AngleEnergyContainer
   use constants, only: ZERO, MAX_WORD_LEN, EMISSION_PROMPT, EMISSION_DELAYED, &
        EMISSION_TOTAL, NEUTRON, PHOTON
-  use endf_header, only: Tabulated1D, Function1D, Constant1D, Polynomial
+  use endf_header, only: Tabulated1D, Function1D, Polynomial
   use hdf5_interface, only: read_attribute, open_group, close_group, &
        open_dataset, close_dataset, read_dataset
   use random_lcg, only: prn
@@ -109,11 +109,9 @@ contains
     yield = open_dataset(group_id, 'yield')
     call read_attribute(temp, yield, 'type')
     select case (temp)
-    case ('constant')
-      allocate(Constant1D :: this % yield)
-    case ('tabulated')
+    case ('Tabulated1D')
       allocate(Tabulated1D :: this % yield)
-    case ('polynomial')
+    case ('Polynomial')
       allocate(Polynomial :: this % yield)
     end select
     call this % yield % from_hdf5(yield)

src/state_point.F90

@@ -51,7 +51,7 @@ contains
     integer(HID_T) :: file_id
     integer(HID_T) :: cmfd_group, tallies_group, tally_group, meshes_group, &
                       mesh_group, filter_group, runtime_group
-    character(20), allocatable :: str_array(:)
+    character(MAX_WORD_LEN), allocatable :: str_array(:)
     character(MAX_FILE_LEN)    :: filename
     type(RegularMesh), pointer :: meshp
     type(TallyObject), pointer    :: tally

src/tally.F90

@@ -1,7 +1,6 @@
 module tally
 
   use constants
-  use endf_header,      only: Constant1D
   use error,            only: fatal_error
   use geometry_header
   use global
@@ -247,24 +246,17 @@ contains
         ! reaction with neutrons in the exit channel
         if (p % event_MT == ELASTIC .or. p % event_MT == N_LEVEL .or. &
              (p % event_MT >= N_N1 .and. p % event_MT <= N_NC)) then
-          ! Don't waste time on very common reactions we know have multiplicities
-          ! of one.
+          ! Don't waste time on very common reactions we know have
+          ! multiplicities of one.
           score = p % last_wgt * flux
         else
-          m = nuclides(p%event_nuclide)%reaction_index% &
+          m = nuclides(p % event_nuclide) % reaction_index % &
                get_key(p % event_MT)
 
           ! Get yield and apply to score
-          associate (rxn => nuclides(p%event_nuclide)%reactions(m))
-            select type (yield => rxn % products(1) % yield)
-            type is (Constant1D)
-              ! Grab the yield from the reaction
-              score = p % last_wgt * yield % y * flux
-            class default
-              ! the yield was already incorporated in to p % wgt per the
-              ! scattering routine
-              score = p % wgt * flux
-            end select
+          associate (rxn => nuclides(p % event_nuclide) % reactions(m))
+            score = p % last_wgt * flux &
+                 * rxn % products(1) % yield % evaluate(p % last_E)
           end associate
         end if
 
@@ -289,16 +281,9 @@ contains
                get_key(p % event_MT)
 
           ! Get yield and apply to score
-          associate (rxn => nuclides(p%event_nuclide)%reactions(m))
-            select type (yield => rxn % products(1) % yield)
-            type is (Constant1D)
-              ! Grab the yield from the reaction
-              score = p % last_wgt * yield % y * flux
-            class default
-              ! the yield was already incorporated in to p % wgt per the
-              ! scattering routine
-              score = p % wgt * flux
-            end select
+          associate (rxn => nuclides(p % event_nuclide) % reactions(m))
+            score = p % last_wgt * flux &
+                 * rxn % products(1) % yield % evaluate(p % last_E)
           end associate
         end if
 
@@ -324,15 +309,8 @@ contains
 
           ! Get yield and apply to score
           associate (rxn => nuclides(p%event_nuclide)%reactions(m))
-            select type (yield => rxn % products(1) % yield)
-            type is (Constant1D)
-              ! Grab the yield from the reaction
-              score = p % last_wgt * yield % y * flux
-            class default
-              ! the yield was already incorporated in to p % wgt per the
-              ! scattering routine
-              score = p % wgt * flux
-            end select
+            score = p % last_wgt * flux &
+                 * rxn % products(1) % yield % evaluate(p % last_E)
           end associate
         end if
 
@@ -703,14 +681,14 @@ contains
           if (survival_biasing) then
             ! No fission events occur if survival biasing is on -- need to
             ! calculate fraction of absorptions that would have resulted in
-            ! fission scale by kappa-fission
-            associate (nuc => nuclides(p%event_nuclide))
-              if (micro_xs(p%event_nuclide)%absorption > ZERO .and. &
-                   nuc%fissionable) then
-                score = p%absorb_wgt * &
-                     nuc%reactions(nuc%index_fission(1))%Q_value * &
-                     micro_xs(p%event_nuclide)%fission / &
-                     micro_xs(p%event_nuclide)%absorption * flux
+            ! fission scaled by kappa-fission
+            associate (nuc => nuclides(p % event_nuclide))
+              if (micro_xs(p % event_nuclide) % absorption > ZERO .and. &
+                   nuc % fissionable) then
+                score = p % absorb_wgt * &
+                     nuc % reactions(nuc % index_fission(1)) % Q_value * &
+                     micro_xs(p % event_nuclide) % fission / &
+                     micro_xs(p % event_nuclide) % absorption * flux
               end if
             end associate
           else
@@ -719,12 +697,12 @@ contains
             ! All fission events will contribute, so again we can use
             ! particle's weight entering the collision as the estimate for
             ! the fission energy production rate
-            associate (nuc => nuclides(p%event_nuclide))
-              if (nuc%fissionable) then
-                score = p%last_wgt * &
-                     nuc%reactions(nuc%index_fission(1))%Q_value * &
-                     micro_xs(p%event_nuclide)%fission / &
-                     micro_xs(p%event_nuclide)%absorption * flux
+            associate (nuc => nuclides(p % event_nuclide))
+              if (nuc % fissionable) then
+                score = p % last_wgt * &
+                     nuc % reactions(nuc % index_fission(1)) % Q_value * &
+                     micro_xs(p % event_nuclide) % fission / &
+                     micro_xs(p % event_nuclide) % absorption * flux
               end if
             end associate
           end if
@@ -732,22 +710,23 @@ contains
         else
           if (i_nuclide > 0) then
             associate (nuc => nuclides(i_nuclide))
-              if (nuc%fissionable) then
-                score = nuc%reactions(nuc%index_fission(1))%Q_value * &
-                     micro_xs(i_nuclide)%fission * atom_density * flux
+              if (nuc % fissionable) then
+                score = nuc % reactions(nuc % index_fission(1)) % Q_value * &
+                     micro_xs(i_nuclide) % fission * atom_density * flux
               end if
             end associate
           else
-            do l = 1, materials(p%material)%n_nuclides
+            do l = 1, materials(p % material) % n_nuclides
               ! Determine atom density and index of nuclide
-              atom_density_ = materials(p%material)%atom_density(l)
-              i_nuc = materials(p%material)%nuclide(l)
+              atom_density_ = materials(p % material) % atom_density(l)
+              i_nuc = materials(p % material) % nuclide(l)
 
               ! If nuclide is fissionable, accumulate kappa fission
               associate(nuc => nuclides(i_nuc))
                 if (nuc % fissionable) then
-                  score = score + nuc%reactions(nuc%index_fission(1))%Q_value * &
-                       micro_xs(i_nuc)%fission * atom_density_ * flux
+                  score = score + &
+                       nuc % reactions(nuc % index_fission(1)) % Q_value * &
+                       micro_xs(i_nuc) % fission * atom_density_ * flux
                 end if
               end associate
             end do
@@ -772,6 +751,123 @@ contains
           end if
         end if
 
