From 966169de084fcfda3a5aaca3edc0065c8caf6bbc Mon Sep 17 00:00:00 2001 From: Adam Nelson Date: Tue, 7 Mar 2017 07:31:03 -0500 Subject: [PATCH] Revised notebooks according to comments and added a C5G7 library --- docs/source/examples/c5g7.h5 | Bin 0 -> 53208 bytes docs/source/examples/mg-mode-part-i.ipynb | 465 ++++++-------------- docs/source/examples/mg-mode-part-ii.ipynb | 263 +++++------ docs/source/examples/mg-mode-part-iii.ipynb | 176 +++++--- 4 files changed, 352 insertions(+), 552 deletions(-) create mode 100644 docs/source/examples/c5g7.h5 diff --git a/docs/source/examples/c5g7.h5 b/docs/source/examples/c5g7.h5 new file mode 100644 index 0000000000000000000000000000000000000000..323afd078d604493892f194b1c635819b7e72826 GIT binary patch literal 53208 zcmeHQc|cRg*1v#D#0_yNO4T4PNKsHxqe4yu6k0dL4W-twM4=+k5CvDFwu(MQ)Vfq$ z;)ZC|#vObv5f`W{C_HgP#EPi3;QHui)$b-VBi2;Fi9LbH7uOYH{;OL zN!5u!btm%!voYO8-&z7bfxm6^9pv-=|7evOvyRqA3 z6Z*Y|hI0-Wy?r}e;8I}ukA2%cfN}x=X;Tkb? zn41w*m$Jcag;P+3^vnAZrM(xRkcaCP#xm=rZbIq&%_t+li{=? 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This example notebook creates and executes the 2-D [C5G7](https://www.oecd-nea.org/science/docs/2003/nsc-doc2003-16.pdf) benchmark model using the `openmc.MGXSLibrary`class to create the supporting data library on the fly." + "This Notebook illustrates the usage of OpenMC's multi-group calculational mode with the Python API. This example notebook creates and executes the 2-D [C5G7](https://www.oecd-nea.org/science/docs/2003/nsc-doc2003-16.pdf) benchmark model using the `openmc.MGXSLibrary` class to create the supporting data library on the fly." ] }, { @@ -24,7 +24,6 @@ "source": [ "import os\n", "\n", - "from IPython.display import Image\n", "import matplotlib.pyplot as plt\n", "import matplotlib.colors as colors\n", "import numpy as np\n", @@ -56,209 +55,66 @@ "# Create a 7-group structure with arbitrary boundaries (the specific boundaries are unimportant)\n", "groups = openmc.mgxs.EnergyGroups(np.logspace(-5, 7, 8))\n", "\n", - "# Add data for the UO2 material\n", "uo2_xsdata = openmc.XSdata('uo2', groups)\n", "uo2_xsdata.order = 0\n", - "# When setting the data let the object know you are setting the data for a temperature of 294K.\n", - "uo2_xsdata.set_total([1.779490E-01, 3.298050E-01, 4.803880E-01, 5.543670E-01,\n", - " 3.118010E-01, 3.951680E-01, 5.644060E-01], temperature=294.)\n", "\n", - "uo2_xsdata.set_absorption([8.02480E-03, 3.71740E-03, 2.67690E-02, 9.62360E-02,\n", - " 3.00200E-02, 1.11260E-01, 2.82780E-01], temperature=294.)\n", + "# When setting the data let the object know you are setting the data for a temperature of 294K.\n", + "uo2_xsdata.set_total([1.77949E-1, 3.29805E-1, 4.80388E-1, 5.54367E-1,\n", + " 3.11801E-1, 3.95168E-1, 5.64406E-1], temperature=294.)\n", + "\n", + "uo2_xsdata.set_absorption([8.0248E-03, 3.7174E-3, 2.6769E-2, 9.6236E-2,\n", + " 3.0020E-02, 1.1126E-1, 2.8278E-1], temperature=294.)\n", + "uo2_xsdata.set_fission([7.21206E-3, 8.19301E-4, 6.45320E-3, 1.85648E-2,\n", + " 1.78084E-2, 8.30348E-2, 2.16004E-1], temperature=294.)\n", + "\n", + "uo2_xsdata.set_nu_fission([2.005998E-2, 2.027303E-3, 1.570599E-2, 4.518301E-2,\n", + " 4.334208E-2, 2.020901E-1, 5.257105E-1], temperature=294.)\n", + "\n", + "uo2_xsdata.set_chi([5.87910E-1, 4.11760E-1, 3.39060E-4, 1.17610E-7,\n", + " 0.00000E-0, 0.00000E-0, 0.00000E-0], temperature=294.)\n", "\n", "# The scattering matrix is ordered with incoming groups as rows and outgoing groups as columns\n", "# (i.e., above the diagonal is up-scattering).\n", "scatter_matrix = \\\n", - " [[[1.275370E-01, 4.237800E-02, 9.437400E-06, 5.516300E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 3.244560E-01, 1.631400E-03, 3.142700E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 4.509400E-01, 2.679200E-03, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 4.525650E-01, 5.566400E-03, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 1.252500E-04, 2.714010E-01, 1.025500E-02, 1.002100E-08],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 1.296800E-03, 2.658020E-01, 1.680900E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 8.545800E-03, 2.730800E-01]]]\n", + " [[[1.27537E-1, 4.23780E-2, 9.43740E-6, 5.51630E-9, 0.00000E-0, 0.00000E-0, 0.00000E-0],\n", + " [0.00000E-0, 3.24456E-1, 1.63140E-3, 3.14270E-9, 0.00000E-0, 0.00000E-0, 0.00000E-0],\n", + " [0.00000E-0, 0.00000E-0, 4.50940E-1, 2.67920E-3, 0.00000E-0, 0.00000E-0, 0.00000E-0],\n", + " [0.00000E-0, 0.00000E-0, 0.00000E-0, 4.52565E-1, 5.56640E-3, 0.00000E-0, 0.00000E-0],\n", + " [0.00000E-0, 0.00000E-0, 0.00000E-0, 1.25250E-4, 2.71401E-1, 1.02550E-2, 1.00210E-8],\n", + " [0.00000E-0, 0.00000E-0, 0.00000E-0, 0.00000E-0, 1.29680E-3, 2.65802E-1, 1.68090E-2],\n", + " [0.00000E-0, 0.00000E-0, 0.00000E-0, 0.00000E-0, 0.00000E-0, 8.54580E-3, 2.73080E-1]]]\n", "scatter_matrix = np.array(scatter_matrix)\n", "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "uo2_xsdata.set_scatter_matrix(scatter_matrix, temperature=294.)\n", - "\n", - "uo2_xsdata.set_fission([7.212060E-03, 8.193010E-04, 6.453200E-03, 1.856480E-02,\n", - " 1.780840E-02, 8.303480E-02, 2.160040E-01], temperature=294.)\n", - "\n", - "uo2_xsdata.set_nu_fission([2.005998E-02, 2.027303E-03, 1.570599E-02, 4.518301E-02,\n", - " 4.334208E-02, 2.020901E-01, 5.257105E-01], temperature=294.)\n", - "\n", - "uo2_xsdata.set_chi([5.87910E-01, 4.11760E-01, 3.39060E-04, 1.17610E-07,\n", - " 0.000000E-00, 0.000000E-00, 0.000000E-00], temperature=294.)" + "uo2_xsdata.set_scatter_matrix(scatter_matrix, temperature=294.)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Now that the UO2 data has been added to the library, we can move on to the remaining materials using the same process. This time, we will be slightly less verbose: 294K is actually the default temperature and so we do not need to explicitly state it as such." + "Now that the UO2 data has been created, we can move on to the remaining materials using the same process.\n", + "\n", + "However, we will actually skip repeating the above for now. Our simulation will instead use the `c5g7.h5` file that has already been created using exactly the same logic as above, but for the remaining materials in the benchmark problem.\n", + "\n", + "For now we will show how you would use the `uo2_xsdata` information to create an `openmc.MGXSLibrary` object and write to disk." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { - "collapsed": false - }, - "outputs": [], - "source": [ - "mox43_xsdata = openmc.XSdata('mox43', groups)\n", - "mox43_xsdata.order = 0\n", - "mox43_xsdata.set_total([1.787310E-01, 3.308490E-01, 4.837720E-01, 5.669220E-01,\n", - " 4.262270E-01, 6.789970E-01, 6.828520E-01])\n", - "mox43_xsdata.set_absorption([8.43390E-03, 3.75770E-03, 2.79700E-02, 1.04210E-01,\n", - " 1.39940E-01, 4.09180E-01, 4.09350E-01])\n", - "scatter_matrix = \\\n", - " [[[1.288760E-01, 4.141300E-02, 8.229000E-06, 5.040500E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 3.254520E-01, 1.639500E-03, 1.598200E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 4.531880E-01, 2.614200E-03, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 4.571730E-01, 5.539400E-03, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 1.604600E-04, 2.768140E-01, 9.312700E-03, 9.165600E-09],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 2.005100E-03, 2.529620E-01, 1.485000E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 8.494800E-03, 2.650070E-01]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "mox43_xsdata.set_scatter_matrix(scatter_matrix)\n", - "mox43_xsdata.set_fission([7.62704E-03, 8.76898E-04, 5.69835E-03, 2.28872E-02,\n", - " 1.07635E-02, 2.32757E-01, 2.48968E-01])\n", - "mox43_xsdata.set_nu_fission([2.175300E-02, 2.535103E-03, 1.626799E-02, 6.547410E-02,\n", - " 3.072409E-02, 6.666510E-01, 7.139904E-01])\n", - "mox43_xsdata.set_chi([5.87910E-01, 4.11760E-01, 3.39060E-04, 1.17610E-07,\n", - " 0.000000E-00, 0.000000E-00, 0.000000E-00])\n", - "\n", - "mox7_xsdata = openmc.XSdata('mox7', groups)\n", - "mox7_xsdata.order = 0\n", - "mox7_xsdata.set_total([1.813230E-01, 3.343680E-01, 4.937850E-01, 5.912160E-01,\n", - " 4.741980E-01, 8.336010E-01, 8.536030E-01])\n", - "mox7_xsdata.set_absorption([9.06570E-03, 4.29670E-03, 3.28810E-02, 1.22030E-01,\n", - " 1.82980E-01, 5.68460E-01, 5.85210E-01])\n", - "scatter_matrix = \\\n", - " [[[1.304570E-01, 4.179200E-02, 8.510500E-06, 5.132900E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 3.284280E-01, 1.643600E-03, 2.201700E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 4.583710E-01, 2.533100E-03, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 4.637090E-01, 5.476600E-03, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 1.761900E-04, 2.823130E-01, 8.728900E-03, 9.001600E-09],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 2.276000E-03, 2.497510E-01, 1.311400E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 8.864500E-03, 2.595290E-01]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "mox7_xsdata.set_scatter_matrix(scatter_matrix)\n", - "mox7_xsdata.set_fission([8.25446E-03, 1.32565E-03, 8.42156E-03, 3.28730E-02,\n", - " 1.59636E-02, 3.23794E-01, 3.62803E-01])\n", - "mox7_xsdata.set_nu_fission([2.381395E-02, 3.858689E-03, 2.413400E-02, 9.436622E-02,\n", - " 4.576988E-02, 9.281814E-01, 1.043200E+00])\n", - "mox7_xsdata.set_chi([5.87910E-01, 4.11760E-01, 3.39060E-04, 1.17610E-07,\n", - " 0.000000E-00, 0.000000E-00, 0.000000E-00])\n", - "\n", - "mox87_xsdata = openmc.XSdata('mox87', groups)\n", - "mox87_xsdata.order = 0\n", - "mox87_xsdata.set_total([1.830450E-01, 3.367050E-01, 5.005070E-01, 6.061740E-01,\n", - " 5.027540E-01, 9.210280E-01, 9.552310E-01])\n", - "mox87_xsdata.set_absorption([9.48620E-03, 4.65560E-03, 3.62400E-02, 1.32720E-01,\n", - " 2.08400E-01, 6.58700E-01, 6.90170E-01])\n", - "scatter_matrix = \\\n", - " [[[1.315040E-01, 