diff --git a/depletion.ipynb b/depletion.ipynb index 3159db7..09feeda 100644 --- a/depletion.ipynb +++ b/depletion.ipynb @@ -125,7 +125,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 6, @@ -282,23 +282,14 @@ "cell_type": "code", "execution_count": 11, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/pshriwise/.pyenv/versions/3.9.1/lib/python3.9/site-packages/openmc/deplete/coupled_operator.py:546: FutureWarning: The Operator(...) class has been renamed and will be removed in a future version of OpenMC. Use CoupledOperator(...) instead.\n", - " warn(\n" - ] - } - ], + "outputs": [], "source": [ "model = openmc.Model(geometry=geometry, settings=settings)\n", - "operator = openmc.deplete.Operator(model, \"./chain_simple.xml\")" + "operator = openmc.deplete.CoupledOperator(model, \"./chain_simple.xml\")" ] }, { - "cell_type": "markdown", + "cell_type": "raw", "metadata": {}, "source": [ "We will then simulate our fuel pin operating at linear power of 174 W/cm, or 174 W given a unit height for our problem." @@ -390,40 +381,39 @@ " License | https://docs.openmc.org/en/latest/license.html\n", " Version | 0.13.1\n", " Git SHA1 | 33bc948f4b855c037975f16d16091fe4ecd12de3\n", - " Date/Time | 2022-10-03 22:39:53\n", + " Date/Time | 2022-10-05 19:02:05\n", " OpenMP Threads | 2\n", "\n", " Reading settings XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", " Reading geometry XML file...\n", - " Reading U234 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/U234.h5\n", - " Reading U235 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/U235.h5\n", - " Reading U238 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/U238.h5\n", - " Reading O16 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/O16.h5\n", - " Reading O17 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/O17.h5\n", - " Reading U236 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/U236.h5\n", - " Reading Zr90 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Zr90.h5\n", - " Reading Zr91 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Zr91.h5\n", - " Reading Zr92 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Zr92.h5\n", - " Reading Zr94 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Zr94.h5\n", - " Reading Zr96 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Zr96.h5\n", - " Reading H1 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/H1.h5\n", - " Reading H2 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/H2.h5\n", - " Reading c_H_in_H2O from\n", - " /home/pshriwise/data/xs/openmc/endfb71_hdf5/c_H_in_H2O.h5\n", + " Reading U234 from /home/pshriwise/data/xs/openmc/nndc_hdf5/U234.h5\n", + " Reading U235 from /home/pshriwise/data/xs/openmc/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/pshriwise/data/xs/openmc/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/pshriwise/data/xs/openmc/nndc_hdf5/O16.h5\n", + " Reading O17 