+      case (SCORE_FISS_Q_PROMPT)
+        if (t % estimator == ESTIMATOR_ANALOG) then
+          if (survival_biasing) then
+            ! No fission events occur if survival biasing is on -- need to
+            ! calculate fraction of absorptions that would have resulted in
+            ! fission scaled by Q-value
+            associate (nuc => nuclides(p % event_nuclide))
+              if (micro_xs(p % event_nuclide) % absorption > ZERO .and. &
+                   allocated(nuc % fission_q_prompt)) then
+                score = p % absorb_wgt &
+                     * nuc % fission_q_prompt % evaluate(p % last_E) &
+                     * micro_xs(p % event_nuclide) % fission &
+                     / micro_xs(p % event_nuclide) % absorption * flux
+              end if
+            end associate
+          else
+            ! Skip any non-absorption events
+            if (p % event == EVENT_SCATTER) cycle SCORE_LOOP
+            ! All fission events will contribute, so again we can use
+            ! particle's weight entering the collision as the estimate for
+            ! the fission energy production rate
+            associate (nuc => nuclides(p % event_nuclide))
+              if (allocated(nuc % fission_q_prompt)) then
+                score = p % last_wgt &
+                     * nuc % fission_q_prompt % evaluate(p % last_E) &
+                     * micro_xs(p % event_nuclide) % fission &
+                     / micro_xs(p % event_nuclide) % absorption * flux
+              end if
+            end associate
+          end if
+
+        else
+          if (t % estimator == ESTIMATOR_COLLISION) then
+            E = p % last_E
+          else
+            E = p % E
+          end if
+
+          if (i_nuclide > 0) then
+            if (allocated(nuclides(i_nuclide) % fission_q_prompt)) then
+              score = micro_xs(i_nuclide) % fission * atom_density * flux &
+                      * nuclides(i_nuclide) % fission_q_prompt % evaluate(E)
+            else
+              score = ZERO
+            end if
+          else
+            score = ZERO
+            do l = 1, materials(p % material) % n_nuclides
+              atom_density_ = materials(p % material) % atom_density(l)
+              i_nuc = materials(p % material) % nuclide(l)
+              if (allocated(nuclides(i_nuc) % fission_q_prompt)) then
+                score = score + micro_xs(i_nuc) % fission * atom_density_ &
+                        * flux &
+                        * nuclides(i_nuc) % fission_q_prompt % evaluate(E)
+              end if
+            end do
+          end if
+        end if
+
+      case (SCORE_FISS_Q_RECOV)
+        if (t % estimator == ESTIMATOR_ANALOG) then
+          if (survival_biasing) then
+            ! No fission events occur if survival biasing is on -- need to
+            ! calculate fraction of absorptions that would have resulted in
+            ! fission scaled by Q-value
+            associate (nuc => nuclides(p % event_nuclide))
+              if (micro_xs(p % event_nuclide) % absorption > ZERO .and. &
+                   allocated(nuc % fission_q_recov)) then
+                score = p % absorb_wgt &
+                     * nuc % fission_q_recov % evaluate(p % last_E) &
+                     * micro_xs(p % event_nuclide) % fission &
+                     / micro_xs(p % event_nuclide) % absorption * flux
+              end if
+            end associate
+          else
+            ! Skip any non-absorption events
+            if (p % event == EVENT_SCATTER) cycle SCORE_LOOP
+            ! All fission events will contribute, so again we can use
+            ! particle's weight entering the collision as the estimate for
+            ! the fission energy production rate
+            associate (nuc => nuclides(p % event_nuclide))
+              if (allocated(nuc % fission_q_recov)) then
+                score = p % last_wgt &
+                     * nuc % fission_q_recov % evaluate(p % last_E) &
+                     * micro_xs(p % event_nuclide) % fission &
+                     / micro_xs(p % event_nuclide) % absorption * flux
+              end if
+            end associate
+          end if
+
+        else
+          if (t % estimator == ESTIMATOR_COLLISION) then
+            E = p % last_E
+          else
+            E = p % E
+          end if
+
+          if (i_nuclide > 0) then
+            if (allocated(nuclides(i_nuclide) % fission_q_recov)) then
+              score = micro_xs(i_nuclide) % fission * atom_density * flux &
+                      * nuclides(i_nuclide) % fission_q_recov % evaluate(E)
+            else
+              score = ZERO
+            end if
+          else
+            score = ZERO
+            do l = 1, materials(p % material) % n_nuclides
+              atom_density_ = materials(p % material) % atom_density(l)
+              i_nuc = materials(p % material) % nuclide(l)
+              if (allocated(nuclides(i_nuc) % fission_q_recov)) then
+                score = score + micro_xs(i_nuc) % fission * atom_density_ &
+                        * flux * nuclides(i_nuc) % fission_q_recov % evaluate(E)
+              end if
+            end do
+          end if
+        end if
+
       case default
         if (t % estimator == ESTIMATOR_ANALOG) then
           ! Any other score is assumed to be a MT number. Thus, we just need
@@ -2231,6 +2327,7 @@ contains
     integer :: filter_index         ! index of scoring bin
     integer :: i_filter_mesh        ! index of mesh filter in filters array
     integer :: i_filter_surf        ! index of surface filter in filters
+    integer :: i_filter_energy      ! index of energy filter in filters
     real(8) :: uvw(3)               ! cosine of angle of particle
     real(8) :: xyz0(3)              ! starting/intermediate coordinates
     real(8) :: xyz1(3)              ! ending coordinates of particle
@@ -2255,9 +2352,10 @@ contains
       i_tally = active_current_tallies % get_item(i)
       t => tallies(i_tally)
 
-      ! Get index for mesh and surface filters
+      ! Get index for mesh, surface, and energy filters
       i_filter_mesh = t % find_filter(FILTER_MESH)
       i_filter_surf = t % find_filter(FILTER_SURFACE)
+      i_filter_energy = t % find_filter(FILTER_ENERGYIN)
 
       ! Get pointer to mesh
       select type(filt => t % filters(i_filter_mesh) % obj)
@@ -2290,11 +2388,11 @@ contains
 
       ! Determine incoming energy bin.  We need to tell the energy filter this
       ! is a tracklength tally so it uses the pre-collision energy.
-      j = t % find_filter(FILTER_ENERGYIN)
-      if (j > 0) then
-        call t % filters(i) % obj % get_next_bin(p, ESTIMATOR_TRACKLENGTH, &
-             & NO_BIN_FOUND, matching_bins(j), filt_score)
-        if (matching_bins(j) == NO_BIN_FOUND) cycle
+      if (i_filter_energy > 0) then
+        call t % filters(i_filter_energy) % obj % get_next_bin(p, &
+             ESTIMATOR_TRACKLENGTH, NO_BIN_FOUND, &
+             matching_bins(i_filter_energy), filt_score)
+        if (matching_bins(i_filter_energy) == NO_BIN_FOUND) cycle
       end if
 
       ! =======================================================================
@@ -2309,10 +2407,10 @@ contains
         if (uvw(3) > 0) then
           do j = ijk0(3), ijk1(3) - 1
             ijk0(3) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_TOP
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2321,12 +2419,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(3) - 1, ijk1(3), -1
+          do j = ijk0(3), ijk1(3) + 1, -1
             ijk0(3) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_TOP
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BOTTOM
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2341,10 +2439,10 @@ contains
         if (uvw(2) > 0) then
           do j = ijk0(2), ijk1(2) - 1
             ijk0(2) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_FRONT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2353,12 +2451,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(2) - 1, ijk1(2), -1
+          do j = ijk0(2), ijk1(2) + 1, -1
             ijk0(2) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_FRONT
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BACK
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2373,10 +2471,10 @@ contains
         if (uvw(1) > 0) then
           do j = ijk0(1), ijk1(1) - 1
             ijk0(1) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_RIGHT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2385,12 +2483,12 @@ contains
             end if
           end do
         else
-          do j = ijk0(1) - 1, ijk1(1), -1
+          do j = ijk0(1), ijk1(1) + 1, -1
             ijk0(1) = j
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_RIGHT
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_LEFT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
               filter_index = sum((matching_bins(1:size(t % filters)) - 1) &
                    * t % stride) + 1
 !$omp atomic
@@ -2442,67 +2540,67 @@ contains
           if (uvw(1) > 0) then
             ! Crossing into right mesh cell -- this is treated as outgoing
             ! current from (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_RIGHT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(1) = ijk0(1) + 1
             xyz_cross(1) = xyz_cross(1) + m % width(1)
           else
-            ! Crossing into left mesh cell -- this is treated as incoming
-            ! current in (i-1,j,k)
+            ! Crossing into left mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_LEFT
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(1) = ijk0(1) - 1
             xyz_cross(1) = xyz_cross(1) - m % width(1)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_RIGHT
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         elseif (distance == d(2)) then
           if (uvw(2) > 0) then
             ! Crossing into front mesh cell -- this is treated as outgoing
             ! current in (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_FRONT
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(2) = ijk0(2) + 1
             xyz_cross(2) = xyz_cross(2) + m % width(2)
           else
-            ! Crossing into back mesh cell -- this is treated as incoming
-            ! current in (i,j-1,k)
+            ! Crossing into back mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BACK
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(2) = ijk0(2) - 1
             xyz_cross(2) = xyz_cross(2) - m % width(2)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_FRONT
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         else if (distance == d(3)) then
           if (uvw(3) > 0) then
             ! Crossing into top mesh cell -- this is treated as outgoing
             ! current in (i,j,k)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
               matching_bins(i_filter_surf) = OUT_TOP
               matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
+                   mesh_indices_to_bin(m, ijk0)
             end if
             ijk0(3) = ijk0(3) + 1
             xyz_cross(3) = xyz_cross(3) + m % width(3)
           else
-            ! Crossing into bottom mesh cell -- this is treated as incoming
-            ! current in (i,j,k-1)
+            ! Crossing into bottom mesh cell -- this is treated as outgoing
+            ! current in (i,j,k)
+            if (all(ijk0 >= 1) .and. all(ijk0 <= m % dimension)) then
+              matching_bins(i_filter_surf) = OUT_BOTTOM
+              matching_bins(i_filter_mesh) = &
+                   mesh_indices_to_bin(m, ijk0)
+            end if
             ijk0(3) = ijk0(3) - 1
             xyz_cross(3) = xyz_cross(3) - m % width(3)
-            if (all(ijk0 >= 0) .and. all(ijk0 <= m % dimension)) then
-              matching_bins(i_filter_surf) = IN_TOP
-              matching_bins(i_filter_mesh) = &
-                   mesh_indices_to_bin(m, ijk0 + 1, .true.)
-            end if
           end if
         end if
 

src/tally_filter.F90

@@ -295,8 +295,12 @@ contains
           search_iter = 0
           do while (any(ijk0(:m % n_dimension) < 1) &
                .or. any(ijk0(:m % n_dimension) > m % dimension))
-            if (search_iter == MAX_SEARCH_ITER) call fatal_error("Failed to &
-                 &find a mesh intersection on a tally mesh filter.")
+            if (search_iter == MAX_SEARCH_ITER) then
+              call warning("Failed to find a mesh intersection on a tally mesh &
+                   &filter.")
+              next_bin = NO_BIN_FOUND
+              return
+            end if
 
             do j = 1, m % n_dimension
               if (abs(uvw(j)) < FP_PRECISION) then
@@ -315,6 +319,8 @@ contains
             else
               ijk0(j) = ijk0(j) - 1
             end if
+
+            search_iter = search_iter + 1
           end do
           distance = d(j)
           xyz0 = xyz0 + distance * uvw

src/trigger.F90

@@ -328,10 +328,11 @@ contains
               matching_bins(i_filter_ein) = l
             end if
 
-            ! Left Surface
             matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i-1, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
+                 mesh_indices_to_bin(m, (/ i, j, k /))
+
+            ! Left Surface
+            matching_bins(i_filter_surf) = OUT_LEFT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -343,33 +344,7 @@ contains
             end if
             trigger % variance = std_dev**2
 
-            matching_bins(i_filter_surf) = OUT_RIGHT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             ! Right Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_RIGHT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_RIGHT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
@@ -383,22 +358,7 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Back Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j-1, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
-
-            matching_bins(i_filter_surf) = OUT_FRONT
+            matching_bins(i_filter_surf) = OUT_BACK
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -411,20 +371,6 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Front Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_FRONT
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_FRONT
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
@@ -438,21 +384,7 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Bottom Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k-1 /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
-            matching_bins(i_filter_surf) = OUT_TOP
+            matching_bins(i_filter_surf) = OUT_BOTTOM
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
             call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
@@ -465,20 +397,6 @@ contains
             trigger % variance = trigger % std_dev**2
 