4.204600E-02, 8.697200E-06, 5.193800E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 3.304030E-01, 1.646300E-03, 2.600600E-09, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 4.617920E-01, 2.474900E-03, 0.000000E-00, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 4.680210E-01, 5.433000E-03, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 1.859700E-04, 2.857710E-01, 8.397300E-03, 8.928000E-09],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 2.391600E-03, 2.476140E-01, 1.232200E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 8.968100E-03, 2.560930E-01]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "mox87_xsdata.set_scatter_matrix(scatter_matrix)\n", - "mox87_xsdata.set_fission([8.67209E-03, 1.62426E-03, 1.02716E-02, 3.90447E-02,\n", - " 1.92576E-02, 3.74888E-01, 4.30599E-01])\n", - "mox87_xsdata.set_nu_fission([2.518600E-02, 4.739509E-03, 2.947805E-02, 1.122500E-01,\n", - " 5.530301E-02, 1.074999E+00, 1.239298E+00])\n", - "mox87_xsdata.set_chi([5.87910E-01, 4.11760E-01, 3.39060E-04, 1.17610E-07,\n", - " 0.000000E-00, 0.000000E-00, 0.000000E-00])\n", - "\n", - "fiss_chamber_xsdata = openmc.XSdata('fiss_chamber', groups)\n", - "fiss_chamber_xsdata.order = 0\n", - "fiss_chamber_xsdata.set_total([1.260320E-01, 2.931600E-01, 2.842500E-01, 2.810200E-01,\n", - " 3.344600E-01, 5.656400E-01, 1.172140E+00])\n", - "fiss_chamber_xsdata.set_absorption([5.11320E-04, 7.58130E-05, 3.16430E-04, 1.16750E-03,\n", - " 3.39770E-03, 9.18860E-03, 2.32440E-02])\n", - "scatter_matrix = \\\n", - " [[[6.616590E-02, 5.907000E-02, 2.833400E-04, 1.462200E-06, 2.064200E-08, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 2.403770E-01, 5.243500E-02, 2.499000E-04, 1.923900E-05, 2.987500E-06, 4.214000E-07],\n", - " [0.000000E-00, 0.000000E-00, 1.834250E-01, 9.228800E-02, 6.936500E-03, 1.079000E-03, 2.054300E-04],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 7.907690E-02, 1.699900E-01, 2.586000E-02, 4.925600E-03],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 3.734000E-05, 9.975700E-02, 2.067900E-01, 2.447800E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 9.174200E-04, 3.167740E-01, 2.387600E-01],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 4.979300E-02, 1.09910E+00]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "fiss_chamber_xsdata.set_scatter_matrix(scatter_matrix)\n", - "fiss_chamber_xsdata.set_fission([4.79002E-09, 5.82564E-09, 4.63719E-07, 5.24406E-06,\n", - " 1.45390E-07, 7.14972E-07, 2.08041E-06])\n", - "fiss_chamber_xsdata.set_nu_fission([1.323401E-08, 1.434500E-08, 1.128599E-06, 1.276299E-05,\n", - " 3.538502E-07, 1.740099E-06, 5.063302E-06])\n", - "fiss_chamber_xsdata.set_chi([5.87910E-01, 4.11760E-01, 3.39060E-04, 1.17610E-07,\n", - " 0.000000E-00, 0.000000E-00, 0.000000E-00])\n", - "\n", - "guide_tube_xsdata = openmc.XSdata('guide_tube', groups)\n", - "guide_tube_xsdata.order = 0\n", - "guide_tube_xsdata.set_total([1.260320E-01, 2.931600E-01, 2.842400E-01, 2.809600E-01,\n", - " 3.344400E-01, 5.656400E-01, 1.172150E+00])\n", - "guide_tube_xsdata.set_absorption([5.11320E-04, 7.58010E-05, 3.15720E-04, 1.15820E-03,\n", - " 3.39750E-03, 9.18780E-03, 2.32420E-02])\n", - "scatter_matrix = \\\n", - " [[[6.616590E-02, 5.907000E-02, 2.833400E-04, 1.462200E-06, 2.064200E-08, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 2.403770E-01, 5.243500E-02, 2.499000E-04, 1.923900E-05, 2.987500E-06, 4.214000E-07],\n", - " [0.000000E-00, 0.000000E-00, 1.832970E-01, 9.239700E-02, 6.944600E-03, 1.080300E-03, 2.056700E-04],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 7.885110E-02, 1.701400E-01, 2.588100E-02, 4.929700E-03],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 3.733300E-05, 9.973720E-02, 2.067900E-01, 2.447800E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 9.172600E-04, 3.167650E-01, 2.387700E-01],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 4.979200E-02, 1.099120E+00]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "guide_tube_xsdata.set_scatter_matrix(scatter_matrix)\n", - "\n", - "water_xsdata = openmc.XSdata('water', groups)\n", - "water_xsdata.order = 0\n", - "water_xsdata.set_total([1.592060E-01, 4.129700E-01, 5.903100E-01, 5.843500E-01,\n", - " 7.180000E-01, 1.254450E+00, 2.650380E+00])\n", - "water_xsdata.set_absorption([6.01050E-04, 1.57930E-05, 3.37160E-04, 1.94060E-03,\n", - " 5.74160E-03, 1.50010E-02, 3.72390E-02])\n", - "scatter_matrix = \\\n", - " [[[4.447770E-02, 1.134000E-01, 7.234700E-04, 3.749900E-06, 5.318400E-08, 0.000000E-00, 0.000000E-00],\n", - " [0.000000E-00, 2.823340E-01, 1.299400E-01, 6.234000E-04, 4.800200E-05, 7.448600E-06, 1.045500E-06],\n", - " [0.000000E-00, 0.000000E-00, 3.452560E-01, 2.245700E-01, 1.699900E-02, 2.644300E-03, 5.034400E-04],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 9.102840E-02, 4.155100E-01, 6.373200E-02, 1.213900E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 7.143700E-05, 1.391380E-01, 5.118200E-01, 6.122900E-02],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 2.215700E-03, 6.999130E-01, 5.373200E-01],\n", - " [0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 0.000000E-00, 1.324400E-01, 2.480700E+00]]]\n", - "scatter_matrix = np.array(scatter_matrix)\n", - "scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)\n", - "water_xsdata.set_scatter_matrix(scatter_matrix)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So far we have not yet set the data for individual materials but have not yet combined them together into a library; we will do that next and then write that library to disk." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ + "# Initialize the library\n", "mg_cross_sections_file = openmc.MGXSLibrary(groups)\n", - "mg_cross_sections_file.add_xsdatas([uo2_xsdata, mox43_xsdata, mox7_xsdata, mox87_xsdata,\n", - " fiss_chamber_xsdata, guide_tube_xsdata, water_xsdata])\n", "\n", - "# And finally, write the file to 'mgxs.h5' in the current directory so OpenMC can read it later\n", - "mg_cross_sections_file.export_to_hdf5('./mgxs.h5')" + "# Add the UO2 data to it\n", + "mg_cross_sections_file.add_xsdata(uo2_xsdata)\n", + "\n", + "# And write to disk\n", + "mg_cross_sections_file.export_to_hdf5('mgxs.h5')" ] }, { @@ -285,50 +141,18 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Instantiate some Macroscopic Data using a name that is the same as that which was used in the\n", - "# MGXS Library earlier\n", - "uo2_data = openmc.Macroscopic('uo2')\n", - "mox43_data = openmc.Macroscopic('mox43')\n", - "mox7_data = openmc.Macroscopic('mox7')\n", - "mox87_data = openmc.Macroscopic('mox87')\n", - "fiss_chamber_data = openmc.Macroscopic('fiss_chamber')\n", - "guide_tube_data = openmc.Macroscopic('guide_tube')\n", - "water_data = openmc.Macroscopic('water')\n", - "\n", - "# Instantiate Materials dictionary\n", + "# For every cross section data set in the library, assign an openmc.Macroscopic object to a material\n", "materials = {}\n", - "\n", - "# Instantiate some Materials and register the appropriate Macroscopic objects\n", - "materials['UO2'] = openmc.Material(name='UO2')\n", - "materials['UO2'].set_density('macro', 1.0)\n", - "materials['UO2'].add_macroscopic(uo2_data)\n", - "\n", - "materials['MOX 4.3%'] = openmc.Material(name='MOX 4.3%')\n", - "materials['MOX 4.3%'].set_density('macro', 1.0)\n", - "materials['MOX 4.3%'].add_macroscopic(mox43_data)\n", - "\n", - "materials['MOX 7.0%'] = openmc.Material(name='MOX 7.0%')\n", - "materials['MOX 7.0%'].set_density('macro', 1.0)\n", - "materials['MOX 7.0%'].add_macroscopic(mox7_data)\n", - "\n", - "materials['MOX 8.7%'] = openmc.Material(name='MOX 8.7%')\n", - "materials['MOX 8.7%'].set_density('macro', 1.0)\n", - "materials['MOX 8.7%'].add_macroscopic(mox87_data)\n", - "\n", - "materials['Fission Chamber'] = openmc.Material(name='Fission Chamber')\n", - "materials['Fission Chamber'].add_macroscopic(fiss_chamber_data)\n", - "\n", - "materials['Guide Tube'] = openmc.Material(name='Guide Tube')\n", - "materials['Guide Tube'].add_macroscopic(guide_tube_data)\n", - "\n", - "materials['Water'] = openmc.Material(name='Water')\n", - "materials['Water'].add_macroscopic(water_data)" + "for xs in ['uo2', 'mox43', 'mox7', 'mox87', 'fiss_chamber', 'guide_tube', 'water']:\n", + " materials[xs] = openmc.Material(name=xs)\n", + " materials[xs].set_density('macro', 1.)\n", + " materials[xs].add_macroscopic(openmc.Macroscopic(xs))" ] }, { @@ -340,7 +164,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "collapsed": true }, @@ -349,8 +173,8 @@ "# Instantiate a Materials collection, register all Materials, and export to XML\n", "materials_file = openmc.Materials(materials.values())\n", "\n", - "# Set the location of the cross sections file\n", - "materials_file.cross_sections = './mgxs.h5'\n", + "# Set the location of the cross sections file to our pre-written set\n", + "materials_file.cross_sections = 'c5g7.h5'\n", "\n", "materials_file.export_to_xml()" ] @@ -366,78 +190,35 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ "# Create the surface used for each pin\n", - "pin_surf = openmc.ZCylinder(surface_id=1, x0=0, y0=0, R=0.54, name='pin_surf')\n", + "pin_surf = openmc.ZCylinder(x0=0, y0=0, R=0.54, name='pin_surf')\n", "\n", - "# Create the cells which will be used to represent each `pin` type.\n", + "# Create the cells which will be used to represent each pin type.\n", "cells = {}\n", - "cells['UO2'] = openmc.Cell(name='UO2')\n", - "cells['MOX 4.3%'] = openmc.Cell(name='MOX 4.3%')\n", - "cells['MOX 7.0%'] = openmc.Cell(name='MOX 7.0%')\n", - "cells['MOX 8.7%'] = openmc.Cell(name='MOX 8.7%')\n", - "cells['Fission Chamber'] = openmc.Cell(name='Fission Chamber')\n", - "cells['Guide Tube'] = openmc.Cell(name='Guide Tube')\n", - "cells['Reflector'] = openmc.Cell(name='Reflector')\n", - "cells['UO2 Moderator'] = openmc.Cell(name='UO2 Moderator')\n", - "cells['MOX 4.3% Moderator'] = openmc.Cell(name='MOX 4.3% Moderator')\n", - "cells['MOX 7.0% Moderator'] = openmc.Cell(name='MOX 7.0% Moderator')\n", - "cells['MOX 8.7% Moderator'] = openmc.Cell(name='MOX 8.7% Moderator')\n", - "cells['Fission Chamber Moderator'] = openmc.Cell(name='Fission Chamber Moderator')\n", - "cells['Guide Tube Moderator'] = openmc.Cell(name='Guide Tube Moderator')\n", - "\n", - "# Use surface half-spaces to define regions.