from /home/pshriwise/data/xs/openmc/nndc_hdf5/O17.h5\n", + " Reading U236 from /home/pshriwise/data/xs/openmc/nndc_hdf5/U236.h5\n", + " Reading Zr90 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Zr90.h5\n", + " Reading Zr91 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Zr91.h5\n", + " Reading Zr92 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Zr92.h5\n", + " Reading Zr94 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Zr94.h5\n", + " Reading Zr96 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Zr96.h5\n", + " Reading H1 from /home/pshriwise/data/xs/openmc/nndc_hdf5/H1.h5\n", + " Reading H2 from /home/pshriwise/data/xs/openmc/nndc_hdf5/H2.h5\n", + " Reading c_H_in_H2O from /home/pshriwise/data/xs/openmc/nndc_hdf5/c_H_in_H2O.h5\n", " Minimum neutron data temperature: 294 K\n", " Maximum neutron data temperature: 294 K\n", " Preparing distributed cell instances...\n", " Reading plot XML file...\n", " Writing summary.h5 file...\n", "[openmc.deplete] t=0.0 s, dt=2592000 s, source=174\n", - " Reading I135 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/I135.h5\n", - " Reading Xe135 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Xe135.h5\n", - " Reading Xe136 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Xe136.h5\n", - " Reading Cs135 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Cs135.h5\n", - " Reading Gd157 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Gd157.h5\n", - " Reading Gd156 from /home/pshriwise/data/xs/openmc/endfb71_hdf5/Gd156.h5\n", + " Reading I135 from /home/pshriwise/data/xs/openmc/nndc_hdf5/I135.h5\n", + " Reading Xe135 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Xe135.h5\n", + " Reading Xe136 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Xe136.h5\n", + " Reading Cs135 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Cs135.h5\n", + " Reading Gd157 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Gd157.h5\n", + " Reading Gd156 from /home/pshriwise/data/xs/openmc/nndc_hdf5/Gd156.h5\n", " Maximum neutron transport energy: 20000000 eV for U235\n", " Initializing source particles...\n", "\n", @@ -431,82 +421,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.53790\n", - " 2/1 1.46903\n", - " 3/1 1.36829\n", - " 4/1 1.45600\n", - " 5/1 1.38633\n", - " 6/1 1.51748\n", - " 7/1 1.35208\n", - " 8/1 1.55790\n", - " 9/1 1.58144\n", - " 10/1 1.42114\n", - " 11/1 1.42185\n", - " 12/1 1.46298 1.44242 +/- 0.02057\n", - " 13/1 1.46751 1.45078 +/- 0.01453\n", - " 14/1 1.53137 1.47093 +/- 0.02261\n", - " 15/1 1.38387 1.45352 +/- 0.02470\n", - " 16/1 1.51570 1.46388 +/- 0.02267\n", - " 17/1 1.55438 1.47681 +/- 0.02312\n", - " 18/1 1.44013 1.47222 +/- 0.02054\n", - " 19/1 1.53542 1.47925 +/- 0.01942\n", - " 20/1 1.36717 1.46804 +/- 0.02068\n", - " 21/1 1.41912 1.46359 +/- 0.01922\n", - " 22/1 1.52130 1.46840 +/- 0.01820\n", - " 23/1 1.43972 1.46619 +/- 0.01688\n", - " 