             ! Top Surface
-            matching_bins(i_filter_mesh) = &
-                 mesh_indices_to_bin(m, (/ i, j, k /) + 1, .true.)
-            matching_bins(i_filter_surf) = IN_TOP
-            filter_index = &
-                 sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1
-            call get_trigger_uncertainty(std_dev, rel_err, 1, filter_index, t)
-            if (trigger % std_dev < std_dev) then
-              trigger % std_dev = std_dev
-            end if
-            if (trigger % rel_err < rel_err) then
-              trigger % rel_err = rel_err
-            end if
-            trigger % variance = trigger % std_dev**2
-
             matching_bins(i_filter_surf) = OUT_TOP
             filter_index = &
                  sum((matching_bins(1:size(t % filters)) - 1) * t % stride) + 1

tests/input_set.py

@@ -2,6 +2,7 @@ import openmc
 from openmc.source import Source
 from openmc.stats import Box
 
+import numpy as np
 
 class InputSet(object):
     def __init__(self):
@@ -673,6 +674,158 @@ class PinCellInputSet(object):
         self.plots.add_plot(plot)
 
 
+class AssemblyInputSet(object):
+    def __init__(self):
+        self.settings = openmc.Settings()
+        self.materials = openmc.Materials()
+        self.geometry = openmc.Geometry()
+        self.tallies = None
+        self.plots = None
+
+    def export(self):
+        self.settings.export_to_xml()
+        self.materials.export_to_xml()
+        self.geometry.export_to_xml()
+        if self.tallies is not None:
+            self.tallies.export_to_xml()
+        if self.plots is not None:
+            self.plots.export_to_xml()
+
+    def build_default_materials_and_geometry(self):
+        # Define materials.
+        fuel = openmc.Material(name='Fuel')
+        fuel.set_density('g/cm3', 10.29769)
+        fuel.add_nuclide("U234", 4.4843e-6)
+        fuel.add_nuclide("U235", 5.5815e-4)
+        fuel.add_nuclide("U238", 2.2408e-2)
+        fuel.add_nuclide("O16", 4.5829e-2)
+
+        clad = openmc.Material(name='Cladding')
+        clad.set_density('g/cm3', 6.55)
+        clad.add_nuclide("Zr90", 2.1827e-2)
+        clad.add_nuclide("Zr91", 4.7600e-3)
+        clad.add_nuclide("Zr92", 7.2758e-3)
+        clad.add_nuclide("Zr94", 7.3734e-3)
+        clad.add_nuclide("Zr96", 1.1879e-3)
+
+        hot_water = openmc.Material(name='Hot borated water')
+        hot_water.set_density('g/cm3', 0.740582)
+        hot_water.add_nuclide("H1", 4.9457e-2)
+        hot_water.add_nuclide("O16", 2.4672e-2)
+        hot_water.add_nuclide("B10", 8.0042e-6)
+        hot_water.add_nuclide("B11", 3.2218e-5)
+        hot_water.add_s_alpha_beta('c_H_in_H2O', '71t')
+
+        # Define the materials file.
+        self.materials.default_xs = '71c'
+        self.materials += (fuel, clad, hot_water)
+
+        # Instantiate ZCylinder surfaces
+        fuel_or = openmc.ZCylinder(x0=0, y0=0, R=0.39218, name='Fuel OR')
+        clad_or = openmc.ZCylinder(x0=0, y0=0, R=0.45720, name='Clad OR')
+
+        # Create boundary planes to surround the geometry
+        min_x = openmc.XPlane(x0=-10.71, boundary_type='reflective')
+        max_x = openmc.XPlane(x0=+10.71, boundary_type='reflective')
+        min_y = openmc.YPlane(y0=-10.71, boundary_type='reflective')
+        max_y = openmc.YPlane(y0=+10.71, boundary_type='reflective')
+
+        # Create a Universe to encapsulate a fuel pin
+        fuel_pin_universe = openmc.Universe(name='Fuel Pin')
+
+        # Create fuel Cell
+        fuel_cell = openmc.Cell(name='fuel')
+        fuel_cell.fill = fuel
+        fuel_cell.region = -fuel_or
+        fuel_pin_universe.add_cell(fuel_cell)
+
+        # Create a clad Cell
+        clad_cell = openmc.Cell(name='clad')
+        clad_cell.fill = clad
+        clad_cell.region = +fuel_or & -clad_or
+        fuel_pin_universe.add_cell(clad_cell)
+
+        # Create a moderator Cell
+        hot_water_cell = openmc.Cell(name='hot water')
+        hot_water_cell.fill = hot_water
+        hot_water_cell.region = +clad_or
+        fuel_pin_universe.add_cell(hot_water_cell)
+
+        # Create a Universe to encapsulate a control rod guide tube
+        guide_tube_universe = openmc.Universe(name='Guide Tube')
+
+        # Create guide tube inner Cell
+        gt_inner_cell = openmc.Cell(name='guide tube inner water')
+        gt_inner_cell.fill = hot_water
+        gt_inner_cell.region = -fuel_or
+        guide_tube_universe.add_cell(gt_inner_cell)
+
+        # Create a clad Cell
+        gt_clad_cell = openmc.Cell(name='guide tube clad')
+        gt_clad_cell.fill = clad
+        gt_clad_cell.region = +fuel_or & -clad_or
+        guide_tube_universe.add_cell(gt_clad_cell)
+
+        # Create a guide tube outer Cell
+        gt_outer_cell = openmc.Cell(name='guide tube outer water')
+        gt_outer_cell.fill = hot_water
+        gt_outer_cell.region = +clad_or
+        guide_tube_universe.add_cell(gt_outer_cell)
+
+        # Create fuel assembly Lattice
+        assembly = openmc.RectLattice(name='Fuel Assembly')
+        assembly.pitch = (1.26, 1.26)
+        assembly.lower_left = [-1.26 * 17. / 2.0] * 2
+
+        # Create array indices for guide tube locations in lattice
+        template_x = np.array([5, 8, 11, 3, 13, 2, 5, 8, 11, 14, 2, 5, 8,
+                               11, 14, 2, 5, 8, 11, 14, 3, 13, 5, 8, 11])
+        template_y = np.array([2, 2, 2, 3, 3, 5, 5, 5, 5, 5, 8, 8, 8, 8,
+                               8, 11, 11, 11, 11, 11, 13, 13, 14, 14, 14])
+
+        # Initialize an empty 17x17 array of the lattice universes
+        universes = np.empty((17, 17), dtype=openmc.Universe)
+
+        # Fill the array with the fuel pin and guide tube universes
+        universes[:,:] = fuel_pin_universe
+        universes[template_x, template_y] = guide_tube_universe
+
+        # Store the array of universes in the lattice
+        assembly.universes = universes
+
+        # Create root Cell
+        root_cell = openmc.Cell(name='root cell')
+        root_cell.fill = assembly
+
+        # Add boundary planes
+        root_cell.region = +min_x & -max_x & +min_y & -max_y
+
+        # Create root Universe
+        root_universe = openmc.Universe(universe_id=0, name='root universe')
+        root_universe.add_cell(root_cell)
+
+        # Instantiate a Geometry, register the root Universe, and export to XML
+        self.geometry.root_universe = root_universe
+
+    def build_default_settings(self):
+        self.settings.batches = 10
+        self.settings.inactive = 5
+        self.settings.particles = 100
+        self.settings.source = Source(space=Box([-10.71, -10.71, -1],
+                                                [10.71, 10.71, 1],
+                                                only_fissionable=True))
+
+    def build_defualt_plots(self):
+        plot = openmc.Plot()
+        plot.filename = 'mat'
+        plot.origin = (0.0, 0.0, 0)
+        plot.width = (21.42, 21.42)
+        plot.pixels = (300, 300)
+        plot.color = 'mat'
+
+        self.plots.add_plot(plot)
+
+
 class MGInputSet(InputSet):
     def build_default_materials_and_geometry(self):
         # Define materials needed for 1D/1G slab problem

tests/test_cmfd_feed/results_true.dat

@@ -124,92 +124,8 @@ tally 3:
 1.020705E+00
 5.413570E-02
 tally 4:
-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
-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
-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
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
 3.049469E+00
 4.677325E-01
-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
-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
-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
-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
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-5.514939E+00
-1.528899E+00
 2.770358E+00
 3.879191E-01
 0.000000E+00
@@ -220,44 +136,8 @@ tally 4:
 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
-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
-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
-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
-7.294002E+00
-2.675589E+00
+5.514939E+00
+1.528899E+00
 5.032131E+00
 1.275040E+00
 0.000000E+00
@@ -268,44 +148,8 @@ tally 4:
 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
-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
-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
-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
-8.668860E+00
-3.776102E+00
+7.294002E+00
+2.675589E+00
 7.036008E+00
 2.490719E+00
 0.000000E+00
@@ -316,44 +160,8 @@ tally 4:
 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
-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
-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
-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
-9.345868E+00
-4.380719E+00
+8.668860E+00
+3.776102E+00
 8.352414E+00
 3.501945E+00
 0.000000E+00
@@ -364,44 +172,8 @@ tally 4:
 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
-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
-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
-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
-9.223771E+00
-4.270119E+00
+9.345868E+00
+4.380719E+00
 9.093766E+00
 4.158282E+00
 0.000000E+00
@@ -412,44 +184,8 @@ tally 4:
 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
-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
-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
-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
-8.530966E+00
-3.651778E+00
+9.223771E+00
+4.270119E+00
 9.219150E+00
 4.264346E+00
 0.000000E+00
@@ -460,44 +196,8 @@ tally 4:
 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
-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
-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
-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
-7.204424E+00
-2.604203E+00
+8.530966E+00
+3.651778E+00
 8.690373E+00
 3.785262E+00
 0.000000E+00
@@ -508,44 +208,8 @@ tally 4:
 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
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
-0.000000E+00
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@@ -556,44 +220,8 @@ tally 4:
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@@ -604,44 +232,8 @@ tally 4:
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@@ -652,6 +244,414 @@ tally 4:
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 cmfd indices
 1.000000E+01
 1.000000E+00

tests/test_cmfd_nofeed/results_true.dat

@@ -124,92 +124,8 @@ tally 3:
 9.213728E-01
 4.422001E-02
 tally 4:
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@@ -220,44 +136,8 @@ tally 4:
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@@ -268,44 +148,8 @@ tally 4:
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@@ -316,44 +160,8 @@ tally 4:
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@@ -364,44 +172,8 @@ tally 4:
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@@ -412,44 +184,8 @@ tally 4:
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@@ -460,44 +196,8 @@ tally 4:
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 1.000000E+01
 1.000000E+00