\n", - "cells['UO2'].region = -pin_surf\n", - "cells['MOX 4.3%'].region = -pin_surf\n", - "cells['MOX 7.0%'].region = -pin_surf\n", - "cells['MOX 8.7%'].region = -pin_surf\n", - "cells['Fission Chamber'].region = -pin_surf\n", - "cells['Guide Tube'].region = -pin_surf\n", - "cells['UO2 Moderator'].region = +pin_surf\n", - "cells['MOX 4.3% Moderator'].region = +pin_surf\n", - "cells['MOX 7.0% Moderator'].region = +pin_surf\n", - "cells['MOX 8.7% Moderator'].region = +pin_surf\n", - "cells['Fission Chamber Moderator'].region = +pin_surf\n", - "cells['Guide Tube Moderator'].region = +pin_surf\n", - "\n", - "# Register Materials with Cells\n", - "cells['UO2'].fill = materials['UO2']\n", - "cells['MOX 4.3%'].fill = materials['MOX 4.3%']\n", - "cells['MOX 7.0%'].fill = materials['MOX 7.0%']\n", - "cells['MOX 8.7%'].fill = materials['MOX 8.7%']\n", - "cells['Fission Chamber'].fill = materials['Fission Chamber']\n", - "cells['Guide Tube'].fill = materials['Guide Tube']\n", - "cells['Reflector'].fill = materials['Water']\n", - "cells['UO2 Moderator'].fill = materials['Water']\n", - "cells['MOX 4.3% Moderator'].fill = materials['Water']\n", - "cells['MOX 7.0% Moderator'].fill = materials['Water']\n", - "cells['MOX 8.7% Moderator'].fill = materials['Water']\n", - "cells['Fission Chamber Moderator'].fill = materials['Water']\n", - "cells['Guide Tube Moderator'].fill = materials['Water']\n", - "\n", - "# Instantiate Universes\n", "universes = {}\n", - "universes['UO2'] = openmc.Universe(name='UO2')\n", - "universes['MOX 4.3%'] = openmc.Universe(name='MOX 4.3%')\n", - "universes['MOX 7.0%'] = openmc.Universe(name='MOX 7.0%')\n", - "universes['MOX 8.7%'] = openmc.Universe(name='MOX 8.7%')\n", - "universes['Fission Chamber'] = openmc.Universe(name='Fission Chamber')\n", - "universes['Guide Tube'] = openmc.Universe(name='Guide Tube')\n", - "universes['Reflector'] = openmc.Universe(name='Reflector')\n", - "\n", - "# Register Cells with Universes\n", - "universes['UO2'].add_cells([cells['UO2'], cells['UO2 Moderator']])\n", - "universes['MOX 4.3%'].add_cells([cells['MOX 4.3%'], cells['MOX 4.3% Moderator']])\n", - "universes['MOX 7.0%'].add_cells([cells['MOX 7.0%'], cells['MOX 7.0% Moderator']])\n", - "universes['MOX 8.7%'].add_cells([cells['MOX 8.7%'], cells['MOX 8.7% Moderator']])\n", - "universes['Fission Chamber'].add_cells([cells['Fission Chamber'], cells['Fission Chamber Moderator']])\n", - "universes['Guide Tube'].add_cells([cells['Guide Tube'], cells['Guide Tube Moderator']])\n", - "universes['Reflector'].add_cell(cells['Reflector'])\n" + "for material in materials.values():\n", + " # Create the cell for the material inside the cladding\n", + " cells[material.name] = openmc.Cell(name=material.name)\n", + " # Assign the half-spaces to the cell\n", + " cells[material.name].region = -pin_surf\n", + " # Register the material with this cell\n", + " cells[material.name].fill = material\n", + " \n", + " # Repeat the above for the material outside the cladding (i.e., the moderator)\n", + " cell_name = material.name + '_moderator'\n", + " cells[cell_name] = openmc.Cell(name=cell_name)\n", + " cells[cell_name].region = +pin_surf\n", + " cells[cell_name].fill = materials['water']\n", + " \n", + " # Finally add the two cells we just made to a Universe object\n", + " universes[material.name] = openmc.Universe(name=material.name)\n", + " universes[material.name].add_cells([cells[material.name], cells[cell_name]])" ] }, { @@ -451,7 +232,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": false }, @@ -464,9 +245,9 @@ "lattices['UO2 Assembly'].dimension = [17, 17]\n", "lattices['UO2 Assembly'].lower_left = [-10.71, -10.71]\n", "lattices['UO2 Assembly'].pitch = [1.26, 1.26]\n", - "u = universes['UO2']\n", - "g = universes['Guide Tube']\n", - "f = universes['Fission Chamber']\n", + "u = universes['uo2']\n", + "g = universes['guide_tube']\n", + "f = universes['fiss_chamber']\n", "lattices['UO2 Assembly'].universes = \\\n", " [[u, u, u, u, u, u, u, u, u, u, u, u, u, u, u, u, u],\n", " [u, u, u, u, u, u, u, u, u, u, u, u, u, u, u, u, u],\n", @@ -497,11 +278,11 @@ "lattices['MOX Assembly'].dimension = [17, 17]\n", "lattices['MOX Assembly'].lower_left = [-10.71, -10.71]\n", "lattices['MOX Assembly'].pitch = [1.26, 1.26]\n", - "m = universes['MOX 4.3%']\n", - "n = universes['MOX 7.0%']\n", - "o = universes['MOX 8.7%']\n", - "g = universes['Guide Tube']\n", - "f = universes['Fission Chamber']\n", + "m = universes['mox43']\n", + "n = universes['mox7']\n", + "o = universes['mox87']\n", + "g = universes['guide_tube']\n", + "f = universes['fiss_chamber']\n", "lattices['MOX Assembly'].universes = \\\n", " [[m, m, m, m, m, m, m, m, m, m, m, m, m, m, m, m, m],\n", " [m, n, n, n, n, n, n, n, n, n, n, n, n, n, n, n, m],\n", @@ -520,18 +301,19 @@ " [m, n, n, n, n, g, n, n, g, n, n, g, n, n, n, n, m],\n", " [m, n, n, n, n, n, n, n, n, n, n, n, n, n, n, n, m],\n", " [m, m, m, m, m, m, m, m, m, m, m, m, m, m, m, m, m]]\n", + " \n", "# Create a containing cell and universe\n", "cells['MOX Assembly'] = openmc.Cell(name='MOX Assembly')\n", "cells['MOX Assembly'].fill = lattices['MOX Assembly']\n", "universes['MOX Assembly'] = openmc.Universe(name='MOX Assembly')\n", "universes['MOX Assembly'].add_cell(cells['MOX Assembly'])\n", " \n", - "# Instantiate the Reflector Lattice\n", + "# Instantiate the reflector Lattice\n", "lattices['Reflector Assembly'] = openmc.RectLattice(name='Reflector Assembly')\n", "lattices['Reflector Assembly'].dimension = [1,1]\n", "lattices['Reflector Assembly'].lower_left = [-10.71, -10.71]\n", "lattices['Reflector Assembly'].pitch = [21.42, 21.42]\n", - "lattices['Reflector Assembly'].universes = [[universes['Reflector']]]\n", + "lattices['Reflector Assembly'].universes = [[universes['water']]]\n", "\n", "# Create a containing cell and universe\n", "cells['Reflector Assembly'] = openmc.Cell(name='Reflector Assembly')\n", @@ -546,13 +328,14 @@ "collapsed": true }, "source": [ - "Lets now create the core layout in a 3x3 lattice wher each lattice position is one of the assemblies we just defined.\n", - "Then we can create the final cell to contain the entire core" + "Let's now create the core layout in a 3x3 lattice where each lattice position is one of the assemblies we just defined.\n", + "\n", + "After that we can create the final cell to contain the entire core." ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": false }, @@ -591,21 +374,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Before we commit to the geometry, lets view it using the Python API's plotting capability" + "Before we commit to the geometry, we should view it using the Python API's plotting capability" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -621,12 +404,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "OK, it looks pretty good, lets go ahead and write the file" + "OK, it looks pretty good, let's go ahead and write the file" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -649,7 +432,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": true }, @@ -683,20 +466,22 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With the geometry and materials finished, we now just need to define simulation parameters for the `settings.xml` file. Note the use of the `energy_mode` attribute of our `settings_file` object. This is used to tell OpenMC that we intend to run in multi-group mode instead of the default continuous-energy mode. If we didn't specify this but our cross sections file was not a continuous-energy data set, then OpenMC would complain." + "With the geometry and materials finished, we now just need to define simulation parameters for the `settings.xml` file. Note the use of the `energy_mode` attribute of our `settings_file` object. This is used to tell OpenMC that we intend to run in multi-group mode instead of the default continuous-energy mode. If we didn't specify this but our cross sections file was not a continuous-energy data set, then OpenMC would complain.\n", + "\n", + "This will be a relatively coarse calculation with only 500,000 active histories. A benchmark-fidelity run would of course require many more!" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# OpenMC simulation parameters\n", - "batches = 1000\n", - "inactive = 100\n", + "batches = 150\n", + "inactive = 50\n", "particles = 5000\n", "\n", "# Instantiate a Settings object\n", @@ -705,10 +490,6 @@ "settings_file.inactive = inactive\n", "settings_file.particles = particles\n", "\n", - "# We dont need a tallies.out file, as we will be working with the StatePoint\n", - "# file instead, so tell OpenMC not to write the file.\n", - "settings_file.output = {'tallies': False}\n", - "\n", "# Tell OpenMC this is a multi-group problem\n", "settings_file.energy_mode = 'multi-group'\n", "\n", @@ -731,12 +512,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Lets go ahead and execute the simulation! You'll notice that the output for multi-group mode is exactly the same as for continuous-energy. The differences are all under the hood." + "Let's go ahead and execute the simulation! You'll notice that the output for multi-group mode is exactly the same as for continuous-energy. The differences are all under the hood." ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -774,8 +555,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:29:09\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-06 20:46:35\n", " OpenMP Threads | 8\n", "\n", " Reading settings XML file...