24/1 1.41279 1.46238 +/- 0.01609\n", - " 25/1 1.45216 1.46170 +/- 0.01499\n", - " 26/1 1.53062 1.46601 +/- 0.01467\n", - " 27/1 1.43426 1.46414 +/- 0.01391\n", - " 28/1 1.39795 1.46046 +/- 0.01362\n", - " 29/1 1.38172 1.45632 +/- 0.01353\n", - " 30/1 1.49705 1.45835 +/- 0.01300\n", - " 31/1 1.42760 1.45689 +/- 0.01245\n", - " 32/1 1.51946 1.45973 +/- 0.01221\n", - " 33/1 1.43375 1.45860 +/- 0.01172\n", - " 34/1 1.41749 1.45689 +/- 0.01135\n", - " 35/1 1.50162 1.45868 +/- 0.01103\n", - " 36/1 1.42764 1.45749 +/- 0.01067\n", - " 37/1 1.44483 1.45702 +/- 0.01027\n", - " 38/1 1.57292 1.46116 +/- 0.01073\n", - " 39/1 1.46150 1.46117 +/- 0.01035\n", - " 40/1 1.54874 1.46409 +/- 0.01042\n", - " 41/1 1.41823 1.46261 +/- 0.01019\n", - " 42/1 1.36083 1.45943 +/- 0.01036\n", - " 43/1 1.47536 1.45991 +/- 0.01006\n", - " 44/1 1.48400 1.46062 +/- 0.00978\n", - " 45/1 1.43449 1.45987 +/- 0.00953\n", - " 46/1 1.47191 1.46021 +/- 0.00926\n", - " 47/1 1.43326 1.45948 +/- 0.00904\n", - " 48/1 1.53823 1.46155 +/- 0.00904\n", - " 49/1 1.51592 1.46294 +/- 0.00891\n", - " 50/1 1.44665 1.46254 +/- 0.00870\n", + " 1/1 1.49721\n", + " 2/1 1.49226\n", + " 3/1 1.44838\n", + " 4/1 1.47163\n", + " 5/1 1.41429\n", + " 6/1 1.42100\n", + " 7/1 1.43656\n", + " 8/1 1.41211\n", + " 9/1 1.45570\n", + " 10/1 1.33919\n", + " 11/1 1.47822\n", + " 12/1 1.47425 1.47624 +/- 0.00198\n", + " 13/1 1.39919 1.45056 +/- 0.02571\n", + " 14/1 1.35785 1.42738 +/- 0.02946\n", + " 15/1 1.38972 1.41985 +/- 0.02403\n", + " 16/1 1.47812 1.42956 +/- 0.02189\n", + " 17/1 1.50905 1.44092 +/- 0.02171\n", + " 18/1 1.48299 1.44618 +/- 0.01952\n", + " 19/1 1.49089 1.45114 +/- 0.01792\n", + " 20/1 1.50543 1.45657 +/- 0.01692\n", + " 21/1 1.41183 1.45251 +/- 0.01584\n", + " 22/1 1.49487 1.45604 +/- 0.01488\n", + " 23/1 1.45853 1.45623 +/- 0.01369\n", + " 24/1 1.45628 1.45623 +/- 0.01268\n", + " 25/1 1.37824 1.45103 +/- 0.01290\n", + " 26/1 1.40298 1.44803 +/- 0.01243\n", + " 27/1 1.48608 1.45027 +/- 0.01189\n", + " 28/1 1.46773 1.45124 +/- 0.01125\n", + " 29/1 1.46127 1.45177 +/- 0.01066\n", + " 30/1 1.38587 1.44847 +/- 0.01063\n", + " 31/1 1.42115 1.44717 +/- 0.01020\n", + " 32/1 1.45934 1.44772 +/- 0.00974\n", + " 33/1 1.40481 1.44586 +/- 0.00949\n", + " 34/1 1.47602 1.44711 +/- 0.00917\n", + " 35/1 1.47601 1.44827 +/- 0.00887\n", + " 36/1 1.44354 1.44809 +/- 0.00853\n", + " 37/1 1.54954 1.45185 +/- 0.00902\n", + " 38/1 1.46876 1.45245 +/- 0.00872\n", + " 39/1 1.51863 1.45473 +/- 0.00872\n", + " 40/1 1.51529 1.45675 +/- 0.00866\n", + " 41/1 1.39841 1.45487 +/- 0.00858\n", + " 42/1 1.58314 1.45888 +/- 0.00923\n", + " 43/1 1.51678 1.46063 +/- 0.00911\n", + " 44/1 1.44328 1.46012 +/- 0.00886\n", + " 45/1 1.42208 1.45903 +/- 0.00867\n", + " 46/1 1.50118 1.46020 +/- 0.00850\n", + " 47/1 1.50796 1.46150 +/- 0.00837\n", + " 48/1 1.44889 1.46116 +/- 0.00816\n", + " 49/1 1.48715 1.46183 +/- 0.00797\n", + " 50/1 1.49559 