diff --git a/Pincell-solution.ipynb b/Pincell-solution.ipynb index 052c2299b7..09285d0457 100644 --- a/Pincell-solution.ipynb +++ b/Pincell-solution.ipynb @@ -1846,7 +1846,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:52:33\n", + " Date/Time | 2024-03-29 14:34:17\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -2002,21 +2002,21 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.5945e+00 seconds\n", - " Reading cross sections = 3.5022e+00 seconds\n", - " Total time in simulation = 1.3932e+00 seconds\n", - " Time in transport only = 1.3779e+00 seconds\n", - " Time in inactive batches = 1.3178e-01 seconds\n", - " Time in active batches = 1.2615e+00 seconds\n", - " Time synchronizing fission bank = 6.1483e-03 seconds\n", - " Sampling source sites = 4.8103e-03 seconds\n", - " SEND/RECV source sites = 5.4429e-04 seconds\n", - " Time accumulating tallies = 4.4751e-05 seconds\n", - " Time writing statepoints = 5.2411e-03 seconds\n", - " Total time for finalization = 3.7780e-06 seconds\n", - " Total time elapsed = 4.9977e+00 seconds\n", - " Calculation Rate (inactive) = 75884 particles/second\n", - " Calculation Rate (active) = 71346.1 particles/second\n", + " Total time for initialization = 2.3567e+00 seconds\n", + " Reading cross sections = 2.2972e+00 seconds\n", + " Total time in simulation = 1.7247e+00 seconds\n", + " Time in transport only = 1.7078e+00 seconds\n", + " Time in inactive batches = 1.6326e-01 seconds\n", + " Time in active batches = 1.5614e+00 seconds\n", + " Time synchronizing fission bank = 6.8949e-03 seconds\n", + " Sampling source sites = 5.3603e-03 seconds\n", + " SEND/RECV source sites = 6.2301e-04 seconds\n", + " Time accumulating tallies = 4.6476e-05 seconds\n", + " Time writing statepoints = 5.4268e-03 seconds\n", + " Total time for finalization = 3.2870e-06 seconds\n", + " Total time elapsed = 4.0915e+00 seconds\n", + " Calculation Rate (inactive) = 61253.5 particles/second\n", + " Calculation Rate (active) = 57640.6 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -2117,7 +2117,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:52:38\n", + " Date/Time | 2024-03-29 14:34:21\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -2163,20 +2163,28 @@ "name": "stdout", "output_type": "stream", "text": [ - "CMakeLists.txt csg_half.png pyproject.toml\r\n", - "CODEOWNERS \u001b[1m\u001b[36mdocs\u001b[m\u001b[m pytest.ini\r\n", - "CODE_OF_CONDUCT.md \u001b[1m\u001b[36mexamples\u001b[m\u001b[m \u001b[1m\u001b[36mscripts\u001b[m\u001b[m\r\n", - "CONTRIBUTING.md geometry.xml settings.xml\r\n", - "Dockerfile \u001b[1m\u001b[36minclude\u001b[m\u001b[m \u001b[31msetup.py\u001b[m\u001b[m\r\n", - "LICENSE \u001b[1m\u001b[36mman\u001b[m\u001b[m \u001b[1m\u001b[36msrc\u001b[m\u001b[m\r\n", - "Lattice-solution.ipynb materials.xml statepoint.100.h5\r\n", - "MANIFEST.in mc_bcs.png summary.h5\r\n", - "Pincell-solution.ipynb model.xml tallies.out\r\n", - "Pincell.ipynb \u001b[1m\u001b[36mopenmc\u001b[m\u001b[m \u001b[1m\u001b[36mtests\u001b[m\u001b[m\r\n", - "README.md \u001b[1m\u001b[36mopenmc.egg-info\u001b[m\u001b[m \u001b[1m\u001b[36mtools\u001b[m\u001b[m\r\n", - "bcs.png pincell.png \u001b[1m\u001b[36mvendor\u001b[m\u001b[m\r\n", - "\u001b[1m\u001b[36mbuild\u001b[m\u001b[m pinplot.png\r\n", - "\u001b[1m\u001b[36mcmake\u001b[m\u001b[m plots.xml\r\n" + "AdvancedGeometry-solution.ipynb mc_bcs.png\r\n", + "CMakeLists.txt mesh.i\r\n", + "CODEOWNERS mesh_in.e\r\n", + "CODE_OF_CONDUCT.md model.xml\r\n", + "CONTRIBUTING.md \u001b[1m\u001b[36mopenmc\u001b[m\u001b[m\r\n", + "Dockerfile \u001b[1m\u001b[36mopenmc.egg-info\u001b[m\u001b[m\r\n", + "LICENSE pincell.png\r\n", + "Lattice-solution.ipynb pinplot.png\r\n", + "MANIFEST.in plots.xml\r\n", + "Pincell-solution.ipynb pyproject.toml\r\n", + "Pincell.ipynb pytest.ini\r\n", + "README.md \u001b[1m\u001b[36mscripts\u001b[m\u001b[m\r\n", + "bcs.png settings.xml\r\n", + "\u001b[1m\u001b[36mbuild\u001b[m\u001b[m \u001b[31msetup.py\u001b[m\u001b[m\r\n", + "\u001b[1m\u001b[36mcmake\u001b[m\u001b[m \u001b[1m\u001b[36msrc\u001b[m\u001b[m\r\n", + "csg_half.png statepoint.100.h5\r\n", + "\u001b[1m\u001b[36mdocs\u001b[m\u001b[m summary.h5\r\n", + "\u001b[1m\u001b[36mexamples\u001b[m\u001b[m tallies.out\r\n", + "geometry.xml \u001b[1m\u001b[36mtests\u001b[m\u001b[m\r\n", + "\u001b[1m\u001b[36minclude\u001b[m\u001b[m \u001b[1m\u001b[36mtools\u001b[m\u001b[m\r\n", + "\u001b[1m\u001b[36mman\u001b[m\u001b[m \u001b[1m\u001b[36mvendor\u001b[m\u001b[m\r\n", + "materials.xml\r\n" ] }, { @@ -2250,7 +2258,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 51, "metadata": {}, "outputs": [ { @@ -2258,7 +2266,7 @@ "output_type": "stream", "text": [ "Tally\n", - "\tID =\t2\n", + "\tID =\t1\n", "\tName =\t\n", "\tFilters =\t\n", "\tNuclides =\t\n", @@ -2276,7 +2284,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": 52, "metadata": {}, "outputs": [], "source": [ @@ -2292,7 +2300,7 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": 53, "metadata": {}, "outputs": [ { @@ -2328,7 +2336,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:52:53\n", + " Date/Time | 2024-03-29 14:34:21\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -2483,21 +2491,21 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.8615e+00 seconds\n", - " Reading cross sections = 1.8077e+00 seconds\n", - " Total time in simulation = 1.6308e+00 seconds\n", - " Time in transport only = 1.6093e+00 seconds\n", - " Time in inactive batches = 1.5203e-01 seconds\n", - " Time in active batches = 1.4788e+00 seconds\n", - " Time synchronizing fission bank = 6.2872e-03 seconds\n", - " Sampling source sites = 4.9126e-03 seconds\n", - " SEND/RECV source sites = 5.4075e-04 seconds\n", - " Time accumulating tallies = 5.1714e-03 seconds\n", - " Time writing statepoints = 5.7013e-03 seconds\n", - " Total time for finalization = 1.9038e-03 seconds\n", - " Total time elapsed = 3.5040e+00 seconds\n", - " Calculation Rate (inactive) = 65778.1 particles/second\n", - " Calculation Rate (active) = 60859.3 particles/second\n", + " Total time for initialization = 2.0523e+00 seconds\n", + " Reading cross sections = 1.9999e+00 seconds\n", + " Total time in simulation = 2.1030e+00 seconds\n", + " Time in transport only = 2.0748e+00 seconds\n", + " Time in inactive batches = 1.4362e-01 seconds\n", + " Time in active batches = 1.9594e+00 seconds\n", + " Time synchronizing fission bank = 7.3517e-03 seconds\n", + " Sampling source sites = 5.7251e-03 seconds\n", + " SEND/RECV source sites = 6.3934e-04 seconds\n", + " Time accumulating tallies = 1.0267e-02 seconds\n", + " Time writing statepoints = 5.5837e-03 seconds\n", + " Total time for finalization = 2.6649e-04 seconds\n", + " Total time elapsed = 4.1654e+00 seconds\n", + " Calculation Rate (inactive) = 69627.5 particles/second\n", + " Calculation Rate (active) = 45932.7 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -2523,9 +2531,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ============================> TALLY 1 <============================\r\n", + "\r\n", + " Total Material\r\n", + " Fission Rate 0.581783 +/- 0.00229294\r\n", + " Kappa-Fission Rate 1.12634e+08 +/- 443455\r\n" + ] + } + ], "source": [ "!cat tallies.out" ] @@ -2539,9 +2559,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/Users/anovak/projects/openmc/statepoint.100.h5\n" + ] + } + ], "source": [ "print(statepoint)" ] @@ -2555,7 +2583,7 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": 56, "metadata": {}, "outputs": [ { @@ -2563,7 +2591,7 @@ "output_type": "stream", "text": [ "Tally\n", - "\tID =\t2\n", + "\tID =\t1\n", "\tName =\t\n", "\tFilters =\t\n", "\tNuclides =\ttotal\n", @@ -2571,7 +2599,7 @@ "\tEstimator =\ttracklength\n", "\tMultiply dens. =\tTrue\n", "Tally\n", - "\tID =\t2\n", + "\tID =\t1\n", "\tName =\t\n", "\tFilters =\t\n", "\tNuclides =\ttotal\n", @@ -2606,7 +2634,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": 57, "metadata": {}, "outputs": [], "source": [ @@ -2615,14 +2643,14 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 58, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "MeV per fission: 193.60144334284888\n" + "MeV per fission: 193.6014433428488\n" ] } ], @@ -2636,7 +2664,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 59, "metadata": {}, "outputs": [ { @@ -2676,7 +2704,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 60, "metadata": {}, "outputs": [ { @@ -2693,7 +2721,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 61, "metadata": {}, "outputs": [ { @@ -2702,7 +2730,7 @@ "70" ] }, - "execution_count": 60, + "execution_count": 61, "metadata": {}, "output_type": "execute_result" } @@ -2714,7 +2742,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ @@ -2725,7 +2753,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 63, "metadata": {}, "outputs": [ { @@ -2761,7 +2789,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:53:04\n", + " Date/Time | 2024-03-29 14:34:26\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -2916,21 +2944,21 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.7547e+00 seconds\n", - " Reading cross sections = 1.7063e+00 seconds\n", - " Total time in simulation = 1.7648e+00 seconds\n", - " Time in transport only = 1.7410e+00 seconds\n", - " Time in inactive batches = 1.2309e-01 seconds\n", - " Time in active batches = 1.6417e+00 seconds\n", - " Time synchronizing fission bank = 5.9754e-03 seconds\n", - " Sampling source sites = 4.6510e-03 seconds\n", - " SEND/RECV source sites = 5.4439e-04 seconds\n", - " Time accumulating tallies = 7.7004e-03 seconds\n", - " Time writing statepoints = 6.2223e-03 seconds\n", - " Total time for finalization = 6.3069e-04 seconds\n", - " Total time elapsed = 3.5296e+00 seconds\n", - " Calculation Rate (inactive) = 81241.8 particles/second\n", - " Calculation Rate (active) = 54820.3 particles/second\n", + " Total time for initialization = 2.0435e+00 seconds\n", + " Reading cross sections = 1.9552e+00 seconds\n", + " Total time in simulation = 1.9591e+00 seconds\n", + " Time in transport only = 1.9310e+00 seconds\n", + " Time in inactive batches = 1.5164e-01 seconds\n", + " Time in active batches = 1.8075e+00 seconds\n", + " Time synchronizing fission bank = 6.6273e-03 seconds\n", + " Sampling source sites = 5.1675e-03 seconds\n", + " SEND/RECV source sites = 5.9234e-04 seconds\n", + " Time accumulating tallies = 8.8949e-03 seconds\n", + " Time writing statepoints = 8.1831e-03 seconds\n", + " Total time for finalization = 4.5152e-04 seconds\n", + " Total time elapsed = 4.0131e+00 seconds\n", + " Calculation Rate (inactive) = 65946 particles/second\n", + " Calculation Rate (active) = 49793.7 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -2950,19 +2978,19 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 64, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " ============================> TALLY 2 <============================\r\n", + " ============================> TALLY 1 <============================\r\n", "\r\n", " Total Material\r\n", " Fission Rate 0.581783 +/- 0.00229294\r\n", " Kappa-Fission Rate 1.12634e+08 +/- 443455\r\n", - " ============================> TALLY 3 <============================\r\n", + " ============================> TALLY 2 <============================\r\n", "\r\n", " Incoming Energy [0, 0.005)\r\n", " Total Material\r\n", @@ -3183,7 +3211,7 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 65, "metadata": {}, "outputs": [], "source": [ @@ -3195,7 +3223,7 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": 66, "metadata": {}, "outputs": [], "source": [ @@ -3204,7 +3232,7 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 67, "metadata": {}, "outputs": [ { @@ -3257,7 +3285,7 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 68, "metadata": {}, "outputs": [ { @@ -3289,7 +3317,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 69, "metadata": {}, "outputs": [], "source": [ @@ -3301,7 +3329,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 70, "metadata": {}, "outputs": [ { @@ -3337,7 +3365,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:53:20\n", + " Date/Time | 2024-03-29 14:34:30\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -3492,21 +3520,21 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.9315e+00 seconds\n", - " Reading cross sections = 1.8820e+00 seconds\n", - " Total time in simulation = 2.4354e+00 seconds\n", - " Time in transport only = 2.4003e+00 seconds\n", - " Time in inactive batches = 2.1139e-01 seconds\n", - " Time in active batches = 2.2240e+00 seconds\n", - " Time synchronizing fission bank = 6.5034e-03 seconds\n", - " Sampling source sites = 4.9867e-03 seconds\n", - " SEND/RECV source sites = 5.9260e-04 seconds\n", - " Time accumulating tallies = 1.7377e-02 seconds\n", - " Time writing statepoints = 6.6364e-03 seconds\n", - " Total time for finalization = 4.7286e-04 seconds\n", - " Total time elapsed = 4.3775e+00 seconds\n", - " Calculation Rate (inactive) = 47305.1 particles/second\n", - " Calculation Rate (active) = 40466.8 particles/second\n", + " Total time for initialization = 2.1963e+00 seconds\n", + " Reading cross sections = 2.1396e+00 seconds\n", + " Total time in simulation = 1.9032e+00 seconds\n", + " Time in transport only = 1.8521e+00 seconds\n", + " Time in inactive batches = 1.4214e-01 seconds\n", + " Time in active batches = 1.7610e+00 seconds\n", + " Time synchronizing fission bank = 6.1936e-03 seconds\n", + " Sampling source sites = 4.8027e-03 seconds\n", + " SEND/RECV source sites = 5.7378e-04 seconds\n", + " Time accumulating tallies = 2.7497e-02 seconds\n", + " Time writing statepoints = 1.2327e-02 seconds\n", + " Total time for finalization = 1.1213e-03 seconds\n", + " Total time elapsed = 4.1105e+00 seconds\n", + " Calculation Rate (inactive) = 70353.3 particles/second\n", + " Calculation Rate (active) = 51106.9 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -3525,7 +3553,7 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 71, "metadata": {}, "outputs": [], "source": [ @@ -3546,14 +3574,14 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 72, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Neutron source (n/s): 11097897947492.566\n" + "Neutron source (n/s): 11097897947492.568\n" ] } ], @@ -3565,7 +3593,7 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": 73, "metadata": {}, "outputs": [], "source": [ @@ -3574,7 +3602,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 74, "metadata": {}, "outputs": [ { @@ -3609,7 +3637,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 75, "metadata": {}, "outputs": [ { @@ -3679,7 +3707,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 76, "metadata": {}, "outputs": [], "source": [ @@ -3691,7 +3719,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 77, "metadata": {}, "outputs": [], "source": [ @@ -3700,7 +3728,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 78, "metadata": {}, "outputs": [ { @@ -3736,7 +3764,7 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.14.1-dev\n", " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", - " Date/Time | 2024-03-28 17:53:32\n", + " Date/Time | 2024-03-29 14:34:35\n", " MPI Processes | 1\n", " OpenMP Threads | 8\n", "\n", @@ -3891,21 +3919,21 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.9356e+00 seconds\n", - " Reading cross sections = 1.8800e+00 seconds\n", - " Total time in simulation = 2.0891e+00 seconds\n", - " Time in transport only = 2.0609e+00 seconds\n", - " Time in inactive batches = 1.5984e-01 seconds\n", - " Time in active batches = 1.9293e+00 seconds\n", - " Time synchronizing fission bank = 6.2127e-03 seconds\n", - " Sampling source sites = 4.8604e-03 seconds\n", - " SEND/RECV source sites = 5.5933e-04 seconds\n", - " Time accumulating tallies = 1.0551e-02 seconds\n", - " Time writing statepoints = 7.4516e-03 seconds\n", - " Total time for finalization = 1.2378e-03 seconds\n", - " Total time elapsed = 4.0361e+00 seconds\n", - " Calculation Rate (inactive) = 62563.5 particles/second\n", - " Calculation Rate (active) = 46649.7 particles/second\n", + " Total time for initialization = 