\n", @@ -796,32 +577,32 @@ "\n", " ====================> K EIGENVALUE SIMULATION <====================\n", "\n", - " Creating state point statepoint.1000.h5...\n", + " Creating state point statepoint.150.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.4368E-01 seconds\n", - " Reading cross sections = 4.5424E-02 seconds\n", - " Total time in simulation = 1.2489E+02 seconds\n", - " Time in transport only = 1.2426E+02 seconds\n", - " Time in inactive batches = 8.0909E+00 seconds\n", - " Time in active batches = 1.1680E+02 seconds\n", - " Time synchronizing fission bank = 2.0736E-01 seconds\n", - " Sampling source sites = 1.5095E-01 seconds\n", - " SEND/RECV source sites = 5.4904E-02 seconds\n", - " Time accumulating tallies = 7.7863E-03 seconds\n", - " Total time for finalization = 1.6174E-05 seconds\n", - " Total time elapsed = 1.2507E+02 seconds\n", - " Calculation Rate (inactive) = 61797.5 neutrons/second\n", - " Calculation Rate (active) = 38527.2 neutrons/second\n", + " Total time for initialization = 9.7265E-02 seconds\n", + " Reading cross sections = 2.7582E-02 seconds\n", + " Total time in simulation = 7.7964E+00 seconds\n", + " Time in transport only = 7.7309E+00 seconds\n", + " Time in inactive batches = 1.7644E+00 seconds\n", + " Time in active batches = 6.0320E+00 seconds\n", + " Time synchronizing fission bank = 1.4392E-02 seconds\n", + " Sampling source sites = 1.0188E-02 seconds\n", + " SEND/RECV source sites = 4.0621E-03 seconds\n", + " Time accumulating tallies = 4.4249E-04 seconds\n", + " Total time for finalization = 1.6782E-02 seconds\n", + " Total time elapsed = 7.9263E+00 seconds\n", + " Calculation Rate (inactive) = 1.41694E+05 neutrons/second\n", + " Calculation Rate (active) = 82891.0 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.18592 +/- 0.00054\n", - " k-effective (Track-length) = 1.18604 +/- 0.00072\n", - " k-effective (Absorption) = 1.18621 +/- 0.00035\n", - " Combined k-effective = 1.18618 +/- 0.00034\n", - " Leakage Fraction = 0.00183 +/- 0.00002\n", + " k-effective (Collision) = 1.18880 +/- 0.00179\n", + " k-effective (Track-length) = 1.18853 +/- 0.00244\n", + " k-effective (Absorption) = 1.18601 +/- 0.00111\n", + " Combined k-effective = 1.18628 +/- 0.00111\n", + " Leakage Fraction = 0.00175 +/- 0.00006\n", "\n" ] }, @@ -831,7 +612,7 @@ "0" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -847,21 +628,21 @@ "source": [ "# Results Visualization\n", "\n", - "Now that we have run the simulation, lets look at the fission rate and flux tallies that we tallied." + "Now that we have run the simulation, let's look at the fission rate and flux tallies that we tallied." ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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SQgykidshzKwL+CrwRirblh80swXu/utBp97i7pfVqlczLiHEUHprfFTnVGCZ\nu//O3XcBNwPnDXd4MlxCiIH0xSrW8qjUW13U7zF3kLZpwIp+r1cWssH8uZk9Yma3mtn0akMc1q2i\nmS0HtlCxvXvcffZw9AkhOoD6bhXXV/ndp4KKfdDrHwHfcfedZvbfgBuB1+c6bcYa1+vcPVdX+Hl6\nSbuEc3m9o5zj12f6CfSFudCjoOCcrvfHTezTwYFcbv2/C3RFQcZBhW0AvyLQ9dG4TTO3Q/j/bqD/\nKOf81wNdudrpka6fxE3CPPEZ/PFAVxQwnfv8A0NhmVwCyc+sGdsYmrsdYiXQfwZ1JLBqQHfuG/q9\nvA64uppS3SoKIYbSPK/ig8BMMzvGzMYCFwAL+p9gZlP7vXwbsLSa0uHOuBz4qZk58H/cff4w9Qkh\n2k0T93G5+x4zuwz4D6ALuMHdHzOzvwUWufsC4H+Y2duKXp8BLq6md7iG6wx3X2VmhwELzey/3P2e\n/icUi3WVBbvxRw2zOyHEiNPkRILufjtw+yDZVf2efwL4RD06h3Wr6O6rir/rgNuouD4HnzPf3We7\n+2y603UNhRAdRJM3oI4EDRsuMzvArLIMaWYHAG8CHm3WwIQQbaTDDZe5D/ZM1tjQ7Fgqsyyo3HL+\ni7vn6gtjB8x2TkzkFc45U3saGFz0hka6Ggmyzo2rNh9rbfoaCdiNyE3/o1TM0Xs5JaMrOpZbmIi8\nmlH/ueuP2uSuP9LXSMB2vdeSJfP7HJ9wOe6cje9dlPNFVsW6Zzs9Uf7vQay3h9qxDarhNS53/x1w\nUhPHIoToBJQdQghROkqQHUKGSwgxkL0okaAQooToVlEIUToa89m1jNYarl7SHpdMcdEw7uy6uIld\nEhyIvEo5r2IjG/Ea8SpFsYfB2PxHsSp7dQP9N9N7GeAL42P2xuBAvWm4obH1meg7kPuFRGOLvrMZ\nY2C2LdNR1P/+9bcZJShWUQhROmS4hBClQ2tcQohBdL5bUYZLCDGIJiadHyFkuIQQg+j8HagyXEKI\nQWjGNZAoz09uy8HytDibujfAvxHoOifTKBhbQ9sRMoQpioNtAtk+oq0C4zNtos+gkW0SwbfKXplp\nE4zN7w105VItB2OLUi0DWJRxKfPd9GAZKEq3XMm3GdHImtKEBtrUggyXEKJ0OFqcF0KUDK1xCSFK\nh24VhRClQzMuIUTp0IxrIBb0mEuDHHl1Ggh+tfcF5+e8bUHws12UaVNvGmbA3hociK4z54mNUidn\nishmA90ym2U1AAAEr0lEQVRT5N7/6J91rk3gCbRX1Hd+VleusHudAdNQpVhrkkYWvHMzn5S+vQ30\nMRjNuIQQpUMhP0KI0qFbRSFEKdGtohCiVGjGJYQoHZ1vuIaVSNDMzjaz35jZMjO7slmDEkK0kz6v\nYueWsm54xmVmXcBXgTdScaY/aGYL3P3XYaODgfMT8pxrPzqW28IQHYuuthFduTHn9NVL9N3I9RFd\nZ+7TPjKQR7nYG3nPctQb5J3bQhPl/M99ZtH7nPttRtcZbdXYk8sR3x3Ic969lL5mJDUe3V7FU4Fl\nRUVrzOxm4DwgNlxCiBLQ+beKwzFc04AV/V6vBE4b3nCEEO1ndG9ATe0bHpJwyMzmAnMBmHTUMLoT\nQrSGzp9xDeeGeCXQP4jiSGDV4JPcfb67z3b32ewfZWsTQnQOo3hxHngQmGlmxwBPARcAf9GUUQkh\n2kjnL86b58rrVmtsdi7wj0AXcIO7f7bK+U8DTxYvp5CvRzzSqH/1Pxr7P9rdh3VrY2b/ThyqP5j1\n7n72cPprhGEZrmF1bLbI3We3pXP1r/738f7LjipZCyFKhwyXEKJ0tNNwzW9j3+pf/e/r/Zeatq1x\nCSFEo+hWUQhROmS4hBCloy2Gq93pcMxsuZktMbPFZraoBf3dYGbrzOzRfrLJZrbQzB4v/h7c4v7n\nmdlTxXuwuNiTNxJ9TzezO81sqZk9ZmYfLuQtuf5M/626/vFm9gsz+1XR/6cL+TFm9kBx/beY2diR\n6H/U4u4tfVDZrPoEcCwwFvgVcGKLx7AcmNLC/l4DnAI82k/2BeDK4vmVwNUt7n8e8PEWXPtU4JTi\n+STgt8CJrbr+TP+tun4DJhbPu4EHgNOB7wIXFPJrgQ+06vs4Gh7tmHE9lw7H3XcBfelwRi3ufg/w\nzCDxecCNxfMbgbe3uP+W4O6r3f3h4vkWYCmVzCItuf5M/y3BK/Rl6OouHg68Hri1kI/o5z8aaYfh\nSqXDadkXqcCBn5rZQ0X2inZwuLuvhsqPCzisDWO4zMweKW4lR+xWtQ8zmwGcTGXW0fLrH9Q/tOj6\nzazLzBYD64CFVO44Nrp7X5RyO34DpaYdhqumdDgjzBnufgpwDvBBM3tNi/vvBL4OHAfMAlYDXxzJ\nzsxsIvA94CPuvnkk+6qx/5Zdv7v3uvssKhlUTgVenDptpPofjbTDcNWUDmckcfdVxd91wG1Uvkyt\nZq2ZTQUo/q5rZefuvrb4Qe0FrmME3wMz66ZiNG5y9+8X4pZdf6r/Vl5/H+6+EbiLyhpXj5n1ZWdp\n+W+g7LTDcD2XDqfwpFwALGhV52Z2gJlN6nsOvAl4NN9qRFgAzCmezwF+2MrO+4xGwTsYoffAzAy4\nHljq7tf0O9SS64/6b+H1H2pmPcXzCcAbqKyz3cnzFRha/vmXnnZ4BIBzqXh3ngD+qsV9H0vFk/kr\n4LFW9A98h8rtyG4qM85LgUOAO4DHi7+TW9z/t4ElwCNUjMjUEer7VVRugx4BFhePc1t1/Zn+W3X9\nLwN+WfTzKHBVv+/hL4BlwL8C40b6eziaHgr5EUKUDu2cF0KUDhkuIUTpkOESQpQOGS4hROmQ4RJC\nlA4ZLiFE6ZDhEkKUjv8PdU5Q4o3YuO4AAAAASUVORK5CYII=\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, diff --git a/docs/source/examples/mg-mode-part-ii.ipynb b/docs/source/examples/mg-mode-part-ii.ipynb index e6a88dec19..d9a96f12fc 100644 --- a/docs/source/examples/mg-mode-part-ii.ipynb +++ b/docs/source/examples/mg-mode-part-ii.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The previous Notebook in this series used multi-group mode to perform a calculation with previously defined cross sections. However, there are times where you would like multi-group data is only a given in some circumstances; in others one would need to calculate cross sections for the specific application (or at least verify the use of cross sections from another application). \n", + "The previous Notebook in this series used multi-group mode to perform a calculation with previously defined cross sections. However, in many circumstances the multi-group data is not given and one must instead generate the cross sections for the specific application (or at least verify the use of cross sections from another application). \n", "\n", "This Notebook illustrates the use of the openmc.mgxs.Library class specifically for the calculation of MGXS to be used in OpenMC's multi-group mode. This example notebook is therefore very similar to the MGXS Part III notebook, except OpenMC is used as the multi-group solver instead of OpenMOC.\n", "\n", @@ -31,7 +31,6 @@ }, "outputs": [], "source": [ - "from IPython.display import Image\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import os\n", @@ -45,37 +44,12 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "\n", - "First we need to define materials that will be used in the problem. Before defining a material, we must create nuclides that are used in the material." + "We will begin by creating three materials for the fuel, water, and cladding of the fuel pins." ] }, { "cell_type": "code", "execution_count": 2, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "# Instantiate some Nuclides\n", - "h1 = openmc.Nuclide('H1')\n", - "b10 = openmc.Nuclide('B10')\n", - "o16 = openmc.Nuclide('O16')\n", - "u235 = openmc.Nuclide('U235')\n", - "u238 = openmc.Nuclide('U238')\n", - "zr90 = openmc.Nuclide('Zr90')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "With the nuclides we defined, we will now create three materials for the fuel, water, and cladding of the fuel pins." - ] - }, - { - "cell_type": "code", - "execution_count": 3, "metadata": { "collapsed": false }, @@ -84,21 +58,20 @@ "# 1.6% enriched fuel\n", "fuel = openmc.Material(name='1.6% Fuel')\n", "fuel.set_density('g/cm3', 10.31341)\n", - "fuel.add_nuclide(u235, 3.7503e-4)\n", - "fuel.add_nuclide(u238, 2.2625e-2)\n", - "fuel.add_nuclide(o16, 4.6007e-2)\n", + "fuel.add_element('U', 1., enrichment=1.6)\n", + "fuel.add_element('O', 2.)\n", "\n", "# zircaloy\n", "zircaloy = openmc.Material(name='Zircaloy')\n", "zircaloy.set_density('g/cm3', 6.55)\n", - "zircaloy.add_nuclide(zr90, 7.2758e-3)\n", + "zircaloy.add_element('Zr', 1.)