tests/test_filter_mesh_2d/results_true.dat

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 7.171591E-02
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@@ -525,24 +525,16 @@ tally 1:
 0.000000E+00
 0.000000E+00
 0.000000E+00
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 0.000000E+00
 0.000000E+00
 0.000000E+00
@@ -565,6 +557,14 @@ tally 1:
 0.000000E+00
 0.000000E+00
 0.000000E+00
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+3.405521E-03
 0.000000E+00
 0.000000E+00
 0.000000E+00

tests/test_mgxs_library_condense/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
+08c5f1c783dd88c5fed51c054718ca09fc4e99aa4560a6f928b3902991948f3a878d055ac46c07548904285c2c5f22dc2a3d8c1bb82b8e73d76dd790820117df

tests/test_mgxs_library_condense/results_true.dat

@@ -40,6 +40,27 @@
 0     10000         1   total  4.996730e-07  3.650635e-08
    material  group in nuclide      mean  std. dev.
 0     10000         1   total  0.090004   0.006367
+   material  delayedgroup  group in nuclide      mean  std. dev.
+0     10000             1         1   total  0.000021   0.000001
+1     10000             2         1   total  0.000110   0.000008
+2     10000             3         1   total  0.000107   0.000007
+3     10000             4         1   total  0.000249   0.000017
+4     10000             5         1   total  0.000112   0.000007
+5     10000             6         1   total  0.000046   0.000003
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10000             1          1   total   0.0   0.000000
+1     10000             2          1   total   1.0   0.869128
+2     10000             3          1   total   1.0   1.414214
+3     10000             4          1   total   1.0   0.360359
+4     10000             5          1   total   0.0   0.000000
+5     10000             6          1   total   0.0   0.000000
+   material  delayedgroup  group in nuclide      mean  std. dev.
+0     10000             1         1   total  0.000227   0.000020
+1     10000             2         1   total  0.001214   0.000108
+2     10000             3         1   total  0.001184   0.000104
+3     10000             4         1   total  0.002752   0.000240
+4     10000             5         1   total  0.001231   0.000105
+5     10000             6         1   total  0.000512   0.000044
    material  group in nuclide      mean  std. dev.
 0     10001         1   total  0.311594   0.013793
    material  group in nuclide      mean  std. dev.
@@ -82,6 +103,27 @@
 0     10001         1   total  5.454760e-07  4.949800e-08
    material  group in nuclide  mean  std. dev.
 0     10001         1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10001             1         1   total   0.0        0.0
+1     10001             2         1   total   0.0        0.0
+2     10001             3         1   total   0.0        0.0
+3     10001             4         1   total   0.0        0.0
+4     10001             5         1   total   0.0        0.0
+5     10001             6         1   total   0.0        0.0
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10001             1          1   total   0.0        0.0
+1     10001             2          1   total   0.0        0.0
+2     10001             3          1   total   0.0        0.0
+3     10001             4          1   total   0.0        0.0
+4     10001             5          1   total   0.0        0.0
+5     10001             6          1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10001             1         1   total   0.0        0.0
+1     10001             2         1   total   0.0        0.0
+2     10001             3         1   total   0.0        0.0
+3     10001             4         1   total   0.0        0.0
+4     10001             5         1   total   0.0        0.0
+5     10001             6         1   total   0.0        0.0
    material  group in nuclide      mean  std. dev.
 0     10002         1   total  0.904999   0.043964
    material  group in nuclide      mean  std. dev.
@@ -124,3 +166,24 @@
 0     10002         1   total  5.773006e-07  5.322132e-08
    material  group in nuclide  mean  std. dev.
 0     10002         1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10002             1         1   total   0.0        0.0
+1     10002             2         1   total   0.0        0.0
+2     10002             3         1   total   0.0        0.0
+3     10002             4         1   total   0.0        0.0
+4     10002             5         1   total   0.0        0.0
+5     10002             6         1   total   0.0        0.0
+   material  delayedgroup  group out nuclide  mean  std. dev.
+0     10002             1          1   total   0.0        0.0
+1     10002             2          1   total   0.0        0.0
+2     10002             3          1   total   0.0        0.0
+3     10002             4          1   total   0.0        0.0
+4     10002             5          1   total   0.0        0.0
+5     10002             6          1   total   0.0        0.0
+   material  delayedgroup  group in nuclide  mean  std. dev.
+0     10002             1         1   total   0.0        0.0
+1     10002             2         1   total   0.0        0.0
+2     10002             3         1   total   0.0        0.0
+3     10002             4         1   total   0.0        0.0
+4     10002             5         1   total   0.0        0.0
+5     10002             6         1   total   0.0        0.0

tests/test_mgxs_library_condense/test_mgxs_library_condense.py

@@ -23,12 +23,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_distribcell/inputs_true.dat

@@ -1 +1 @@
-2d948f3b12293294eaeca231a3df9d51195379e8bb38dd3e68d3bc512a7d08ed52a1109054ca381684ec127268710f6d6e9210ac8154c9b379608e996627624a
+9ce3d6987d67e92b0924916bb54288429d2bd6dfd12a69f86c5dbefb407f7eb72adb0e44d558c09e9a39610ffeb651aee4aedc629cf3a28a181d62ca4cfbcd5a

tests/test_mgxs_library_distribcell/results_true.dat

@@ -1,42 +1,63 @@
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.145934   0.553822
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.457353   0.010474
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.718919   0.520644
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.405649   0.015784
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.718919   0.520644
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.405641   0.015787
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.019762   0.010629
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.066556    0.00251
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.019762   0.010629
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.028979   0.002712
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.126172    0.54344
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.037577   0.001487
                                     avg(distribcell)  group in nuclide      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  1.142547   0.570131
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.092377   0.003628
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  7.276707   0.287579
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.390797   0.008717
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.387332   0.014241
                                     avg(distribcell)  group in  group out nuclide moment      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  1.142547   0.570131
-1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.447381   0.216322
-2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.141202   0.066504
-3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.039228   0.024621
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  0.387009   0.014230
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.047179   0.004923
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.015713   0.003654
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.005378   0.003137
                                     avg(distribcell)  group in  group out nuclide moment      mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  1.142547   0.570131
-1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.447381   0.216322
-2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.141202   0.066504
-3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.039228   0.024621
-                                    avg(distribcell)  group in  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total   1.0   0.529717
-                                    avg(distribcell)  group in  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P0  0.387332   0.014241
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P1  0.047187   0.004933
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P2  0.015727   0.003654
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total     P3  0.005387   0.003141
+                                    avg(distribcell)  group in  group out nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total  1.000834   0.037242
+                                    avg(distribcell)  group in  group out nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1          1   total  0.094516     0.0059
                                     avg(distribcell)  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   1.0   0.080455
                                     avg(distribcell)  group out nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   0.0        0.0
-                                    avg(distribcell)  group in nuclide      mean     std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.000001  6.946255e-07
-                                    avg(distribcell)  group in nuclide  mean  std. dev.
-0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total   0.0        0.0
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...          1   total   1.0   0.080541
+                                    avg(distribcell)  group in nuclide          mean     std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  5.139437e-07  2.133314e-08
+                                    avg(distribcell)  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...         1   total  0.091725   0.003604
+                                    avg(distribcell)  delayedgroup  group in nuclide      mean     std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1         1   total  0.000021  8.253907e-07
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2         1   total  0.000112  4.284000e-06
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3         1   total  0.000109  4.105197e-06
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4         1   total  0.000252  9.271420e-06
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5         1   total  0.000112  3.888625e-06
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6         1   total  0.000047  1.625563e-06
+                                    avg(distribcell)  delayedgroup  group out nuclide  mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1          1   total   0.0   0.000000
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2          1   total   1.0   1.414214
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3          1   total   1.0   1.414214
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4          1   total   0.0   0.000000
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5          1   total   0.0   0.000000
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6          1   total   1.0   1.414214
+                                    avg(distribcell)  delayedgroup  group in nuclide      mean  std. dev.
+0  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             1         1   total  0.000227   0.000012
+1  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             2         1   total  0.001209   0.000061
+2  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             3         1   total  0.001177   0.000059
+3  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             4         1   total  0.002727   0.000135
+4  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             5         1   total  0.001210   0.000058
+5  (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,...             6         1   total  0.000504   0.000024

tests/test_mgxs_library_distribcell/test_mgxs_library_distribcell.py

@@ -6,29 +6,39 @@ import glob
 import hashlib
 sys.path.insert(0, os.pardir)
 from testing_harness import PyAPITestHarness
+from input_set import AssemblyInputSet
 import openmc
 import openmc.mgxs
 
 
 class MGXSTestHarness(PyAPITestHarness):
     def _build_inputs(self):
+        # Set the input set to use the pincell model
+        self._input_set = AssemblyInputSet()
+
         # Generate inputs using parent class routine
         super(MGXSTestHarness, self)._build_inputs()
 
         # Initialize a one-group structure
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         # for one material-filled cell in the geometry
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'distribcell'
-        material_cells = self.mgxs_lib.openmc_geometry.get_all_material_cells()
-        self.mgxs_lib.domains = [material_cells[-1]]
+        cells = self.mgxs_lib.openmc_geometry.get_all_material_cells()
+        self.mgxs_lib.domains = [c for c in cells if c.name == 'fuel']
         self.mgxs_lib.build_library()
 