1.46267 +/- 0.00782\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 1.7021e+00 seconds\n", - " Reading cross sections = 1.6923e+00 seconds\n", - " Total time in simulation = 1.4132e+01 seconds\n", - " Time in transport only = 1.4123e+01 seconds\n", - " Time in inactive batches = 2.4396e+00 seconds\n", - " Time in active batches = 1.1692e+01 seconds\n", - " Time synchronizing fission bank = 4.0944e-03 seconds\n", - " Sampling source sites = 3.9258e-03 seconds\n", - " SEND/RECV source sites = 1.4190e-04 seconds\n", - " Time accumulating tallies = 2.1257e-04 seconds\n", - " Time writing statepoints = 1.4112e-03 seconds\n", - " Total time for finalization = 3.4840e-05 seconds\n", - " Total time elapsed = 1.5859e+01 seconds\n", - " Calculation Rate (inactive) = 4098.98 particles/second\n", - " Calculation Rate (active) = 3421.07 particles/second\n", + " Total time for initialization = 1.1968e+00 seconds\n", + " Reading cross sections = 1.1906e+00 seconds\n", + " Total time in simulation = 1.3040e+01 seconds\n", + " Time in transport only = 1.3031e+01 seconds\n", + " Time in inactive batches = 2.2501e+00 seconds\n", + " Time in active batches = 1.0790e+01 seconds\n", + " Time synchronizing fission bank = 4.3167e-03 seconds\n", + " Sampling source sites = 3.9236e-03 seconds\n", + " SEND/RECV source sites = 3.6606e-04 seconds\n", + " Time accumulating tallies = 2.4592e-04 seconds\n", + " Time writing statepoints = 1.4237e-03 seconds\n", + " Total time for finalization = 5.2430e-05 seconds\n", + " Total time elapsed = 1.4251e+01 seconds\n", + " Calculation Rate (inactive) = 4444.21 particles/second\n", + " Calculation Rate (active) = 3707.27 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.46314 +/- 0.00636\n", - " k-effective (Track-length) = 1.46254 +/- 0.00870\n", - " k-effective (Absorption) = 1.46104 +/- 0.00528\n", - " Combined k-effective = 1.46184 +/- 0.00460\n", + " k-effective (Collision) = 1.46857 +/- 0.00652\n", + " k-effective (Track-length) = 1.46267 +/- 0.00782\n", + " k-effective (Absorption) = 1.46527 +/- 0.00455\n", + " Combined k-effective = 1.46478 +/- 0.00392\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n0.h5...\n", @@ -518,82 +508,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.40447\n", - " 2/1 1.46409\n", - " 3/1 1.41697\n", - " 4/1 1.47293\n", - " 5/1 1.40942\n", - " 6/1 1.33075\n", - " 7/1 1.51129\n", - " 8/1 1.42074\n", - " 9/1 1.42390\n", - " 10/1 1.45595\n", - " 11/1 1.44417\n", - " 12/1 1.53237 1.48827 +/- 0.04410\n", - " 13/1 1.50886 1.49513 +/- 0.02637\n", - " 14/1 1.47570 1.49027 +/- 0.01927\n", - " 15/1 1.37653 1.46753 +/- 0.02721\n", - " 16/1 1.32482 1.44374 +/- 0.03255\n", - " 17/1 1.43044 1.44184 +/- 0.02757\n", - " 18/1 1.40452 1.43718 +/- 0.02433\n", - " 19/1 1.57279 1.45224 +/- 0.02622\n", - " 20/1 1.50655 1.45768 +/- 0.02407\n", - " 21/1 1.45460 1.45740 +/- 0.02178\n", - " 22/1 1.44881 1.45668 +/- 0.01989\n", - " 23/1 1.46728 1.45750 +/- 0.01832\n", - " 24/1 1.40401 1.45368 +/- 0.01738\n", - " 25/1 1.47119 1.45484 +/- 0.01622\n", - " 26/1 1.37773 1.45002 +/- 0.01592\n", - " 27/1 1.49799 1.45285 +/- 0.01522\n", - " 28/1 1.39252 1.44949 +/- 0.01474\n", - " 29/1 1.40978 1.44740 +/- 0.01409\n", - " 30/1 1.38517 1.44429 +/- 0.01373\n", - " 31/1 1.42478 1.44336 +/- 0.01309\n", - " 32/1 1.43802 1.44312 +/- 0.01248\n", - " 33/1 1.41992 1.44211 +/- 0.01197\n", - " 34/1 1.50261 1.44463 +/- 0.01174\n", - " 35/1 1.46153 1.44531 +/- 0.01128\n", - " 36/1 1.40062 1.44359 +/- 0.01097\n", - " 37/1 1.45439 1.44399 +/- 0.01056\n", - " 38/1 1.46819 1.44485 +/- 0.01022\n", - " 39/1 1.45317 1.44514 +/- 0.00986\n", - " 40/1 1.52401 1.44777 +/- 0.00988\n", - " 41/1 1.42428 1.44701 +/- 0.00959\n", - " 42/1 1.45040 1.44712 +/- 0.00929\n", - " 43/1 1.47218 1.44788 +/- 0.00903\n", - " 44/1 1.49330 1.44921 +/- 0.00886\n", - " 45/1 1.43803 1.44889 +/- 0.00861\n", - " 46/1 1.44053 1.44866 +/- 0.00837\n", - " 47/1 1.55714 1.45159 +/- 0.00866\n", - " 48/1 1.41795 1.45071 +/- 0.00847\n", - " 49/1 1.41987 1.44992 +/- 0.00829\n", - " 50/1 1.45097 1.44994 +/- 0.00808\n", + " 1/1 1.53241\n", + " 2/1 1.40513\n", + " 3/1 1.45199\n", + " 4/1 1.48296\n", + " 5/1 1.45516\n", + " 6/1 1.49568\n", + " 7/1 1.41651\n", + " 8/1 1.41637\n", + " 9/1 1.41213\n", + " 10/1 1.43048\n", + " 11/1 1.43207\n", + " 12/1 1.51388 1.47297 +/- 0.04091\n", + " 13/1 1.44591 1.46395 +/- 0.02528\n", + " 14/1 1.50325 1.47378 +/- 0.02040\n", + " 15/1 1.44463 1.46795 +/- 0.01684\n", + " 16/1 1.45528 1.46583 +/- 0.01391\n", + " 17/1 1.39473 1.45568 +/- 0.01554\n", + " 18/1 1.41153 1.45016 +/- 0.01454\n", + " 19/1 1.36173 1.44033 +/- 0.01616\n", + " 20/1 1.48965 1.44527 +/- 0.01527\n", + " 21/1 1.42710 1.44361 +/- 0.01391\n", + " 22/1 1.41558 1.44128 +/- 0.01291\n", + " 23/1 1.39316 1.43758 +/- 0.01244\n", + " 24/1 1.46698 1.43968 +/- 0.01171\n", + " 25/1 1.42137 1.43846 +/- 0.01097\n", + " 26/1 1.44859 1.43909 +/- 0.01028\n", + " 27/1 1.39159 1.43630 +/- 0.01005\n", + " 28/1 1.51030 1.44041 +/- 0.01033\n", + " 29/1 1.58514 1.44802 +/- 0.01239\n", + " 30/1 1.33291 1.44227 +/- 0.01309\n", + " 31/1 1.38694 1.43963 +/- 0.01272\n", + " 32/1 1.46008 1.44056 +/- 0.01217\n", + " 33/1 1.39234 1.43847 +/- 0.01181\n", + " 34/1 1.40957 1.43726 +/- 0.01138\n", + " 35/1 1.47587 1.43881 +/- 0.01102\n", + " 36/1 1.43015 1.43847 +/- 0.01059\n", + " 37/1 1.38802 1.43661 +/- 0.01036\n", + " 38/1 1.33953 1.43314 +/- 0.01057\n", + " 39/1 1.48062 1.43478 +/- 0.01033\n", + " 40/1 1.44053 1.43497 +/- 0.00998\n", + " 41/1 1.46435 1.43592 +/- 0.00970\n", + " 42/1 1.49916 1.43789 +/- 0.00960\n", + " 43/1 1.46589 1.43874 +/- 0.00934\n", + " 44/1 1.40238 1.43767 +/- 0.00913\n", + " 45/1 1.44733 1.43795 +/- 0.00887\n", + " 46/1 1.35951 1.43577 +/- 0.00889\n", + " 47/1 1.45303 1.43623 +/- 0.00866\n", + " 48/1 1.43982 1.43633 +/- 0.00843\n", + " 