\n", "\n", "# borated water\n", "water = openmc.Material(name='Borated Water')\n", "water.set_density('g/cm3', 0.740582)\n", - "water.add_nuclide(h1, 4.9457e-2)\n", - "water.add_nuclide(o16, 2.4732e-2)\n", - "water.add_nuclide(b10, 8.0042e-6)\n" + "water.add_element('H', 4.9457e-2)\n", + "water.add_element('O', 2.4732e-2)\n", + "water.add_element('B', 8.0042e-6)\n" ] }, { @@ -110,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": true }, @@ -132,13 +105,15 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# Create cylinders for the fuel and clad\n", + "# The x0 and y0 parameters (0. and 0.) are the default values for an\n", + "# openmc.ZCylinder object. We could therefore leave them out to no effect\n", "fuel_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.39218)\n", "clad_outer_radius = openmc.ZCylinder(x0=0.0, y0=0.0, R=0.45720)\n", "\n", @@ -160,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "collapsed": false }, @@ -197,7 +172,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { "collapsed": false }, @@ -234,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": false }, @@ -255,7 +230,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": true }, @@ -287,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -314,16 +289,16 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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L1Ma3EZPPJjbt6dr0aGrxA3pCz1zxL8UYSEgLkCqmk9jE9jeRiJx8x7VstNtM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\nWAIxDEOMJRDDMMT8PzL4N8qRZ8wAAAAAAElFTkSuQmCC\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -345,7 +320,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -367,7 +342,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": true }, @@ -376,7 +351,7 @@ "# OpenMC simulation parameters\n", "batches = 1000\n", "inactive = 100\n", - "particles = 1000\n", + "particles = 2000\n", "\n", "# Instantiate a Settings object\n", "settings_file = openmc.Settings()\n", @@ -407,7 +382,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -427,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": true }, @@ -449,7 +424,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "collapsed": true }, @@ -464,14 +439,14 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now we must specify the type of domain over which we would like the `Library` to compute multi-group cross sections. The domain type corresponds to the type of tally filter to be used in the tallies created to compute multi-group cross sections. At the present time, the `Library` supports \"material\" \"cell\", \"universe\", and \"mesh\" domain types. In this simple example, we wish to compute multi-group cross sections only for each material and therefore will use a \"material\" domain type.\n", + "Now we must specify the type of domain over which we would like the `Library` to compute multi-group cross sections. The domain type corresponds to the type of tally filter to be used in the tallies created to compute multi-group cross sections. At the present time, the `Library` supports \"material\", \"cell\", \"universe\", and \"mesh\" domain types. In this simple example, we wish to compute multi-group cross sections only for each material and therefore will use a \"material\" domain type.\n", "\n", - "**Note:** By default, the `Library` class will instantiate `MGXS` objects for each and every domain (material, cell, universe, or mesh) in the geometry of interest. However, one may specify a subset of these domains to the `Library.domains` property." + "**NOTE:** By default, the `Library` class will instantiate `MGXS` objects for each and every domain (material, cell, universe, or mesh) in the geometry of interest. However, one may specify a subset of these domains to the `Library.domains` property." ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -495,7 +470,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -514,7 +489,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -544,7 +519,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -563,7 +538,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "collapsed": false }, @@ -584,7 +559,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { "collapsed": true }, @@ -604,7 +579,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": true }, @@ -643,7 +618,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false }, @@ -681,8 +656,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:45:17\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-06 21:25:02\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -691,10 +666,10 @@ "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02507 +/- 0.00114\n", - " k-effective (Track-length) = 1.02333 +/- 0.00131\n", - " k-effective (Absorption) = 1.02416 +/- 0.00113\n", - " Combined k-effective = 1.02430 +/- 0.00091\n", + " k-effective (Collision) = 1.16427 +/- 0.00088\n", + " k-effective (Track-length) = 1.16499 +/- 0.00102\n", + " k-effective (Absorption) = 1.16506 +/- 0.00079\n", + " Combined k-effective = 1.16481 +/- 0.00067\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -705,7 +680,7 @@ "0" ] }, - "execution_count": 24, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -724,17 +699,17 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "# Move the StatePoint File\n", - "ce_spfile = './ce_statepoint.h5'\n", + "# Move the statepoint File\n", + "ce_spfile = './statepoint_ce.h5'\n", "os.rename('statepoint.' + str(batches) + '.h5', ce_spfile)\n", "# Move the Summary file\n", - "ce_sumfile = './ce_summary.h5'\n", + "ce_sumfile = './summary_ce.h5'\n", "os.rename('summary.h5', ce_sumfile)" ] }, @@ -749,7 +724,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "collapsed": false }, @@ -772,7 +747,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "collapsed": false }, @@ -806,7 +781,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "collapsed": false }, @@ -828,7 +803,7 @@ "# Create a MGXS File which can then be written to disk\n", "mgxs_file = mgxs_lib.create_mg_library(xs_type='macro', xsdata_names=['fuel', 'zircaloy', 'water'])\n", "\n", - "# Write the file to disk using the default filename of `mgxs.h5`\n", + "# Write the file to disk using the default filename of \"mgxs.h5\"\n", "mgxs_file.export_to_hdf5()" ] }, @@ -845,7 +820,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -874,7 +849,7 @@ "materials_file = openmc.Materials((fuel_mg, zircaloy_mg, water_mg))\n", "\n", "# Set the location of the cross sections file\n", - "materials_file.cross_sections = './mgxs.h5'\n", + "materials_file.cross_sections = 'mgxs.h5'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -897,7 +872,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": true }, @@ -919,7 +894,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": true }, @@ -948,16 +923,16 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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bYjVOqg4A9OuAPdrz7rWHcGj/Dvz17Xlc8swMNm636nuiBH+4NyY5HuoVkXMc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\nkp3lfPzDOqYv28R3K0q4ffP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nL7deVymkujaSEkdoXhJHg+64nq/qgb2fTBO8VFX9CWcMx/mqeh4wEvhLfMOK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\npZNlqvpX4LD4hhUdaxw3xpj485I4Kt1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LgfPzF1LmJJ0InDhs2LBCh+KcS6K9SxqennIvZVWVpApgJzPbA9gd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\ntPx/RfHQqmw1MBwAAAAASUVORK5CYII=\n", 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ShwU/7OSh923tCJPa7OZuouVpPQgROVdE/uo+kjoGAhI3WZ8Xgw5rxfWndOGV\nGasYO9faI0zyRKpiikmCsCRTp3jp5voo8Ctgofv4lbvNuG47swf9Ojbhd299w6J1dbbWzSRZqt27\nYzUi2ySPlxLE2cAZqvqSqr4EDHa3GVdOlo/nftaXRvWzuXb0TLbsLkl2SMYcJNGD3KxKK/15XXI0\nsFtr8ut1UlDLRnmMuLyIzbtL+L/XZlNaXpHskEwdE7GKyeNxwu1npYK6xUuCeAT4WkRGichoYBbw\ncHzDSk992hfy54t688WKrdzz3gKblsAkVMReTF4n67O/W+PyMt33GBGZAvTH+ZJyu6quj3dg6eq8\no9qyeP0unpuyjLaF9blpYLdkh2QMABUeb/zhVhK13FG3eGmk/gmwV1XfU9V3gWIROT/+oYWNKSW6\nuYby2x/14Pyj2vCXD5bwxszVyQ7H1BGxqmKyWiTj56WK6R5VrbwTq+p24J74hRRZKnVzDcbnE/58\nUR9O7t6cO9+ex6RFG5IdkqkDIt3XG9YLX2EgbobxWtIwmc9Lggi2T8SqqbouN9vH8z/vx+FtGvF/\nr81m2tLNyQ7J1FGnHNoCgIuK2oXdz+dmiApVtu/dz8PjF1FWrbOFpY66xUuCmCkij4lIVxHpIiKP\n4zRUmwgK6mUz8sr+dG5ewNWjvuLT7zYlOySTwUJVMeX4nHf8CSDS5ysU7h+3kBFTlzNhQeY2Ny7b\ntDvZIaQ8LwliOM4cTP8G3gSKgZviGVQmadagHq8PO47OzQu4ZvRMPvnWkoRJLP+3/kg1R/4Eoiil\n5c7O5dVarKPp4TRy2krP+ybD7/87L9khpDwvczHtUdU7VLUIOAZ4RFVt+tIoNC3IZcyw4+jWogHD\nRs+0KTlMSvIXMFRj09V13trU7ETiF+wS127fx8vTV9o4JpeXXkyvi0gjESkAFgBLROS38Q8tszQp\nyOX1YcdyVPtCho/5muemLLP+5iahIg1y89JInUl/scs2Vf2eu3l3CSc+Opk/vruASYs2Jimq1OKl\niqmXqu4EzgfGAx2Ay+MaVYYqzM/l5WuOYUifNvxpwmJ+/8589pfZNxUTX16/iAj+RmqQCO0VmWBz\ntSlxHpv4beXzGcu3ADB92RYmzF+X0LhSiZcEkSMiOTgJ4l1VLSWzvkgkVF5OFk/89ChuHNCV17/4\nnp+OmM7a7fuSHZapAyLliQNVTFpnSrdTljglhT0lZfx39lqG9m/Pyd2bM32ZkyAuf/ELbnh1Ngt/\nOHgSzn/Mye8/AAAaLElEQVR+upznpixLaLyJ5iVB/ANYCRQAU0WkI2BTltaCzyfcPrgnz1zWl+82\n7OacJz9l8mIbK2Fi65pRX/G3D5d43r+ykboOjaS+dvRMPl+2mf/NX8++0nIu6NuO47o0Y8mGXazf\nUUyZ20j/4cKqvbl27CvlwfcX8acJizN6sTAvjdRPqmpbVT1bHauAgQmILaRUH0nt1Tm9D+G9m0+k\ndaM8rh41k9venMuOvaXJDstkiEmLN/LU5KWei/sHurlqxC6xmaDXIY3o0CyfG1+dzcPjF9GzdUOK\nOjbh+K7NABj1+crKfb9YvrXKZ5du3FX5fPiYrxMSbzJ4aaRu7I6DmOk+/oZTmkiaVB9JHY0uLRrw\nzk0nctPArvz367Wc/vgnTJi/rs4U8U3iRPybqmykDt1gnUmzuY4ZdhzP/7wf3Vs2oDA/h4d+ciQ+\nn3Bk28bUz8nixc+WA3BMp6Z8v3UvxaXlqCrvf7OOC5+bDkDP1g2ZuHADq7bsYd/+zCtJeKliegnY\nBVziPnYCI+MZVF2Tl5PFb8/sybs3nUizglxueHU2Q0fM4Js125MdmskA/nu8x/yAqgY8r36wGAaW\nZI3zczi0VUPeuvEEJt86gH4dmwDO+i6HHdKQ0nKlaUEu/Ts3Ye32ffT8wwSe/2Q5f3x3fuUxbh/c\nE4BT/zKFs5/8NCnXEU9eEkRXVb1HVZe7j/uALvEOrC46om1jxg4/iQfOP4KlG3dz7tPTGD7ma1ul\nztSK5yomOdCLKVR7RLiZXtNJpHmpurdsCEDfDoW0Lcyv3D5hwXr27C+rfN2tZYPK5ys276EiU35B\nLi9zKu0TkZNU9TMAETkRsG43cZKT5ePy4zpy3lFteH7KMkZ/vpKxc39gYI8WXH9qV47t3LROdEE0\nsRfp1hXYi4kMr2Ia0LNl2Pc7NXdq0S/o247G9XMqt6/dtpfi0gpaNKzHFcd1pGWjelU+t3FXCa0b\n58U+4CTxkiBuAF4WEX+F/zbgF/ELyQA0ysvhd4N7ct0pXXhl+ipGfr6SoSNm0LVFAUP7d+AnfdvS\nvEG9yAcydYZUfusPfhP3WsVUpQRRbZ90/4I8/LRunNP7EDo3D9+MetWJnejVphGndG+OKtxxVk/+\n+emKyrETIy7vx9Edmhz0uS9XbmX+2h3k52bx69MPjcs1JFLYBCEiPqCHqvYRkUYA7qA5kyCF+bkM\nH9Sda0/uwrhvfuBfX63mofGLeHTCYo7t3JSzjmjNmYe3pmWjzPnWYmrGFzBVRiD/jb+47EAj6luz\n1nDbm3NZ/MBg8nKynP0C5mLyBZYmAqR7FUrHZgX0bN0o4n55OVmc6s6CKwI3nNqVktIKHv/IGUzX\nvVXDoJ/7ZUCPpoE9WtKnfWHQ/dJF2DYIVa0Abnaf77TkkDz1c7O4uKg9/7nxBCb+5hRuPLUrG3YW\n84d3F3DsI5MY8tRnPDJ+EZ98u4m9AXWkpu4InK47kP/V7uIDfxePu6OGA0cT+5NCRcWBUdWZ1pmu\nNgmuXZP6lc8bBGnDOLZzUwBOc6uvMqGTiZcqpokichvObK6Vk5eo6tbQHzHx1L1VQ247swe3ndmD\n7zbsYsL89Xy6dDMvTVvBP6YuJydL6HVII3q3K+TIdo3p3a4x3Vo0IDvLS58Ek678bQihZmDdUxLp\ni8OBBFPZHlFtj8Dkk47Jo1+ng6uFvGrrJogWDatW7U749cl8uWIrZx95CBMXbuDCvu3o+8BElm5M\n/+nEvSSIq92fgVN8K9aTKSV0b9WQ7q0aMnxQd/buL2Pmym18vmwLc1dv552v1/LKjFWAs4BR52YF\ndG1ZQNcWDejaogGdmhfQpjCP5gX18Pms4TvdZUUYCb0rQoIInM1VQpRGAnNPeYIzxBvXH88l/5ge\n9eca5WWzs7iM7x46i5xafEnq3a4x5x/VhptP615le8/WjSqrrS49pgMAXVsUMGfNDt6atYZz+7Qh\nNzs9v5xJOg/IKioq0pkzZyY7jJRVUaGs2LKHeWt2sHDdTpZv2s2yTXv4fuveKt8yc7N8tG6cR5vC\nPNo0rk/LRnk0LcihaUE9mhXk0jTgkZ+blXq9qGaOhHlvJTuKpNtZXMrCdTtpWC+bw9s0ZsYKZz6h\nRnk57CwupSA3myPbOn1NZn+/jf3lFRzdvpB62VlVth3ephGbdpWwcVcJnZoV0DqgfWtfaTlz3aqT\nI9s2rvWU3g3qZbM7YsnGUdSxCTNXbYv6HEe3L6RclfycxC2EuXTT7srqu/ZN6lfpKpsK5Orxs9wl\nHMKK+BsTkZuA19y1qBGRJsClqvps7cOspc3fwchzkh1FyvIBXd3H+f6NzaCiqVJcVk5JaQUlZRXs\nL6ugpKyc/ZsqKFlXQWl5RZWqhX3AWvchQJZPDjxEDnrt8wk+EXxClefi3yZVt4k4314F9znudg5s\nD2vVZ87PjifF7peXhkJVC/m7phaXlqNoyN9nlk+g3Kmi8vIVoCwGDdYFUSSImvInwESqn3PgnNv3\nldI2TduqvaTUYar6jP+Fqm4TkWFA0hKEiAwBhvRpl1pZOV34RMjPySY/J/j7ilJeoZRVKKXlFZSV\nuz8rlLJy571ydX9WOKuPFZdWVG6Lx6L3lUkjWALxHc7knFOZsH0wWT4fWT6cnwLZPh8+n/PzoMSW\n5fzM9jlJrcpPd7t//8j7BJy38vwHPpsV6iFVz5Gd5aOgXhYN6+WQl+PzXFqbvHgDkxdv5NWV39On\nVSHvXnUiQ+94H4C+rQuZ/b3zrf/NgcfTv1NThj86mbXb9/HZRQNp18T5f3Tvs9P4+vvtPH3S0Xyx\nfCuvzFjFff0P5xcndKo8z5oNuxj6+FQARpzSj+teqd3qw38e0JvfvfWNp33n/exHDL33w6jPsfKq\nxH+JnL9gPde7v5vsMmH2pWfQKC/Ef7hkuNrb35WXBOETEVG3LkpEsoDcWoRWa6o6FhhbVFQ0jKve\nT2YoGUlw/jCygZp0nq2oUErcUklJWYVbUnGeF5eWH3ivtILisnLKyp1kVFahlPsTUWXyqahMQuUV\nB5KU837FgeeqdCmvmrgCH3vLyihXKK+ooLzC/zMg2VX7bFm1z8fi23K0snxCg3rZNKiXTcM852dh\nfi4tGtY78Gjg/Lx6VOiq1vIKpX+nJizduJt731vAy1cfE3Q/f8+cXcVlVQfNBQj8NcTim7+/ysur\nPu0Lmbs69XsHdW1xYIR1WYXy2XebOfvIQ5IYUc14SRAfAG+IyPM4pdcbgAlxjcqkNZ9PqJ+bRf3c\nxBft46mi4uAkUuH/qVVf+xNRWUUFFf6f6pbAQiQxJzFWsLuknN3FZewuKWV3cRm7Ssqcn8VlrNm2\nlzmrt7Flz/6QjdFzV29nzJffV74uLVdaNMzhrxf34cZXZzPwr1PY6XZ59a89DdDCHXi5YvOekAPl\nAkdS7yqufYIInKoiEhGhXZP6nhJE28L6SV1npWMzp1R2eJtGrNm2jw8WrM/YBHE7cD1wI86Xyw+B\nf8YzKGNSkc8n+BByUiDvlZVXsHXPfjbuKmHT7hK+Xb+Lb9bsYOp3m8j2CXe+Pa9y3z37y8j2+Rh0\nWCvG/fIk/vLBEiYudNYfuWb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2fltO6u6Nzufh7s8Bz7X2uLpVJSLNMTMO2b0nh+zek3eWbeKPL3/M715ayD2v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\nwxIRkXQVyxXH94DOwHeBgwi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WbdjGbj06JSjStpHoK44KM7sWOA94PHzeIi37ubn7NHefWFpamupQRCTNFeXn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\nvcbdn3L384HRwCLgRTP7bpt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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -990,21 +965,21 @@ "fig = openmc.plot_xs(fuel, ['total'])\n", "\n", "# We will now add in the corresponding multi-group data and show the result\n", - "openmc.plot_xs(fuel_mg, ['total'], plot_CE=False, mg_cross_sections='./mgxs.h5', axis=fig.axes[0])\n", + "openmc.plot_xs(fuel_mg, ['total'], plot_CE=False, mg_cross_sections='mgxs.h5', axis=fig.axes[0])\n", "fig.axes[0].legend().set_visible(False)\n", "plt.show()\n", "plt.close()\n", "\n", "# Then repeat for the zircaloy data\n", "fig = openmc.plot_xs(zircaloy, ['total'])\n", - "openmc.plot_xs(zircaloy_mg, ['total'], plot_CE=False, mg_cross_sections='./mgxs.h5', axis=fig.axes[0])\n", + "openmc.plot_xs(zircaloy_mg, ['total'], plot_CE=False, mg_cross_sections='mgxs.h5', axis=fig.axes[0])\n", "fig.axes[0].legend().set_visible(False)\n", "plt.show()\n", "plt.close()\n", "\n", "# And finally repeat for the water data\n", "fig = openmc.plot_xs(water, ['total'])\n", - "openmc.plot_xs(water_mg, ['total'], plot_CE=False, mg_cross_sections='./mgxs.h5', axis=fig.axes[0])\n", + "openmc.plot_xs(water_mg, ['total'], plot_CE=False, mg_cross_sections='mgxs.h5', axis=fig.axes[0])\n", "fig.axes[0].legend().set_visible(False)\n", "plt.show()\n", "plt.close()" @@ -1019,7 +994,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false, "scrolled": true @@ -1058,8 +1033,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:46:38\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-06 21:35:03\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -1068,10 +1043,10 @@ "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02649 +/- 0.00111\n", - " k-effective (Track-length) = 1.02562 +/- 0.00124\n", - " k-effective (Absorption) = 1.02597 +/- 0.00073\n", - " Combined k-effective = 1.02586 +/- 0.00067\n", + " k-effective (Collision) = 1.16401 +/- 0.00087\n", + " k-effective (Track-length) = 1.16395 +/- 0.00101\n", + " k-effective (Absorption) = 1.16454 +/- 0.00046\n", + " Combined k-effective = 1.16450 +/- 0.00045\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -1082,7 +1057,7 @@ "0" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -1104,17 +1079,17 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [], "source": [ "# Move the StatePoint File\n", - "mg_spfile = './mg_statepoint.h5'\n", + "mg_spfile = './statepoint_mg.h5'\n", "os.rename('statepoint.' + str(batches) + '.h5', mg_spfile)\n", "# Move the Summary file\n", - "mg_sumfile = './mg_summary.h5'\n", + "mg_sumfile = './summary_mg.h5'\n", "os.rename('summary.h5', mg_sumfile)\n", "\n", "# Rename and then load the last statepoint file and keff value\n", @@ -1137,7 +1112,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "metadata": { "collapsed": false }, @@ -1155,7 +1130,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": { "collapsed": false }, @@ -1164,9 +1139,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Continuous-Energy keff = 1.024296\n", - "Multi-Group keff = 1.025863\n", - "bias [pcm]: -156.7\n" + "Continuous-Energy keff = 1.164814\n", + "Multi-Group keff = 1.164501\n", + "bias [pcm]: 31.4\n" ] } ], @@ -1203,7 +1178,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": { "collapsed": false }, @@ -1229,7 +1204,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": { "collapsed": false }, @@ -1255,7 +1230,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "metadata": { "collapsed": false }, @@ -1263,18 +1238,18 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 39, + "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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7V5wd2sx6m9mmjZ+BAwhvdIVoX+TbogikdOe8AfgbsKOZzTOzU4HLgU3JbnFn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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1333,7 +1308,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 39, "metadata": { "collapsed": true }, @@ -1355,7 +1330,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "metadata": { "collapsed": false }, @@ -1393,8 +1368,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:47:21\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-06 21:40:33\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -1403,10 +1378,10 @@ "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02479 +/- 0.00120\n", - " k-effective (Track-length) = 1.02486 +/- 0.00130\n", - " k-effective (Absorption) = 1.02338 +/- 0.00077\n", - " Combined k-effective = 1.02362 +/- 0.00071\n", + " k-effective (Collision) = 1.16341 +/- 0.00089\n", + " k-effective (Track-length) = 1.16347 +/- 0.00102\n", + " k-effective (Absorption) = 1.16321 +/- 0.00048\n", + " Combined k-effective = 1.16323 +/- 0.00048\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -1417,7 +1392,7 @@ "0" ] }, - "execution_count": 41, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -1436,7 +1411,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": { "collapsed": false }, @@ -1445,17 +1420,17 @@ "name": "stdout", "output_type": "stream", "text": [ - "P3 bias [pcm]: -156.7\n", - "P0 bias [pcm]: 68.0\n" + "P3 bias [pcm]: 31.4\n", + "P0 bias [pcm]: 158.4\n" ] } ], "source": [ - "# Move the StatePoint File\n", - "mgp0_spfile = './mg_p0_statepoint.h5'\n", + "# Move the statepoint File\n", + "mgp0_spfile = './statepoint_mg_p0.h5'\n", "os.rename('statepoint.' + str(batches) + '.h5', mgp0_spfile)\n", "# Move the Summary file\n", - "mgp0_sumfile = './mg_p0_summary.h5'\n", + "mgp0_sumfile = './summary_mg_p0.h5'\n", "os.rename('summary.h5', mgp0_sumfile)\n", "\n", "# Load the last statepoint file and keff value\n", @@ -1482,7 +1457,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 42, "metadata": { "collapsed": false }, @@ -1503,7 +1478,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 43, "metadata": { "collapsed": true }, @@ -1516,7 +1491,7 @@ " elif xsdata.name == 'fuel':\n", " mgxs_file.xsdatas[i] = xsdata.convert_scatter_format('tabular', 2)\n", " \n", - "mgxs_file.export_to_hdf5('./mgxs.h5')" + "mgxs_file.export_to_hdf5('mgxs.h5')" ] }, { @@ -1528,7 +1503,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 44, "metadata": { "collapsed": false }, @@ -1566,8 +1541,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:48:04\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-06 21:45:21\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -1576,10 +1551,10 @@ "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02423 +/- 0.00115\n", - " k-effective (Track-length) = 1.02549 +/- 0.00127\n", - " k-effective (Absorption) = 1.02409 +/- 0.00074\n", - " Combined k-effective = 1.02447 +/- 0.00068\n", + " k-effective (Collision) = 1.16474 +/- 0.00091\n", + " k-effective (Track-length) = 1.16503 +/- 0.00105\n", + " k-effective (Absorption) = 1.16458 +/- 0.00047\n", + " Combined k-effective = 1.16462 +/- 0.00047\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -1590,7 +1565,7 @@ "0" ] }, - "execution_count": 45, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -1627,7 +1602,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 45, "metadata": { "collapsed": false }, @@ -1636,8 +1611,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "P3 bias [pcm]: -156.7\n", - "Mixed Scattering bias [pcm]: -17.3\n" + "P3 bias [pcm]: 31.4\n", + "Mixed Scattering bias [pcm]: 19.6\n" ] } ], @@ -1656,7 +1631,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Our tests in this section showed the flexibility of data formatting within OpenMC's multi-group mode: every material can be represented with its own format with the approximations that make the most sense. Now, as you'll see above, the runtimes from our P3, P0, and mixed cases are not significantly different and therefore this might not be a useful strategy for multi-group Monte Carlo. However, this capability provides a useful benchmark for the accuracy hit one may expect due to these scattering approximations before implementing this generality in a deterministic solver where the runtime savings are more significant." + "Our tests in this section showed the flexibility of data formatting within OpenMC's multi-group mode: every material can be represented with its own format with the approximations that make the most sense. Now, as you'll see above, the runtimes from our P3, P0, and mixed cases are not significantly different and therefore this might not be a useful strategy for multi-group Monte Carlo. However, this capability provides a useful benchmark for the accuracy hit one may expect due to these scattering approximations before implementing this generality in a deterministic solver where the runtime savings are more significant.