         # Initialize a tallies file

tests/test_mgxs_library_hdf5/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
+08c5f1c783dd88c5fed51c054718ca09fc4e99aa4560a6f928b3902991948f3a878d055ac46c07548904285c2c5f22dc2a3d8c1bb82b8e73d76dd790820117df

tests/test_mgxs_library_hdf5/results_true.dat

@@ -72,6 +72,45 @@ domain=10000 type=inverse-velocity
 domain=10000 type=prompt-nu-fission
 [ 0.01923922  0.46671903]
 [ 0.00130951  0.04141087]
+domain=10000 type=delayed-nu-fission
+[[  2.29808234e-05   1.06974158e-04]
+ [  1.43606337e-04   5.52167907e-04]
+ [  1.51382216e-04   5.27147681e-04]
+ [  7.42603178e-05   2.22018043e-04]
+ [  4.14908454e-05   9.10244403e-05]
+ [  1.70016000e-05   3.81298119e-05]]
+[[  1.66363133e-06   9.49156242e-06]
+ [  1.05907806e-05   4.89925426e-05]
+ [  1.12671238e-05   4.67725567e-05]
+ [  5.22610273e-06   1.87563195e-05]
+ [  2.99830766e-06   7.68984041e-06]
+ [  1.22654684e-06   3.22124663e-06]]
+domain=10000 type=chi-delayed
+[[ 0.  0.]
+ [ 1.  0.]
+ [ 1.  0.]
+ [ 1.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.          0.        ]
+ [ 0.86912776  0.        ]
+ [ 1.41421356  0.        ]
+ [ 0.36035904  0.        ]
+ [ 0.          0.        ]
+ [ 0.          0.        ]]
+domain=10000 type=beta
+[[  4.89188107e-05   2.27713711e-04]
+ [  3.05691886e-04   1.17538858e-03]
+ [  3.22244241e-04   1.12212853e-03]
+ [  3.82159891e-03   1.14255357e-02]
+ [  2.13520995e-03   4.68431744e-03]
+ [  8.74939644e-04   1.96224379e-03]]
+[[  4.67388620e-06   2.46946810e-05]
+ [  2.95223877e-05   1.27466393e-04]
+ [  3.12885004e-05   1.21690543e-04]
+ [  3.21434855e-04   1.09939816e-03]
+ [  1.82980497e-04   4.50738567e-04]
+ [  7.48899920e-05   1.88812772e-04]]
 domain=10001 type=total
 [ 0.31373767  0.3008214 ]
 [ 0.0155819   0.02805245]
@@ -146,6 +185,45 @@ domain=10001 type=inverse-velocity
 domain=10001 type=prompt-nu-fission
 [ 0.  0.]
 [ 0.  0.]
+domain=10001 type=delayed-nu-fission
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10001 type=chi-delayed
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10001 type=beta
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
 domain=10002 type=total
 [ 0.66457226  2.05238401]
 [ 0.03121475  0.22434291]
@@ -220,3 +298,42 @@ domain=10002 type=inverse-velocity
 domain=10002 type=prompt-nu-fission
 [ 0.  0.]
 [ 0.  0.]
+domain=10002 type=delayed-nu-fission
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10002 type=chi-delayed
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+domain=10002 type=beta
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]
+[[ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]
+ [ 0.  0.]]

tests/test_mgxs_library_hdf5/test_mgxs_library_hdf5.py

@@ -24,12 +24,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_mesh/inputs_true.dat

@@ -1 +1 @@
-a4cd030bea212e45fdb159e75a7fb3d1947e9bf3d0384ac5d37a72298d67dcfdd1b9eb5c6af8ac6e5983bd5b47de9c17a2ea472b467b7222a4909ee070bf1ca3
+5f167bdd4d6ae5873d48483e85aceaec8a934239ed5a50ef6f6500ce204f5851ae330621a5007f3b3d6bdab49f2cd627d011c1f6e6983fec958a6984eb9cb7ca

tests/test_mgxs_library_mesh/results_true.dat

@@ -1,62 +1,62 @@
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.640786  0.044177
-1      1  2  1        1   total  0.660597  0.128423
-2      2  1  1        1   total  0.615276  0.104046
+1      1  2  1        1   total  0.615276  0.104046
+2      2  1  1        1   total  0.660597  0.128423
 3      2  2  1        1   total  0.646999  0.186709
   mesh 1       group in nuclide     mean std. dev.
        x  y  z                                    
 0      1  1  1        1   total  0.36665  0.048814
-1      1  2  1        1   total  0.40784  0.096486
-2      2  1  1        1   total  0.36356  0.074111
+1      1  2  1        1   total  0.36356  0.074111
+2      2  1  1        1   total  0.40784  0.096486
 3      2  2  1        1   total  0.41456  0.160443
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.366650  0.048814
-1      1  2  1        1   total  0.407840  0.096486
-2      2  1  1        1   total  0.363560  0.074111
+1      1  2  1        1   total  0.363560  0.074111
+2      2  1  1        1   total  0.407840  0.096486
 3      2  2  1        1   total  0.414593  0.160436
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.025749  0.002863
-1      1  2  1        1   total  0.028400  0.005275
-2      2  1  1        1   total  0.022988  0.004099
+1      1  2  1        1   total  0.022988  0.004099
+2      2  1  1        1   total  0.028400  0.005275
 3      2  2  1        1   total  0.027589  0.010350
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.015861  0.002876
-1      1  2  1        1   total  0.017280  0.004371
-2      2  1  1        1   total  0.014403  0.003542
+1      1  2  1        1   total  0.014403  0.003542
+2      2  1  1        1   total  0.017280  0.004371
 3      2  2  1        1   total  0.018061  0.010110
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.009888  0.001077
-1      1  2  1        1   total  0.011121  0.002456
-2      2  1  1        1   total  0.008585  0.001552
+1      1  2  1        1   total  0.008585  0.001552
+2      2  1  1        1   total  0.011121  0.002456
 3      2  2  1        1   total  0.009527  0.003659
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.026065  0.002907
-1      1  2  1        1   total  0.029084  0.006430
-2      2  1  1        1   total  0.022596  0.004062
+1      1  2  1        1   total  0.022596  0.004062
+2      2  1  1        1   total  0.029084  0.006430
 3      2  2  1        1   total  0.025066  0.009687
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  1.938476  0.211550
-1      1  2  1        1   total  2.177360  0.480780
-2      2  1  1        1   total  1.682799  0.303764
+1      1  2  1        1   total  1.682799  0.303764
+2      2  1  1        1   total  2.177360  0.480780
 3      2  2  1        1   total  1.864890  0.715661
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.615037  0.041754
-1      1  2  1        1   total  0.632196  0.123878
-2      2  1  1        1   total  0.592288  0.100439
+1      1  2  1        1   total  0.592288  0.100439
+2      2  1  1        1   total  0.632196  0.123878
 3      2  2  1        1   total  0.619410  0.177190
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.584014  0.054315
-1      1  2  1        1   total  0.622514  0.111323
-2      2  1  1        1   total  0.587256  0.084833
+1      1  2  1        1   total  0.587256  0.084833
+2      2  1  1        1   total  0.622514  0.111323
 3      2  2  1        1   total  0.613792  0.168612
    mesh 1       group in group out nuclide moment      mean std. dev.
         x  y  z                                                      
@@ -64,14 +64,14 @@
 1       1  1  1        1         1   total     P1  0.243427  0.025488
 2       1  1  1        1         1   total     P2  0.089236  0.007357
 3       1  1  1        1         1   total     P3  0.008994  0.005768
-4       1  2  1        1         1   total     P0  0.622514  0.111323
-5       1  2  1        1         1   total     P1  0.239376  0.042594
-6       1  2  1        1         1   total     P2  0.088386  0.017200
-7       1  2  1        1         1   total     P3 -0.001243  0.005639
-8       2  1  1        1         1   total     P0  0.587256  0.084833
-9       2  1  1        1         1   total     P1  0.245120  0.041033
-10      2  1  1        1         1   total     P2  0.086784  0.016255
-11      2  1  1        1         1   total     P3  0.008660  0.004755
+4       1  2  1        1         1   total     P0  0.587256  0.084833
+5       1  2  1        1         1   total     P1  0.245120  0.041033
+6       1  2  1        1         1   total     P2  0.086784  0.016255
+7       1  2  1        1         1   total     P3  0.008660  0.004755
+8       2  1  1        1         1   total     P0  0.622514  0.111323
+9       2  1  1        1         1   total     P1  0.239376  0.042594
+10      2  1  1        1         1   total     P2  0.088386  0.017200
+11      2  1  1        1         1   total     P3 -0.001243  0.005639
 12      2  2  1        1         1   total     P0  0.612950  0.167940
 13      2  2  1        1         1   total     P1  0.226176  0.061882
 14      2  2  1        1         1   total     P2  0.086593  0.026126
@@ -82,14 +82,14 @@
 1       1  1  1        1         1   total     P1  0.243427  0.025488
 2       1  1  1        1         1   total     P2  0.089236  0.007357
 3       1  1  1        1         1   total     P3  0.008994  0.005768
-4       1  2  1        1         1   total     P0  0.622514  0.111323
-5       1  2  1        1         1   total     P1  0.239376  0.042594
-6       1  2  1        1         1   total     P2  0.088386  0.017200
-7       1  2  1        1         1   total     P3 -0.001243  0.005639
-8       2  1  1        1         1   total     P0  0.587256  0.084833
-9       2  1  1        1         1   total     P1  0.245120  0.041033
-10      2  1  1        1         1   total     P2  0.086784  0.016255
-11      2  1  1        1         1   total     P3  0.008660  0.004755
+4       1  2  1        1         1   total     P0  0.587256  0.084833
+5       1  2  1        1         1   total     P1  0.245120  0.041033
+6       1  2  1        1         1   total     P2  0.086784  0.016255
+7       1  2  1        1         1   total     P3  0.008660  0.004755
+8       2  1  1        1         1   total     P0  0.622514  0.111323
+9       2  1  1        1         1   total     P1  0.239376  0.042594
+10      2  1  1        1         1   total     P2  0.088386  0.017200
+11      2  1  1        1         1   total     P3 -0.001243  0.005639
 12      2  2  1        1         1   total     P0  0.613792  0.168612
 13      2  2  1        1         1   total     P1  0.226142  0.061856
 14      2  2  1        1         1   total     P2  0.086174  0.025979
@@ -97,36 +97,114 @@
   mesh 1       group in group out nuclide      mean std. dev.
        x  y  z                                               
 0      1  1  1        1         1   total  1.000000  0.088094
-1      1  2  1        1         1   total  1.000000  0.160891
-2      2  1  1        1         1   total  1.000000  0.126864
+1      1  2  1        1         1   total  1.000000  0.126864
+2      2  1  1        1         1   total  1.000000  0.160891
 3      2  2  1        1         1   total  1.001374  0.305883
   mesh 1       group in group out nuclide      mean std. dev.
        x  y  z                                               
 0      1  1  1        1         1   total  0.027395  0.004680
-1      1  2  1        1         1   total  0.022914  0.006025
-2      2  1  1        1         1   total  0.019384  0.002846
+1      1  2  1        1         1   total  0.019384  0.002846
+2      2  1  1        1         1   total  0.022914  0.006025
 3      2  2  1        1         1   total  0.029629  0.006292
   mesh 1       group out nuclide mean std. dev.
        x  y  z                                 
 0      1  1  1         1   total  1.0  0.220956
-1      1  2  1         1   total  1.0  0.316565
-2      2  1  1         1   total  1.0  0.132140
+1      1  2  1         1   total  1.0  0.132140
+2      2  1  1         1   total  1.0  0.316565
 3      2  2  1         1   total  1.0  0.181577
   mesh 1       group out nuclide mean std. dev.
        x  y  z                                 
 0      1  1  1         1   total  1.0  0.222246
-1      1  2  1         1   total  1.0  0.316565
-2      2  1  1         1   total  1.0  0.132140
+1      1  2  1         1   total  1.0  0.132140
+2      2  1  1         1   total  1.0  0.316565
 3      2  2  1         1   total  1.0  0.181577
   mesh 1       group in nuclide          mean     std. dev.
        x  y  z                                             
 0      1  1  1        1   total  3.610522e-07  3.169931e-08
-1      1  2  1        1   total  3.942353e-07  8.459167e-08
-2      2  1  1        1   total  3.097784e-07  5.252025e-08
+1      1  2  1        1   total  3.097784e-07  5.252025e-08
+2      2  1  1        1   total  3.942353e-07  8.459167e-08
 3      2  2  1        1   total  3.799163e-07  1.806470e-07
   mesh 1       group in nuclide      mean std. dev.
        x  y  z                                     
 0      1  1  1        1   total  0.025920  0.002893
-1      1  2  1        1   total  0.028922  0.006394
-2      2  1  1        1   total  0.022467  0.004039
+1      1  2  1        1   total  0.022467  0.004039
+2      2  1  1        1   total  0.028922  0.006394
 3      2  2  1        1   total  0.024923  0.009632
+   mesh 1       delayedgroup group in nuclide      mean     std. dev.
+        x  y  z                                                      
+0       1  1  1            1        1   total  0.000004  4.432732e-07
+1       1  1  1            2        1   total  0.000026  2.653319e-06
+2       1  1  1            3        1   total  0.000024  2.402270e-06
+3       1  1  1            4        1   total  0.000054  5.464055e-06
+4       1  1  1            5        1   total  0.000026  2.663025e-06
+5       1  1  1            6        1   total  0.000010  1.038005e-06
+6       1  2  1            1        1   total  0.000004  6.987770e-07
+7       1  2  1            2        1   total  0.000023  4.115234e-06
+8       1  2  1            3        1   total  0.000021  3.816392e-06
+9       1  2  1            4        1   total  0.000049  8.885822e-06
+10      1  2  1            5        1   total  0.000024  4.378290e-06
+11      1  2  1            6        1   total  0.000009  1.745695e-06
+12      2  1  1            1        1   total  0.000005  1.098837e-06
+13      2  1  1            2        1   total  0.000029  6.436855e-06
+14      2  1  1            3        1   total  0.000027  5.926286e-06
+15      2  1  1            4        1   total  0.000061  1.359391e-05
+16      2  1  1            5        1   total  0.000029  6.489015e-06
+17      2  1  1            6        1   total  0.000011  2.574270e-06
+18      2  2  1            1        1   total  0.000004  1.660497e-06
+19      2  2  1            2        1   total  0.000025  9.701974e-06
+20      2  2  1            3        1   total  0.000023  9.005217e-06
+21      2  2  1            4        1   total  0.000054  2.084107e-05
+22      2  2  1            5        1   total  0.000026  9.981045e-06
+23      2  2  1            6        1   total  0.000010  3.987979e-06
+   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  0.0  0.000000
+2       1  1  1            3         1   total  0.0  0.000000
+3       1  1  1            4         1   total  1.0  1.414214
+4       1  1  1            5         1   total  0.0  0.000000
+5       1  1  1            6         1   total  0.0  0.000000
+6       1  2  1            1         1   total  0.0  0.000000
+7       1  2  1            2         1   total  0.0  0.000000
+8       1  2  1            3         1   total  0.0  0.000000
+9       1  2  1            4         1   total  0.0  0.000000
+10      1  2  1            5         1   total  0.0  0.000000
+11      1  2  1            6         1   total  0.0  0.000000
+12      2  1  1            1         1   total  0.0  0.000000
+13      2  1  1            2         1   total  0.0  0.000000
+14      2  1  1            3         1   total  0.0  0.000000
+15      2  1  1            4         1   total  0.0  0.000000
+16      2  1  1            5         1   total  0.0  0.000000
+17      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  0.0  0.000000
+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  0.000166  0.000023
+1       1  1  1            2        1   total  0.000989  0.000136
+2       1  1  1            3        1   total  0.000907  0.000123
+3       1  1  1            4        1   total  0.002087  0.000282
+4       1  1  1            5        1   total  0.001014  0.000137
+5       1  1  1            6        1   total  0.000400  0.000054
+6       1  2  1            1        1   total  0.000167  0.000030
+7       1  2  1            2        1   total  0.001002  0.000178
+8       1  2  1            3        1   total  0.000926  0.000165
+9       1  2  1            4        1   total  0.002149  0.000384
+10      1  2  1            5        1   total  0.001056  0.000189
+11      1  2  1            6        1   total  0.000417  0.000076
+12      2  1  1            1        1   total  0.000171  0.000039
+13      2  1  1            2        1   total  0.001003  0.000226
+14      2  1  1            3        1   total  0.000918  0.000208
+15      2  1  1            4        1   total  0.002100  0.000477
+16      2  1  1            5        1   total  0.000996  0.000228
+17      2  1  1            6        1   total  0.000394  0.000090
+18      2  2  1            1        1   total  0.000171  0.000082
+19      2  2  1            2        1   total  0.001007  0.000480
+20      2  2  1            3        1   total  0.000929  0.000445
+21      2  2  1            4        1   total  0.002143  0.001028
+22      2  2  1            5        1   total  0.001026  0.000492
+23      2  2  1            6        1   total  0.000408  0.000196