1.9115e+00 seconds\n", + " Reading cross sections = 1.8639e+00 seconds\n", + " Total time in simulation = 1.9756e+00 seconds\n", + " Time in transport only = 1.9494e+00 seconds\n", + " Time in inactive batches = 1.4190e-01 seconds\n", + " Time in active batches = 1.8337e+00 seconds\n", + " Time synchronizing fission bank = 5.9623e-03 seconds\n", + " Sampling source sites = 4.6432e-03 seconds\n", + " SEND/RECV source sites = 5.3352e-04 seconds\n", + " Time accumulating tallies = 9.3554e-03 seconds\n", + " Time writing statepoints = 6.9239e-03 seconds\n", + " Total time for finalization = 5.6553e-04 seconds\n", + " Total time elapsed = 3.8974e+00 seconds\n", + " Calculation Rate (inactive) = 70471.2 particles/second\n", + " Calculation Rate (active) = 49081 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -3931,7 +3959,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 79, "metadata": {}, "outputs": [], "source": [ @@ -3945,7 +3973,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 80, "metadata": {}, "outputs": [ { @@ -4093,7 +4121,7 @@ "11 5 total fission 0.00e+00 0.00e+00" ] }, - "execution_count": 79, + "execution_count": 80, "metadata": {}, "output_type": "execute_result" } @@ -4104,7 +4132,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 81, "metadata": {}, "outputs": [ { @@ -4265,7 +4293,7 @@ "11 5 total fission 0.00e+00 0.00e+00 0.00e+00" ] }, - "execution_count": 80, + "execution_count": 81, "metadata": {}, "output_type": "execute_result" } @@ -4284,8 +4312,10 @@ }, { "cell_type": "code", - "execution_count": 81, - "metadata": {}, + "execution_count": 82, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -4472,7 +4502,7 @@ "11 NaN " ] }, - "execution_count": 81, + "execution_count": 82, "metadata": {}, "output_type": "execute_result" } @@ -4487,6 +4517,241 @@ "df" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Task 4: Mesh Tallies\n", + "\n", + "In order to restrict a tally to a particular region in space, OpenMC supports (i) cell, (ii) structured mesh, and (iii) unstructured mesh tallies. For unstructured mesh tallies, you need to compile OpenMC with libMesh enabled. We don't have this dependency set up on the Collab instance, so we'll just work with structured mesh tallies." + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [], + "source": [ + "mesh = openmc.RegularMesh()\n", + "mesh.lower_left = (-pitch/2, -pitch/2)\n", + "mesh.upper_right = (pitch/2, pitch/2)\n", + "mesh.dimension = (50, 50)\n", + "\n", + "mesh_filter = openmc.MeshFilter(mesh)\n", + "heat = openmc.Tally()\n", + "heat.scores = ['kappa-fission']\n", + "heat.filters = [mesh_filter]\n", + "model.tallies += [heat]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", + "\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2024 MIT, UChicago Argonne LLC, and contributors\n", + " License | https://docs.openmc.org/en/latest/license.html\n", + " Version | 0.14.1-dev\n", + " Git SHA1 | 14ce3cec4b388ae8b7ec5b28db57dbcbff06f147\n", + " Date/Time | 2024-03-29 14:39:01\n", + " MPI Processes | 1\n", + " OpenMP Threads | 8\n", + "\n", + " Reading model XML file 'model.xml' ...\n", + " WARNING: Other XML file input(s) are present. These files may be ignored in\n", + " favor of the model.xml file.\n", + " Reading cross sections XML file...\n", + " Reading Zr90 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Zr90.h5\n", + " Reading Zr91 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Zr91.h5\n", + " Reading Zr92 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Zr92.h5\n", + " Reading Zr94 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Zr94.h5\n", + " Reading Zr96 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Zr96.h5\n", + " Reading U234 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/U234.h5\n", + " Reading U235 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/U235.h5\n", + " Reading U238 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/U238.h5\n", + " Reading U236 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/U236.h5\n", + " Reading