\n", + "\n", + "**NOTE**: The biases obtained above with P3, P0, and mixed representations do not necessarily reflect the inherent accuracies of each mode. These cases were no run with a sufficient number of histories to truly discern the accuracy benefits of scattering representations." ] } ], diff --git a/docs/source/examples/mg-mode-part-iii.ipynb b/docs/source/examples/mg-mode-part-iii.ipynb index 66f90f8e9c..f3c242576b 100644 --- a/docs/source/examples/mg-mode-part-iii.ipynb +++ b/docs/source/examples/mg-mode-part-iii.ipynb @@ -30,7 +30,6 @@ "source": [ "import os\n", "\n", - "from IPython.display import Image\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", @@ -43,7 +42,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We will be running a rodded 8x8 assembly with Gadolinia fuel pins. Lets create all the elemental data we would need for this case." + "We will be running a rodded 8x8 assembly with Gadolinia fuel pins. Let's create all the elemental data we would need for this case." ] }, { @@ -144,9 +143,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now let's move on to the geometry. The first step is to define some constants which will be used to set our dimensions and then we can start creating surfaces for the problem, the 8x8 lattice, the rods and the control blade.\n", + "Now let's move on to the geometry. The first step is to define some constants which will be used to set our dimensions and then we can start creating the surfaces and regions for the problem, the 8x8 lattice, the rods and the control blade.\n", "\n", - "Before proceeding lets discuss some simplifications made to the problem geometry:\n", + "Before proceeding let's discuss some simplifications made to the problem geometry:\n", "- To enable the use of an equal-width mesh for running the multi-group calculations, the intra-assembly gap was increased to the same size as the pitch of the 8x8 fuel lattice\n", "- The can is neglected\n", "- The pin-in-water geometry for the control blade is ignored and instead the blade is a solid block of B4C\n", @@ -168,6 +167,7 @@ "Np = 8\n", "pin_pitch = 1.6256\n", "length = float(Np + 2) * pin_pitch\n", + "assembly_width = length - 2. * pin_pitch\n", "rod_thick = 0.47752 / 2. + 0.14224\n", "rod_span = 7. * pin_pitch\n", "\n", @@ -179,17 +179,16 @@ "surfaces['Global y-'] = openmc.YPlane(y0=0., boundary_type='reflective')\n", "surfaces['Global y+'] = openmc.YPlane(y0=length, boundary_type='reflective')\n", "\n", - "# Create planes to surround the 8x8 assembly\n", + "# Create cylinders for the fuel and clad\n", + "surfaces['Fuel Radius'] = openmc.ZCylinder(R=fuel_rad)\n", + "surfaces['Clad Radius'] = openmc.ZCylinder(R=clad_rad)\n", + "\n", "surfaces['Assembly x-'] = openmc.XPlane(x0=pin_pitch)\n", "surfaces['Assembly x+'] = openmc.XPlane(x0=length - pin_pitch)\n", "surfaces['Assembly y-'] = openmc.YPlane(y0=pin_pitch)\n", "surfaces['Assembly y+'] = openmc.YPlane(y0=length - pin_pitch)\n", "\n", - "# Create cylinders for the fuel and clad\n", - "surfaces['Fuel Radius'] = openmc.ZCylinder(R=fuel_rad)\n", - "surfaces['Clad Radius'] = openmc.ZCylinder(R=clad_rad)\n", - "\n", - "# Set surfaces for Control Rods\n", + "# Set surfaces for the control blades\n", "surfaces['Top Blade y-'] = openmc.YPlane(y0=length - rod_thick)\n", "surfaces['Top Blade x-'] = openmc.XPlane(x0=pin_pitch)\n", "surfaces['Top Blade x+'] = openmc.XPlane(x0=rod_span)\n", @@ -202,7 +201,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "With the surfaces defined, we can now construct half-spaces with these surfaces before we use those to create cells" + "With the surfaces defined, we can now construct regions with these surfaces before we use those to create cells" ] }, { @@ -213,35 +212,35 @@ }, "outputs": [], "source": [ - "# Set half-spaces for geometry building\n", - "half_spaces = {}\n", - "half_spaces['Global'] = \\\n", + "# Set regions for geometry building\n", + "regions = {}\n", + "regions['Global'] = \\\n", " (+surfaces['Global x-'] & -surfaces['Global x+'] &\n", " +surfaces['Global y-'] & -surfaces['Global y+'])\n", - "half_spaces['Assembly'] = \\\n", + "regions['Assembly'] = \\\n", " (+surfaces['Assembly x-'] & -surfaces['Assembly x+'] &\n", " +surfaces['Assembly y-'] & -surfaces['Assembly y+'])\n", - "half_spaces['Fuel'] = -surfaces['Fuel Radius']\n", - "half_spaces['Clad'] = +surfaces['Fuel Radius'] & -surfaces['Clad Radius']\n", - "half_spaces['Pin Moderator'] = +surfaces['Clad Radius']\n", - "half_spaces['Top Blade'] = \\\n", + "regions['Fuel'] = -surfaces['Fuel Radius']\n", + "regions['Clad'] = +surfaces['Fuel Radius'] & -surfaces['Clad Radius']\n", + "regions['Water'] = +surfaces['Clad Radius']\n", + "regions['Top Blade'] = \\\n", " (+surfaces['Top Blade y-'] & -surfaces['Global y+']) & \\\n", " (+surfaces['Top Blade x-'] & -surfaces['Top Blade x+'])\n", - "half_spaces['Top Steel'] = \\\n", + "regions['Top Steel'] = \\\n", " (+surfaces['Global x-'] & -surfaces['Top Blade x-']) & \\\n", " (+surfaces['Top Blade y-'] & -surfaces['Global y+'])\n", - "half_spaces['Left Blade'] = \\\n", + "regions['Left Blade'] = \\\n", " (+surfaces['Left Blade y-'] & -surfaces['Left Blade y+']) & \\\n", " (+surfaces['Global x-'] & -surfaces['Left Blade x+'])\n", - "half_spaces['Left Steel'] = \\\n", + "regions['Left Steel'] = \\\n", " (+surfaces['Left Blade y+'] & -surfaces['Top Blade y-']) & \\\n", " (+surfaces['Global x-'] & -surfaces['Left Blade x+'])\n", - "half_spaces['Corner Blade'] = \\\n", - " half_spaces['Left Steel'] | half_spaces['Top Steel']\n", - "half_spaces['Water Fill'] = \\\n", - " half_spaces['Global'] & ~half_spaces['Assembly'] & \\\n", - " ~half_spaces['Top Blade'] & ~half_spaces['Left Blade'] &\\\n", - " ~half_spaces['Corner Blade']" + "regions['Corner Blade'] = \\\n", + " regions['Left Steel'] | regions['Top Steel']\n", + "regions['Water Fill'] = \\\n", + " regions['Global'] & ~regions['Assembly'] & \\\n", + " ~regions['Top Blade'] & ~regions['Left Blade'] &\\\n", + " ~regions['Corner Blade']" ] }, { @@ -267,15 +266,17 @@ " universes[name] = openmc.Universe(name=name)\n", " cells[name] = openmc.Cell(name=name)\n", " cells[name].fill = mat\n", - " cells[name].region = half_spaces['Fuel']\n", + " cells[name].region = regions['Fuel']\n", " universes[name].add_cell(cells[name])\n", + " \n", " cells[name + ' Clad'] = openmc.Cell(name=name + ' Clad')\n", " cells[name + ' Clad'].fill = materials['Zirc2']\n", - " cells[name + ' Clad'].region = half_spaces['Clad']\n", + " cells[name + ' Clad'].region = regions['Clad']\n", " universes[name].add_cell(cells[name + ' Clad'])\n", + " \n", " cells[name + ' Water'] = openmc.Cell(name=name + ' Water')\n", " cells[name + ' Water'].fill = materials['Water']\n", - " cells[name + ' Water'].region = half_spaces['Pin Moderator']\n", + " cells[name + ' Water'].region = regions['Water']\n", " universes[name].add_cell(cells[name + ' Water'])\n", "\n", "universes['Hole'] = openmc.Universe(name='Hole')\n", @@ -322,7 +323,7 @@ "\n", "cells['Assembly'] = openmc.Cell(name='Assembly')\n", "cells['Assembly'].fill = universes['Assembly']\n", - "cells['Assembly'].region = half_spaces['Assembly']" + "cells['Assembly'].region = regions['Assembly']" ] }, { @@ -343,22 +344,22 @@ "# The top portion of the blade, poisoned with B4C\n", "cells['Top Blade'] = openmc.Cell(name='Top Blade')\n", "cells['Top Blade'].fill = materials['B4C']\n", - "cells['Top Blade'].region = half_spaces['Top Blade']\n", + "cells['Top Blade'].region = regions['Top Blade']\n", "\n", "# The left portion of the blade, poisoned with B4C\n", "cells['Left Blade'] = openmc.Cell(name='Left Blade')\n", "cells['Left Blade'].fill = materials['B4C']\n", - "cells['Left Blade'].region = half_spaces['Left Blade']\n", + "cells['Left Blade'].region = regions['Left Blade']\n", "\n", "# The top-left corner portion of the blade, with no poison\n", "cells['Corner Blade'] = openmc.Cell(name='Corner Blade')\n", "cells['Corner Blade'].fill = materials['Steel']\n", - "cells['Corner Blade'].region = half_spaces['Corner Blade']\n", + "cells['Corner Blade'].region = regions['Corner Blade']\n", "\n", "# Water surrounding all other cells and our assembly\n", "cells['Water Fill'] = openmc.Cell(name='Water Fill')\n", "cells['Water Fill'].fill = materials['Water']\n", - "cells['Water Fill'].region = half_spaces['Water Fill']" + "cells['Water Fill'].region = regions['Water Fill']" ] }, { @@ -403,7 +404,7 @@ "data": { "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -587,9 +588,9 @@ "source": [ "Now we will set the scattering treatment that we wish to use.\n", "\n", - "In the `mg-mode-part-ii` notebook, the cross sections were generated with a typical P3 scattering expansion in mind. Now, however, we will use a more advanced technique: OpenMC will directly provide us a histogram of the change-in-angle (i.e., $\\mu$) distribution.\n", + "In the [mg-mode-part-ii](mg-mode-part-ii.html) notebook, the cross sections were generated with a typical P3 scattering expansion in mind. Now, however, we will use a more advanced technique: OpenMC will directly provide us a histogram of the change-in-angle (i.e., $\\mu$) distribution.