tests/test_mgxs_library_mesh/test_mgxs_library_mesh.py

@@ -18,14 +18,19 @@ class MGXSTestHarness(PyAPITestHarness):
         # Initialize a one-group structure
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         # for one material-filled cell in the geometry
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
 
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'mesh'
 

tests/test_mgxs_library_no_nuclides/inputs_true.dat

@@ -1 +1 @@
-e2cdca7ea5b3532050af5b12fac26d7ef212d2696bb1b73cdd00929b2243c40d100ad02438c7b090555b49815d0de6c48cf1b4ebf437a48bc80c2d2b4bad292e
+08c5f1c783dd88c5fed51c054718ca09fc4e99aa4560a6f928b3902991948f3a878d055ac46c07548904285c2c5f22dc2a3d8c1bb82b8e73d76dd790820117df

tests/test_mgxs_library_no_nuclides/results_true.dat

@@ -29,39 +29,39 @@
 1     10000         1   total  0.385188   0.026946
 0     10000         2   total  0.412389   0.015425
     material  group in  group out nuclide moment      mean  std. dev.
-12     10000         1          1   total     P0  0.384199   0.027001
-13     10000         1          1   total     P1  0.051870   0.006983
-14     10000         1          1   total     P2  0.020069   0.002846
+9      10000         1          1   total     P0 -0.000207   0.000149
+11     10000         1          1   total     P1  0.000234   0.000128
+13     10000         1          1   total     P2  0.051870   0.006983
 15     10000         1          1   total     P3  0.009478   0.002234
 8      10000         1          2   total     P0  0.000989   0.000482
-9      10000         1          2   total     P1 -0.000207   0.000149
-10     10000         1          2   total     P2 -0.000103   0.000184
-11     10000         1          2   total     P3  0.000234   0.000128
-4      10000         2          1   total     P0  0.000925   0.000925
-5      10000         2          1   total     P1 -0.000768   0.000768
-6      10000         2          1   total     P2  0.000494   0.000494
+10     10000         1          2   total     P1 -0.000103   0.000184
+12     10000         1          2   total     P2  0.384199   0.027001
+14     10000         1          2   total     P3  0.020069   0.002846
+1      10000         2          1   total     P0  0.016482   0.004502
+3      10000         2          1   total     P1 -0.010499   0.010438
+5      10000         2          1   total     P2 -0.000768   0.000768
 7      10000         2          1   total     P3 -0.000171   0.000172
 0      10000         2          2   total     P0  0.411465   0.015245
-1      10000         2          2   total     P1  0.016482   0.004502
-2      10000         2          2   total     P2  0.006371   0.010551
-3      10000         2          2   total     P3 -0.010499   0.010438
+2      10000         2          2   total     P1  0.006371   0.010551
+4      10000         2          2   total     P2  0.000925   0.000925
+6      10000         2          2   total     P3  0.000494   0.000494
     material  group in  group out nuclide moment      mean  std. dev.
-12     10000         1          1   total     P0  0.384199   0.027001
-13     10000         1          1   total     P1  0.051870   0.006983
-14     10000         1          1   total     P2  0.020069   0.002846
+9      10000         1          1   total     P0 -0.000207   0.000149
+11     10000         1          1   total     P1  0.000234   0.000128
+13     10000         1          1   total     P2  0.051870   0.006983
 15     10000         1          1   total     P3  0.009478   0.002234
 8      10000         1          2   total     P0  0.000989   0.000482
-9      10000         1          2   total     P1 -0.000207   0.000149
-10     10000         1          2   total     P2 -0.000103   0.000184
-11     10000         1          2   total     P3  0.000234   0.000128
-4      10000         2          1   total     P0  0.000925   0.000925
-5      10000         2          1   total     P1 -0.000768   0.000768
-6      10000         2          1   total     P2  0.000494   0.000494
+10     10000         1          2   total     P1 -0.000103   0.000184
+12     10000         1          2   total     P2  0.384199   0.027001
+14     10000         1          2   total     P3  0.020069   0.002846
+1      10000         2          1   total     P0  0.016482   0.004502
+3      10000         2          1   total     P1 -0.010499   0.010438
+5      10000         2          1   total     P2 -0.000768   0.000768
 7      10000         2          1   total     P3 -0.000171   0.000172
 0      10000         2          2   total     P0  0.411465   0.015245
-1      10000         2          2   total     P1  0.016482   0.004502
-2      10000         2          2   total     P2  0.006371   0.010551
-3      10000         2          2   total     P3 -0.010499   0.010438
+2      10000         2          2   total     P1  0.006371   0.010551
+4      10000         2          2   total     P2  0.000925   0.000925
+6      10000         2          2   total     P3  0.000494   0.000494
    material  group in  group out nuclide  mean  std. dev.
 3     10000         1          1   total   1.0   0.078516
 2     10000         1          2   total   1.0   0.687184
@@ -84,6 +84,45 @@
    material  group in nuclide      mean  std. dev.
 1     10000         1   total  0.019239   0.001310
 0     10000         2   total  0.466719   0.041411
+    material  delayedgroup  group in nuclide      mean  std. dev.
+1      10000             1         1   total  0.000023   0.000002
+3      10000             2         1   total  0.000144   0.000011
+5      10000             3         1   total  0.000151   0.000011
+7      10000             4         1   total  0.000074   0.000005
+9      10000             5         1   total  0.000041   0.000003
+11     10000             6         1   total  0.000017   0.000001
+0      10000             1         2   total  0.000107   0.000009
+2      10000             2         2   total  0.000552   0.000049
+4      10000             3         2   total  0.000527   0.000047
+6      10000             4         2   total  0.000222   0.000019
+8      10000             5         2   total  0.000091   0.000008
+10     10000             6         2   total  0.000038   0.000003
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10000             1          1   total   0.0   0.000000
+3      10000             2          1   total   1.0   0.869128
+5      10000             3          1   total   1.0   1.414214
+7      10000             4          1   total   1.0   0.360359
+9      10000             5          1   total   0.0   0.000000
+11     10000             6          1   total   0.0   0.000000
+0      10000             1          2   total   0.0   0.000000
+2      10000             2          2   total   0.0   0.000000
+4      10000             3          2   total   0.0   0.000000
+6      10000             4          2   total   0.0   0.000000
+8      10000             5          2   total   0.0   0.000000
+10     10000             6          2   total   0.0   0.000000
+    material  delayedgroup  group in nuclide      mean  std. dev.
+1      10000             1         1   total  0.000049   0.000005
+3      10000             2         1   total  0.000306   0.000030
+5      10000             3         1   total  0.000322   0.000031
+7      10000             4         1   total  0.003822   0.000321
+9      10000             5         1   total  0.002135   0.000183
+11     10000             6         1   total  0.000875   0.000075
+0      10000             1         2   total  0.000228   0.000025
+2      10000             2         2   total  0.001175   0.000127
+4      10000             3         2   total  0.001122   0.000122
+6      10000             4         2   total  0.011426   0.001099
+8      10000             5         2   total  0.004684   0.000451
+10     10000             6         2   total  0.001962   0.000189
    material  group in nuclide      mean  std. dev.
 1     10001         1   total  0.313738   0.015582
 0     10001         2   total  0.300821   0.028052
@@ -115,39 +154,39 @@
 1     10001         1   total  0.310121   0.033788
 0     10001         2   total  0.296264   0.043792
     material  group in  group out nuclide moment      mean  std. dev.
-12     10001         1          1   total     P0  0.310121   0.033788
-13     10001         1          1   total     P1  0.038230   0.008484
-14     10001         1          1   total     P2  0.020745   0.004696
+9      10001         1          1   total     P0  0.000000   0.000000
+11     10001         1          1   total     P1  0.000000   0.000000
+13     10001         1          1   total     P2  0.038230   0.008484
 15     10001         1          1   total     P3  0.007964   0.003732
 8      10001         1          2   total     P0  0.000000   0.000000
-9      10001         1          2   total     P1  0.000000   0.000000
-10     10001         1          2   total     P2  0.000000   0.000000
-11     10001         1          2   total     P3  0.000000   0.000000
-4      10001         2          1   total     P0  0.000000   0.000000
-5      10001         2          1   total     P1  0.000000   0.000000
-6      10001         2          1   total     P2  0.000000   0.000000
+10     10001         1          2   total     P1  0.000000   0.000000
+12     10001         1          2   total     P2  0.310121   0.033788
+14     10001         1          2   total     P3  0.020745   0.004696
+1      10001         2          1   total     P0 -0.011214   0.016180
+3      10001         2          1   total     P1 -0.003270   0.007329
+5      10001         2          1   total     P2  0.000000   0.000000
 7      10001         2          1   total     P3  0.000000   0.000000
 0      10001         2          2   total     P0  0.296264   0.043792
-1      10001         2          2   total     P1 -0.011214   0.016180
-2      10001         2          2   total     P2  0.008837   0.011504
-3      10001         2          2   total     P3 -0.003270   0.007329
+2      10001         2          2   total     P1  0.008837   0.011504
+4      10001         2          2   total     P2  0.000000   0.000000
+6      10001         2          2   total     P3  0.000000   0.000000
     material  group in  group out nuclide moment      mean  std. dev.
-12     10001         1          1   total     P0  0.310121   0.033788
-13     10001         1          1   total     P1  0.038230   0.008484
-14     10001         1          1   total     P2  0.020745   0.004696
+9      10001         1          1   total     P0  0.000000   0.000000
+11     10001         1          1   total     P1  0.000000   0.000000
+13     10001         1          1   total     P2  0.038230   0.008484
 15     10001         1          1   total     P3  0.007964   0.003732
 8      10001         1          2   total     P0  0.000000   0.000000
-9      10001         1          2   total     P1  0.000000   0.000000
-10     10001         1          2   total     P2  0.000000   0.000000
-11     10001         1          2   total     P3  0.000000   0.000000