O16 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/O16.h5\n", + " Reading H1 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/H1.h5\n", + " Reading H2 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/H2.h5\n", + " Reading O17 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/O17.h5\n", + " Reading Pu239 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Pu239.h5\n", + " Reading Si28 from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/Si28.h5\n", + " Reading c_H_in_H2O from\n", + " /Users/anovak/projects/cross_sections/endfb-vii.1-hdf5/neutron/c_H_in_H2O.h5\n", + " Minimum neutron data temperature: 250 K\n", + " Maximum neutron data temperature: 2500 K\n", + " Preparing distributed cell instances...\n", + " Writing summary.h5 file...\n", + " Maximum neutron transport energy: 20000000 eV for Zr90\n", + " Initializing source particles...\n", + "\n", + " ====================> K EIGENVALUE SIMULATION <====================\n", + "\n", + " Bat./Gen. k Average k\n", + " ========= ======== ====================\n", + " 1/1 1.50315\n", + " 2/1 1.44086\n", + " 3/1 1.46540\n", + " 4/1 1.37107\n", + " 5/1 1.33015\n", + " 6/1 1.48464\n", + " 7/1 1.47998\n", + " 8/1 1.28684\n", + " 9/1 1.45556\n", + " 10/1 1.40944\n", + " 11/1 1.39122\n", + " 12/1 1.32307 1.35714 +/- 0.03407\n", + " 13/1 1.52588 1.41339 +/- 0.05959\n", + " 14/1 1.46026 1.42511 +/- 0.04373\n", + " 15/1 1.41125 1.42233 +/- 0.03399\n", + " 16/1 1.45798 1.42827 +/- 0.02838\n", + " 17/1 1.46100 1.43295 +/- 0.02444\n", + " 18/1 1.42515 1.43197 +/- 0.02119\n", + " 19/1 1.54914 1.44499 +/- 0.02277\n", + " 20/1 1.43623 1.44412 +/- 0.02039\n", + " 21/1 1.40115 1.44021 +/- 0.01885\n", + " 22/1 1.43731 1.43997 +/- 0.01721\n", + " 23/1 1.41573 1.43811 +/- 0.01594\n", + " 24/1 1.46427 1.43997 +/- 0.01487\n", + " 25/1 1.45526 1.44099 +/- 0.01389\n", + " 26/1 1.33933 1.43464 +/- 0.01446\n", + " 27/1 1.42147 1.43386 +/- 0.01360\n", + " 28/1 1.36027 1.42978 +/- 0.01346\n", + " 29/1 1.46546 1.43165 +/- 0.01287\n", + " 30/1 1.45070 1.43261 +/- 0.01225\n", + " 31/1 1.48473 1.43509 +/- 0.01191\n", + " 32/1 1.47264 1.43680 +/- 0.01149\n", + " 33/1 1.45237 1.43747 +/- 0.01100\n", + " 34/1 1.41749 1.43664 +/- 0.01056\n", + " 35/1 1.47971 1.43836 +/- 0.01027\n", + " 36/1 1.45378 1.43896 +/- 0.00989\n", + " 37/1 1.35765 1.43594 +/- 0.00998\n", + " 38/1 1.40397 1.43480 +/- 0.00969\n", + " 39/1 1.41697 1.43419 +/- 0.00937\n", + " 40/1 1.40400 1.43318 +/- 0.00910\n", + " 41/1 1.43270 1.43317 +/- 0.00881\n", + " 42/1 1.36535 1.43105 +/- 0.00879\n", + " 43/1 1.43240 1.43109 +/- 0.00851\n", + " 44/1 1.46349 1.43204 +/- 0.00832\n", + " 45/1 1.32866 1.42909 +/- 0.00860\n", + " 46/1 1.32249 1.42613 +/- 0.00886\n", + " 47/1 1.41734 1.42589 +/- 0.00862\n", + " 48/1 1.39802 1.42516 +/- 0.00843\n", + " 49/1 1.54696 1.42828 +/- 0.00878\n", + " 50/1 1.44601 1.42872 +/- 0.00857\n", + " 51/1 1.37546 1.42742 +/- 0.00846\n", + " 52/1 1.48833 1.42887 +/- 0.00838\n", + " 53/1 1.36864 1.42747 +/- 0.00830\n", + " 54/1 1.45539 1.42811 +/- 0.00814\n", + " 55/1 1.47463 1.42914 +/- 0.00802\n", + " 56/1 1.43531 1.42927 +/- 0.00785\n", + " 57/1 1.37650 1.42815 +/- 0.00776\n", + " 58/1 1.43163 1.42822 +/- 0.00760\n", + " 59/1 1.39161 1.42748 +/- 0.00748\n", + " 60/1 1.48475 1.42862 +/- 0.00742\n", + " 61/1 1.47918 1.42961 +/- 0.00734\n", + " 62/1 1.47997 1.43058 +/- 0.00726\n", + " 63/1 1.41811 1.43035 +/- 0.00712\n", + " 64/1 1.41011 1.42997 +/- 0.00700\n", + " 65/1 1.44239 1.43020 +/- 0.00688\n", + " 66/1 1.42912 1.43018 +/- 0.00675\n", + " 67/1 1.39312 1.42953 +/- 0.00666\n", + " 68/1 1.47339 1.43028 +/- 0.00659\n", + " 69/1 1.38559 1.42953 +/- 0.00652\n", + " 70/1 1.42211 1.42940 +/- 0.00641\n", + " 71/1 1.35744 1.42822 +/- 0.00642\n", + " 72/1 1.40876 1.42791 +/- 0.00632\n", + " 73/1 1.53582 1.42962 +/- 0.00645\n", + " 74/1 1.44605 1.42988 +/- 0.00636\n", + " 75/1 1.47428 1.43056 +/- 0.00629\n", + " 76/1 1.37855 1.42977 +/- 0.00625\n", + " 77/1 1.39439 1.42925 +/- 0.00618\n", + " 78/1 1.49117 1.43016 +/- 0.00615\n", + " 79/1 1.34815 1.42897 +/- 0.00618\n", + " 80/1 1.30610 1.42721 +/- 0.00634\n", + " 81/1 1.44634 1.42748 +/- 0.00625\n", + " 82/1 1.41633 1.42733 +/- 0.00617\n", + " 83/1 1.45974 1.42777 +/- 0.00610\n", + " 84/1 1.45538 1.42814 +/- 0.00603\n", + " 85/1 1.45563 1.42851 +/- 0.00596\n", + " 86/1 1.37790 1.42785 +/- 0.00592\n", + " 87/1 1.43465 1.42793 +/- 0.00584\n", + " 88/1 1.32547 1.42662 +/- 0.00591\n" + ] + } + ], + "source": [ + "statepoint = model.run()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "with openmc.StatePoint(statepoint) as sp:\n", + " mesh_tally_out = sp.get_tally(id=heat.id)\n", + " \n", + "mesh_flux = mesh_tally_out.get_values(scores=['ka'])\n", + "mesh_flux = mesh_flux.reshape(mesh.dimension)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure()\n", + "img = plt.imshow(mesh_flux)\n", + "plt.colorbar(img, label='Heating')" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -4500,77 +4765,16 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[Material\n", - "\tID =\t3\n", - "\tName =\tuo2\n", - "\tTemperature =\tNone\n", - "\tDensity =\t10.0 [g/cm3]\n", - "\tVolume =\tNone [cm^3]\n", - "\tDepletable =\tTrue\n", - "\tS(a,b) Tables \n", - "\tNuclides \n", - "\tU234 =\t0.0003166930253944235 [ao]\n", - "\tU235 =\t0.03543164439454172 [ao]\n", - "\tU238 =\t0.964089368630351 [ao]\n", - "\tU236 =\t0.00016229394971280895 [ao]\n", - "\tO16 =\t2.0 [ao]\n", - ", Material\n", - "\tID =\t1\n", - "\tName =\tzirconium\n", - "\tTemperature =\tNone\n", - "\tDensity =\t6.5 [g/cm3]\n", - "\tVolume =\tNone [cm^3]\n", - "\tDepletable =\tFalse\n", - "\tS(a,b) Tables \n", - "\tNuclides \n", - "\tZr90 =\t0.5145 [ao]\n", - "\tZr91 =\t0.1122 [ao]\n", - "\tZr92 =\t0.1715 [ao]\n", - "\tZr94 =\t0.1738 [ao]\n", - "\tZr96 =\t0.028 [ao]\n", - ", Material\n", - "\tID =\t4\n", - "\tName =\twater\n", - "\tTemperature =\tNone\n", - "\tDensity =\t1.0 [g/cm3]\n", - "\tVolume =\tNone [cm^3]\n", - "\tDepletable =\tFalse\n", - "\tS(a,b) Tables \n", - "\tS(a,b) =\t('c_H_in_H2O', 1.0)\n", - "\tNuclides \n", - "\tH1 =\t1.99968852 [ao]\n", - "\tH2 =\t0.00031148 [ao]\n", - "\tO16 =\t0.999621 [ao]\n", - "\tO17 =\t0.000379 [ao]\n", - ", Material\n", - "\tID =\t5\n", - "\tName =\tnew_fuel\n", - "\tTemperature =\tNone\n", - "\tDensity =\t9.0 [g/cm3]\n", - "\tVolume =\tNone [cm^3]\n", - "\tDepletable =\tTrue\n", - "\tS(a,b) Tables \n", - "\tNuclides \n", - "\tPu239 =\t1.0 [ao]\n", - "\tSi28 =\t2.0 [ao]\n", - "]\n" - ] - } - ], + "outputs": [], "source": [ "print(model.materials)" ] }, { "cell_type": "code", - "execution_count": 83, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4583,7 +4787,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4600,7 +4804,7 @@ }, { "cell_type": "code", - "execution_count": 85, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4619,30 +4823,9 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "big_universe = openmc.Universe(cells=[big_cell])\n", "big_universe.plot(width=(10.0, 10.0))" @@ -4657,30 +4840,9 @@ }, { "cell_type": "code", - "execution_count": 87, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "pin_surface.x0 = 1.0\n", "pin_surface.y0 = 1.5\n", @@ -4696,30 +4858,9 @@ }, { "cell_type": "code", - "execution_count": 91, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 91, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "big_cell.translation = [-1.0, 0.0, 0.0]\n", "big_universe.plot(width=(10.0, 10.0))" @@ -4736,7 +4877,7 @@ }, { "cell_type": "code", - "execution_count": 102, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4763,30 +4904,9 @@ }, { "cell_type": "code", - "execution_count": 98, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 98, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "pitch = 1.26\n", "fuel_or = openmc.ZCylinder(r=0.39)\n", @@ -4811,30 +4931,9 @@ }, { "cell_type": "code", - "execution_count": 101, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 101, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "guide_clad_ir = openmc.ZCylinder(r=0.56)\n", "guide_clad_or = openmc.ZCylinder(r=0.60)\n", @@ -4863,7 +4962,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4898,30 +4997,9 @@ }, { "cell_type": "code", - "execution_count": 111, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 111, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "u = openmc.Universe(cells=[openmc.Cell(fill=lattice)])\n", "u.plot(width=(3*pitch, 3*pitch), color_by='material', colors=colors)" @@ -4938,30 +5016,9 @@ }, { "cell_type": "code", - "execution_count": 112, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 112, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "lattice.outer = guide_tube\n", "u.plot(width=(3*pitch, 3*pitch), color_by='material', colors=colors)" @@ -4976,7 +5033,7 @@ }, { "cell_type": "code", - "execution_count": 113, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -4991,7 +5048,7 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5022,7 +5079,7 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5032,30 +5089,9 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 128, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "u = openmc.Universe(cells=(main_cell,))\n", "u.plot(width=(assembly_pitch, assembly_pitch), color_by='material', colors=colors, pixels=(500,500))" @@ -5088,20 +5124,9 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(449, 3)" - ] - }, - "execution_count": 129, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "r_cylinder = 10.\n", "h_cylinder = 20.\n", @@ -5118,29 +5143,9 @@ }, { "cell_type": "code", - "execution_count": 130, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[-5.10289038, 6.29780828, 0.8952101 ],\n", - " [-4.25201716, -5.970076 , -1.37623342],\n", - " [ 1.52830345, -0.08304641, -4.7576057 ],\n", - " [-5.3332856 , -1.4678357 , -6.97819421],\n", - " [ 1.5334012 , 1.58441154, -1.72639827],\n", - " [-2.15249399, 3.37401012, -3.64399805],\n", - " [-6.99253594, 3.50814097, 0.30360063],\n", - " [-1.99582165, 0.68561887, -3.13899813],\n", - " [-5.68554108, -4.9068005 , -4.54563289],\n", - " [ 4.52719666, 3.54688819, 6.33369786]])" - ] - }, - "execution_count": 130, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "centers[:10]" ] @@ -5154,7 +5159,7 @@ }, { "cell_type": "code", - "execution_count": 132, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5171,27 +5176,9 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Cell\n", - "\tID =\t495\n", - "\tName =\t\n", - "\tFill =\t31\n", - "\tRegion =\t-491\n", - "\tRotation =\tNone\n", - "\tTranslation =\t[-5.10289038 6.29780828 0.8952101 ]\n", - "\tVolume =\tNone" - ] - }, - "execution_count": 135, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "trisos = [openmc.model.TRISO(outer_radius=r_sphere, fill=sphere_univ, center=center) for center in centers]\n", "trisos[0]" @@ -5206,20 +5193,9 @@ }, { "cell_type": "code", - "execution_count": 138, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0.2993333333333333" - ] - }, - "execution_count": 138, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import math\n", "volume_trisos = len(trisos)*4/3*math.pi*r_sphere**3\n", @@ -5229,30 +5205,9 @@ }, { "cell_type": "code", - "execution_count": 142, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 142, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "region_background = openmc.Intersection([~t.region for t in trisos])\n", "background_cell = openmc.Cell(region=region_background & -cylinder)\n", @@ -5269,7 +5224,7 @@ }, { "cell_type": "code", - "execution_count": 144, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -5282,10 +5237,30 @@ " lower_left=lower_left,\n", " pitch=pitch,\n", " shape=shape,\n", - " background=None\n", + " background=zirconium\n", ")" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "c = openmc.Cell(fill=lattice, region=-cylinder)\n", + "univ = openmc.Universe(cells=[c])\n", + "univ.plot(width=(20., 20.))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "univ.plot(width=(20., 20.), color_by='material')" + ] + }, { "cell_type": "code", "execution_count": null,