\n", "\n", - "Where as in the `mg-mode-part-ii` notebook, all that was required was to set the `legendre_order` attribute of `mgxs_lib`, here we have only slightly more work: we have to tell the Library that we want to use a histogram distribution (as it is not the default), and then tell it the number of bins.\n", + "Where as in the [mg-mode-part-ii](mg-mode-part-ii.html) notebook, all that was required was to set the `legendre_order` attribute of `mgxs_lib`, here we have only slightly more work: we have to tell the Library that we want to use a histogram distribution (as it is not the default), and then tell it the number of bins.\n", "\n", "For this problem we will use 11 bins." ] @@ -604,7 +605,7 @@ "source": [ "# Set the scattering format to histogram and then define the number of bins\n", "\n", - "# Avoid a warning that corrections dont make sense with histogram data\n", + "# Avoid a warning that corrections don't make sense with histogram data\n", "iso_mgxs_lib.correction = None\n", "# Set the histogram data\n", "iso_mgxs_lib.scatter_format = 'histogram'\n", @@ -617,7 +618,7 @@ "source": [ "Ok, we made our isotropic library with histogram-scattering!\n", "\n", - "Now why dont we go ahead and create a library to do the same, but with angle-dependent MGXS. That is, we will avoid making the isotropic flux weighting approximation and instead just store a cross section for every polar and azimuthal angle pair.\n", + "Now why don't we go ahead and create a library to do the same, but with angle-dependent MGXS. That is, we will avoid making the isotropic flux weighting approximation and instead just store a cross section for every polar and azimuthal angle pair.\n", "\n", "To do this with the Python API and OpenMC, all we have to do is set the number of polar and azimuthal bins. Here we only need to set the number of bins, the API will convert all of angular space into equal-width bins for us.\n", "\n", @@ -634,7 +635,7 @@ }, "outputs": [], "source": [ - "# Lets repeat all of the above for an angular MGXS library so we can gather\n", + "# Let's repeat all of the above for an angular MGXS library so we can gather\n", "# that in the same continuous-energy calculation\n", "angle_mgxs_lib = openmc.mgxs.Library(geometry)\n", "angle_mgxs_lib.energy_groups = groups\n", @@ -655,7 +656,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now that our libraries have been setup, lets make sure they contain the types of cross sections which meet the needs of OpenMC's multi-group solver. Note that this step is done automatically when writing the Multi-Group Library file later in the process (as part of the `mgxs_lib.write_mg_library()`), but it is a good practice to also run this before spending all the time running OpenMC to generate the cross sections." + "Now that our libraries have been setup, let's make sure they contain the types of cross sections which meet the needs of OpenMC's multi-group solver. Note that this step is done automatically when writing the Multi-Group Library file later in the process (as part of the `mgxs_lib.write_mg_library()`), but it is a good practice to also run this before spending all the time running OpenMC to generate the cross sections." ] }, { @@ -802,8 +803,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:14:47\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-07 07:26:33\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -852,10 +853,10 @@ "outputs": [], "source": [ "# Move the StatePoint File\n", - "ce_spfile = './ce_statepoint.h5'\n", + "ce_spfile = './statepoint_ce.h5'\n", "os.rename('statepoint.' + str(batches) + '.h5', ce_spfile)\n", "# Move the Summary file\n", - "ce_sumfile = './ce_summary.h5'\n", + "ce_sumfile = './summary_ce.h5'\n", "os.rename('summary.h5', ce_sumfile)" ] }, @@ -970,10 +971,10 @@ "iso_mgxs_file, materials_file, geometry_file = iso_mgxs_lib.create_mg_mode()\n", "\n", "# Tell the materials file what we want to call the multi-group library\n", - "materials_file.cross_sections = './mgxs.h5'\n", + "materials_file.cross_sections = 'mgxs.h5'\n", "\n", "# Write our newly-created files to disk\n", - "iso_mgxs_file.export_to_hdf5('./mgxs.h5')\n", + "iso_mgxs_file.export_to_hdf5('mgxs.h5')\n", "materials_file.export_to_xml()\n", "geometry_file.export_to_xml()" ] @@ -1005,7 +1006,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Lets clear up the tallies file so it doesn't include all the extra tallies for re-generating a multi-group library" + "Let's clear up the tallies file so it doesn't include all the extra tallies for re-generating a multi-group library" ] }, { @@ -1030,7 +1031,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Before running the calculation let's look at our meshed model. It might not be interesting, but lets take a look anyways." + "Before running the calculation let's look at our meshed model. It might not be interesting, but let's take a look anyways." ] }, { @@ -1042,9 +1043,9 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1106,8 +1107,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:18:19\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-07 07:28:23\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -1144,7 +1145,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Before we go the angle-dependent case, lets save the StatePoint and Summary files so they don't get over-written" + "Before we go the angle-dependent case, let's save the StatePoint and Summary files so they don't get over-written" ] }, { @@ -1156,10 +1157,10 @@ "outputs": [], "source": [ "# Move the StatePoint File\n", - "iso_mg_spfile = './iso_mg_statepoint.h5'\n", + "iso_mg_spfile = './statepoint_mg_iso.h5'\n", "os.rename('statepoint.' + str(batches) + '.h5', iso_mg_spfile)\n", "# Move the Summary file\n", - "iso_mg_sumfile = './iso_mg_summary.h5'\n", + "iso_mg_sumfile = './summary_mg_iso.h5'\n", "os.rename('summary.h5', iso_mg_sumfile)" ] }, @@ -1169,7 +1170,7 @@ "source": [ "# Angle-Dependent Multi-Group OpenMC Calculation\n", "\n", - "Lets now run the calculation with the angle-dependent multi-group cross sections. This process will be the exact same as above, except this time we will use the angle-dependent Library as our starting point.\n", + "Let's now run the calculation with the angle-dependent multi-group cross sections. This process will be the exact same as above, except this time we will use the angle-dependent Library as our starting point.\n", "\n", "We do not need to re-write the materials, geometry, or tallies file to disk since they are the same as for the isotropic case." ] @@ -1195,7 +1196,7 @@ } ], "source": [ - "# Lets repeat for the angle-dependent case\n", + "# Let's repeat for the angle-dependent case\n", "angle_mgxs_lib.load_from_statepoint(sp)\n", "angle_mgxs_file, materials_file, geometry_file = angle_mgxs_lib.create_mg_mode()\n", "angle_mgxs_file.export_to_hdf5()" @@ -1248,8 +1249,8 @@ " Copyright | 2011-2017 Massachusetts Institute of Technology\n", " License | http://openmc.readthedocs.io/en/latest/license.html\n", " Version | 0.8.0\n", - " Git SHA1 | e10a92487255a233e03533b2570e1b5c010b8506\n", - " Date/Time | 2017-03-05 13:18:55\n", + " Git SHA1 | 6d1115aec2619254c38e95ac2e29b5eef1c809e9\n", + " Date/Time | 2017-03-07 07:28:39\n", " OpenMP Threads | 8\n", "\n", "\n", @@ -1338,7 +1339,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Lets compare the eigenvalues in units of pcm" + "Let's compare the eigenvalues in units of pcm" ] }, { @@ -1390,7 +1391,7 @@ "data": { "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1419,8 +1420,7 @@ "\n", " fig = plt.subplot(1, len(titles), i + 1)\n", " # Plot only the fueled regions\n", - " plt.imshow(fiss_rates[-1][1:-1, 1:-1], cmap='jet',\n", - " origin='lower')\n", + " plt.imshow(fiss_rates[-1][1:-1, 1:-1], cmap='jet', origin='lower')\n", " plt.title(title + '\\nFission Rates')" ] }, @@ -1432,7 +1432,49 @@ "source": [ "With this colormap, dark blue is the lowest power and dark red is the highest power.\n", "\n", - "We see general agreement between the fission rate distributions, but it is evident that the continuous-energy and angle-dependent cases have less of a gradient near the rods than does the isotropic case (see the top left of each grid). This sort of effect is likely the culprit behind the large eigenvalue differences." + "We see general agreement between the fission rate distributions, but it looks like there may be less of a gradient near the rods in the continuous-energy and angle-dependent MGXS cases than in the isotropic MGXS case. \n", + "\n", + "To better see the differences, let's plot ratios of the fission powers for our two multi-group cases compared to the continuous-energy case t" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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AgKLR8AIAAKBoNLwAAAAoGg0vAAAAikbDCwAAgKKN7sioKyQt6sjIQzO56gCN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\nAABJRU5ErkJggg==\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Calculate and plot the ratios of MG to CE for each of the 2 MG cases\n", + "ratios = []\n", + "fig = plt.figure(figsize=(12, 6))\n", + "for i, (case, title) in enumerate(zip(sp_files[1:], titles[1:])):\n", + " # Get our ratio relative to the CE (in fiss_ratios[0])\n", + " ratios.append(np.divide(fiss_rates[i + 1], fiss_rates[0]))\n", + " \n", + " fig = plt.subplot(1, len(titles[1:]), i + 1)\n", + " # Plot only the fueled regions\n", + " plt.imshow(ratios[-1][1:-1, 1:-1], cmap='jet', origin='lower',\n", + " vmin = 0.9, vmax = 1.1)\n", + " plt.title(title + '\\nFission Rates Relative\\nto Continuous-Energy')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With this ratio its clear that the errors are significantly worse in the isotropic case. These errors are conveniently located right where the most anisotropy is espected: by the control blades and by the gadolina-bearing pins!" ] } ],