-4      10001         2          1   total     P0  0.000000   0.000000
-5      10001         2          1   total     P1  0.000000   0.000000
-6      10001         2          1   total     P2  0.000000   0.000000
+10     10001         1          2   total     P1  0.000000   0.000000
+12     10001         1          2   total     P2  0.310121   0.033788
+14     10001         1          2   total     P3  0.020745   0.004696
+1      10001         2          1   total     P0 -0.011214   0.016180
+3      10001         2          1   total     P1 -0.003270   0.007329
+5      10001         2          1   total     P2  0.000000   0.000000
 7      10001         2          1   total     P3  0.000000   0.000000
 0      10001         2          2   total     P0  0.296264   0.043792
-1      10001         2          2   total     P1 -0.011214   0.016180
-2      10001         2          2   total     P2  0.008837   0.011504
-3      10001         2          2   total     P3 -0.003270   0.007329
+2      10001         2          2   total     P1  0.008837   0.011504
+4      10001         2          2   total     P2  0.000000   0.000000
+6      10001         2          2   total     P3  0.000000   0.000000
    material  group in  group out nuclide  mean  std. dev.
 3     10001         1          1   total   1.0   0.108779
 2     10001         1          2   total   0.0   0.000000
@@ -170,6 +209,45 @@
    material  group in nuclide  mean  std. dev.
 1     10001         1   total   0.0        0.0
 0     10001         2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10001             1         1   total   0.0        0.0
+3      10001             2         1   total   0.0        0.0
+5      10001             3         1   total   0.0        0.0
+7      10001             4         1   total   0.0        0.0
+9      10001             5         1   total   0.0        0.0
+11     10001             6         1   total   0.0        0.0
+0      10001             1         2   total   0.0        0.0
+2      10001             2         2   total   0.0        0.0
+4      10001             3         2   total   0.0        0.0
+6      10001             4         2   total   0.0        0.0
+8      10001             5         2   total   0.0        0.0
+10     10001             6         2   total   0.0        0.0
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10001             1          1   total   0.0        0.0
+3      10001             2          1   total   0.0        0.0
+5      10001             3          1   total   0.0        0.0
+7      10001             4          1   total   0.0        0.0
+9      10001             5          1   total   0.0        0.0
+11     10001             6          1   total   0.0        0.0
+0      10001             1          2   total   0.0        0.0
+2      10001             2          2   total   0.0        0.0
+4      10001             3          2   total   0.0        0.0
+6      10001             4          2   total   0.0        0.0
+8      10001             5          2   total   0.0        0.0
+10     10001             6          2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10001             1         1   total   0.0        0.0
+3      10001             2         1   total   0.0        0.0
+5      10001             3         1   total   0.0        0.0
+7      10001             4         1   total   0.0        0.0
+9      10001             5         1   total   0.0        0.0
+11     10001             6         1   total   0.0        0.0
+0      10001             1         2   total   0.0        0.0
+2      10001             2         2   total   0.0        0.0
+4      10001             3         2   total   0.0        0.0
+6      10001             4         2   total   0.0        0.0
+8      10001             5         2   total   0.0        0.0
+10     10001             6         2   total   0.0        0.0
    material  group in nuclide      mean  std. dev.
 1     10002         1   total  0.664572   0.031215
 0     10002         2   total  2.052384   0.224343
@@ -201,39 +279,39 @@
 1     10002         1   total  0.671269   0.026186
 0     10002         2   total  2.035388   0.258060
     material  group in  group out nuclide moment      mean  std. dev.
-12     10002         1          1   total     P0  0.639901   0.024709
-13     10002         1          1   total     P1  0.381167   0.016243
-14     10002         1          1   total     P2  0.152392   0.008156
+9      10002         1          1   total     P0  0.008758   0.000926
+11     10002         1          1   total     P1 -0.003785   0.000817
+13     10002         1          1   total     P2  0.381167   0.016243
 15     10002         1          1   total     P3  0.009148   0.003889
 8      10002         1          2   total     P0  0.031368   0.001728
-9      10002         1          2   total     P1  0.008758   0.000926
-10     10002         1          2   total     P2 -0.002568   0.001014
-11     10002         1          2   total     P3 -0.003785   0.000817
-4      10002         2          1   total     P0  0.000443   0.000445
-5      10002         2          1   total     P1  0.000400   0.000401
-6      10002         2          1   total     P2  0.000320   0.000321
+10     10002         1          2   total     P1 -0.002568   0.001014
+12     10002         1          2   total     P2  0.639901   0.024709
+14     10002         1          2   total     P3  0.152392   0.008156
+1      10002         2          1   total     P0  0.509941   0.051236
+3      10002         2          1   total     P1  0.024988   0.008312
+5      10002         2          1   total     P2  0.000400   0.000401
 7      10002         2          1   total     P3  0.000214   0.000215
 0      10002         2          2   total     P0  2.034945   0.257800
-1      10002         2          2   total     P1  0.509941   0.051236
-2      10002         2          2   total     P2  0.111175   0.013020
-3      10002         2          2   total     P3  0.024988   0.008312
+2      10002         2          2   total     P1  0.111175   0.013020
+4      10002         2          2   total     P2  0.000443   0.000445
+6      10002         2          2   total     P3  0.000320   0.000321
     material  group in  group out nuclide moment      mean  std. dev.
-12     10002         1          1   total     P0  0.639901   0.024709
-13     10002         1          1   total     P1  0.381167   0.016243
-14     10002         1          1   total     P2  0.152392   0.008156
+9      10002         1          1   total     P0  0.008758   0.000926
+11     10002         1          1   total     P1 -0.003785   0.000817
+13     10002         1          1   total     P2  0.381167   0.016243
 15     10002         1          1   total     P3  0.009148   0.003889
 8      10002         1          2   total     P0  0.031368   0.001728
-9      10002         1          2   total     P1  0.008758   0.000926
-10     10002         1          2   total     P2 -0.002568   0.001014
-11     10002         1          2   total     P3 -0.003785   0.000817
-4      10002         2          1   total     P0  0.000443   0.000445
-5      10002         2          1   total     P1  0.000400   0.000401
-6      10002         2          1   total     P2  0.000320   0.000321
+10     10002         1          2   total     P1 -0.002568   0.001014
+12     10002         1          2   total     P2  0.639901   0.024709
+14     10002         1          2   total     P3  0.152392   0.008156
+1      10002         2          1   total     P0  0.509941   0.051236
+3      10002         2          1   total     P1  0.024988   0.008312
+5      10002         2          1   total     P2  0.000400   0.000401
 7      10002         2          1   total     P3  0.000214   0.000215
 0      10002         2          2   total     P0  2.034945   0.257800
-1      10002         2          2   total     P1  0.509941   0.051236
-2      10002         2          2   total     P2  0.111175   0.013020
-3      10002         2          2   total     P3  0.024988   0.008312
+2      10002         2          2   total     P1  0.111175   0.013020
+4      10002         2          2   total     P2  0.000443   0.000445
+6      10002         2          2   total     P3  0.000320   0.000321
    material  group in  group out nuclide  mean  std. dev.
 3     10002         1          1   total   1.0   0.038609
 2     10002         1          2   total   1.0   0.067667
@@ -256,3 +334,42 @@
    material  group in nuclide  mean  std. dev.
 1     10002         1   total   0.0        0.0
 0     10002         2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10002             1         1   total   0.0        0.0
+3      10002             2         1   total   0.0        0.0
+5      10002             3         1   total   0.0        0.0
+7      10002             4         1   total   0.0        0.0
+9      10002             5         1   total   0.0        0.0
+11     10002             6         1   total   0.0        0.0
+0      10002             1         2   total   0.0        0.0
+2      10002             2         2   total   0.0        0.0
+4      10002             3         2   total   0.0        0.0
+6      10002             4         2   total   0.0        0.0
+8      10002             5         2   total   0.0        0.0
+10     10002             6         2   total   0.0        0.0
+    material  delayedgroup  group out nuclide  mean  std. dev.
+1      10002             1          1   total   0.0        0.0
+3      10002             2          1   total   0.0        0.0
+5      10002             3          1   total   0.0        0.0
+7      10002             4          1   total   0.0        0.0
+9      10002             5          1   total   0.0        0.0
+11     10002             6          1   total   0.0        0.0
+0      10002             1          2   total   0.0        0.0
+2      10002             2          2   total   0.0        0.0
+4      10002             3          2   total   0.0        0.0
+6      10002             4          2   total   0.0        0.0
+8      10002             5          2   total   0.0        0.0
+10     10002             6          2   total   0.0        0.0
+    material  delayedgroup  group in nuclide  mean  std. dev.
+1      10002             1         1   total   0.0        0.0
+3      10002             2         1   total   0.0        0.0
+5      10002             3         1   total   0.0        0.0
+7      10002             4         1   total   0.0        0.0
+9      10002             5         1   total   0.0        0.0
+11     10002             6         1   total   0.0        0.0
+0      10002             1         2   total   0.0        0.0
+2      10002             2         2   total   0.0        0.0
+4      10002             3         2   total   0.0        0.0
+6      10002             4         2   total   0.0        0.0
+8      10002             5         2   total   0.0        0.0
+10     10002             6         2   total   0.0        0.0

tests/test_mgxs_library_no_nuclides/test_mgxs_library_no_nuclides.py

@@ -23,12 +23,18 @@ class MGXSTestHarness(PyAPITestHarness):
         energy_groups = openmc.mgxs.EnergyGroups(group_edges=[0, 0.625e-6,
                                                               20.])
 
+        # Initialize a six-delayed-group structure
+        delayed_groups = list(range(1,7))
+
         # Initialize MGXS Library for a few cross section types
         self.mgxs_lib = openmc.mgxs.Library(self._input_set.geometry)
         self.mgxs_lib.by_nuclide = False
+
         # Test all MGXS types
-        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES
+        self.mgxs_lib.mgxs_types = openmc.mgxs.MGXS_TYPES + \
+                                   openmc.mgxs.MDGXS_TYPES
         self.mgxs_lib.energy_groups = energy_groups
+        self.mgxs_lib.delayed_groups = delayed_groups
         self.mgxs_lib.legendre_order = 3
         self.mgxs_lib.domain_type = 'material'
         self.mgxs_lib.build_library()

tests/test_mgxs_library_nuclides/results_true.dat

@@ -1 +1 @@
-e494320a213b5704a2ac915a2ba504857be91961ceb6735b6ad05d81eb31c44c9584d5bd9d40baececf1dcb5b030e6ecec63cfbd20639baf69bcb596c5c46591
+8142ae4e107002a835999e4ace85c17376f262a7059fc224f3756a2de19aba6ca4c4fa14ca2085c87d7729aa8d6d6f78fdae21ac6dfe33ca303449c769076074

tests/test_score_current/results_true.dat

@@ -1 +1 @@
-bafab1921a12146abb2bb29603b52b9cc28a5a950a7a6bb1e3f012c05891c310fad643760d4f148b04d0fef3d1f3e141d146e3a278d81cc6fc8187c37717c5e7
+c2921f159dac64099862c1cd9c6d421c977991f621f954f893ec1351cfcea6794ca2c98c9c2dcc3411f1b8dac91ec83bd895788ba33179222c450a7df1d64f1e

tests/test_tallies/inputs_true.dat

@@ -1 +1 @@
-930af242a043f2676a000dbc5a2db6b148edcb31ed8c87dbaa35a8efb37a3be8cff30cdf4dc03f9c5c7eb4021f7e4c3327e64681cdd8fd8722c95c69db850227
+1bef757d276362fdcd9405096b4cdcbd894f9215ed406493486a45193729be446c9a12242c887f89b6e209ec5beaaacb04dee2fd61e72b4f5c6a8712b776ed6e

tests/test_tallies/results_true.dat

@@ -1 +1 @@
-a51db2a4efc681805f85968e04411dc33beee0532c202f5179b9a82880ab60a75e53fa9141c81045ea1d2842372f2d8da900326f09382ea61dd80a3c9b43bba1
+a6afd2f11affce2467d77b8477881ab20091f67df4f632226ec2dd5d4cd7fabb9ac3e182563bb467ed249e4b3fe95b319cb688d653757f8ea154759b8a7f50e1

tests/test_tallies/test_tallies.py

@@ -123,8 +123,9 @@ class TalliesTestHarness(PyAPITestHarness):
             t.filters = [cell_filter]
             t.scores = ['absorption', 'delayed-nu-fission', 'events', 'fission',
                         'inverse-velocity', 'kappa-fission', '(n,2n)', '(n,n1)',
-                        '(n,gamma)', 'nu-fission', 'scatter', 'elastic', 'total',
-                        'prompt-nu-fission']
+                        '(n,gamma)', 'nu-fission', 'scatter', 'elastic', 
+                        'total', 'prompt-nu-fission', 'fission-q-prompt',
+                        'fission-q-recoverable']
         score_tallies[0].estimator = 'tracklength'
         score_tallies[1].estimator = 'analog'
         score_tallies[2].estimator = 'collision'

tests/test_tally_slice_merge/results_true.dat

@@ -49,19 +49,19 @@
 14     (500, 5000, 50000)          6.25e-07           2.00e+01    U238     fission 0.00e+00   0.00e+00
 15     (500, 5000, 50000)          6.25e-07           2.00e+01    U238  nu-fission 0.00e+00   0.00e+00
                  sum(mesh)  energy low [MeV]  energy high [MeV] nuclide       score     mean  std. dev.
-0   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235     fission 9.18e-03   1.62e-03
-1   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.24e-02   3.94e-03
-2   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.31e-08   2.08e-09
-3   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.26e-08   5.19e-09
-4   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235     fission 8.40e-04   2.13e-04
-5   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 2.06e-03   5.17e-04
-6   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238     fission 7.05e-04   3.42e-04
-7   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 1.99e-03   1.01e-03
-8   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235     fission 8.77e-03   1.30e-03
-9   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.14e-02   3.18e-03
-10  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.24e-08   1.74e-09
-11  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.08e-08   4.33e-09
-12  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235     fission 2.30e-03   6.20e-04
-13  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 5.63e-03   1.52e-03
-14  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238     fission 1.45e-03   7.19e-04
-15  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 3.97e-03   1.98e-03
+0   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235     fission 8.54e-03   1.30e-03
+1   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.08e-02   3.17e-03
+2   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.21e-08   1.74e-09
+3   ((1, 1, 1), (1, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.01e-08   4.34e-09
+4   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235     fission 2.20e-03   6.05e-04
+5   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 5.38e-03   1.48e-03
+6   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238     fission 1.40e-03   7.17e-04
+7   ((1, 1, 1), (1, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 3.84e-03   1.97e-03
+8   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235     fission 9.40e-03   1.62e-03
+9   ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U235  nu-fission 2.29e-02   3.95e-03
+10  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238     fission 1.34e-08   2.08e-09
+11  ((2, 1, 1), (2, 2, 1))          0.00e+00           6.25e-07    U238  nu-fission 3.33e-08   5.18e-09
+12  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235     fission 9.41e-04   2.52e-04
+13  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U235  nu-fission 2.31e-03   6.13e-04
+14  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238     fission 7.54e-04   3.45e-04
+15  ((2, 1, 1), (2, 2, 1))          6.25e-07           2.00e+01    U238  nu-fission 2.12e-03   1.02e-03

tests/test_track_output/results_true.dat

@@ -1,5 +1,5 @@
 <?xml version="1.0"?>
-<VTKFile type="PPolyData" version="0.1" byte_order="LittleEndian" compressor="vtkZLibDataCompressor">
+<VTKFile type="PPolyData" version="0.1" byte_order="LittleEndian" header_type="UInt32" compressor="vtkZLibDataCompressor">
   <PPolyData GhostLevel="0">
     <PPoints>
       <PDataArray type="Float32" Name="Points" NumberOfComponents="3"/>