49/1 1.53025 1.43874 +/- 0.00855\n", + " 50/1 1.45253 1.43908 +/- 0.00834\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.4334e+01 seconds\n", - " Time in transport only = 1.4323e+01 seconds\n", - " Time in inactive batches = 2.4599e+00 seconds\n", - " Time in active batches = 1.1874e+01 seconds\n", - " Time synchronizing fission bank = 4.7284e-03 seconds\n", - " Sampling source sites = 4.3409e-03 seconds\n", - " SEND/RECV source sites = 3.5783e-04 seconds\n", - " Time accumulating tallies = 2.7686e-04 seconds\n", - " Time writing statepoints = 2.7450e-03 seconds\n", - " Total time for finalization = 6.6834e-03 seconds\n", - " Total time elapsed = 1.4365e+01 seconds\n", - " Calculation Rate (inactive) = 4065.28 particles/second\n", - " Calculation Rate (active) = 3368.77 particles/second\n", + " Total time in simulation = 1.2879e+01 seconds\n", + " Time in transport only = 1.2870e+01 seconds\n", + " Time in inactive batches = 2.1932e+00 seconds\n", + " Time in active batches = 1.0686e+01 seconds\n", + " Time synchronizing fission bank = 4.6210e-03 seconds\n", + " Sampling source sites = 4.2406e-03 seconds\n", + " SEND/RECV source sites = 3.5471e-04 seconds\n", + " Time accumulating tallies = 2.2210e-04 seconds\n", + " Time writing statepoints = 2.5594e-03 seconds\n", + " Total time for finalization = 5.4901e-05 seconds\n", + " Total time elapsed = 1.2893e+01 seconds\n", + " Calculation Rate (inactive) = 4559.54 particles/second\n", + " Calculation Rate (active) = 3743.15 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.44685 +/- 0.00591\n", - " k-effective (Track-length) = 1.44994 +/- 0.00808\n", - " k-effective (Absorption) = 1.43801 +/- 0.00415\n", - " Combined k-effective = 1.43997 +/- 0.00407\n", + " k-effective (Collision) = 1.43941 +/- 0.00730\n", + " k-effective (Track-length) = 1.43908 +/- 0.00834\n", + " k-effective (Absorption) = 1.43889 +/- 0.00475\n", + " Combined k-effective = 1.43891 +/- 0.00466\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n1.h5...\n", @@ -605,82 +595,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.49609\n", - " 2/1 1.47153\n", - " 3/1 1.41531\n", - " 4/1 1.42063\n", - " 5/1 1.46329\n", - " 6/1 1.44056\n", - " 7/1 1.38761\n", - " 8/1 1.45656\n", - " 9/1 1.45922\n", - " 10/1 1.40711\n", - " 11/1 1.46788\n", - " 12/1 1.45795 1.46292 +/- 0.00497\n", - " 13/1 1.50546 1.47710 +/- 0.01447\n", - " 14/1 1.44094 1.46806 +/- 0.01365\n", - " 15/1 1.36331 1.44711 +/- 0.02347\n", - " 16/1 1.39131 1.43781 +/- 0.02130\n", - " 17/1 1.31723 1.42058 +/- 0.02491\n", - " 18/1 1.39658 1.41758 +/- 0.02178\n", - " 19/1 1.41203 1.41696 +/- 0.01922\n", - " 20/1 1.37762 1.41303 +/- 0.01764\n", - " 21/1 1.48863 1.41990 +/- 0.01737\n", - " 22/1 1.41002 1.41908 +/- 0.01588\n", - " 23/1 1.41208 1.41854 +/- 0.01462\n", - " 24/1 1.41126 1.41802 +/- 0.01354\n", - " 25/1 1.43126 1.41890 +/- 0.01264\n", - " 26/1 1.51326 1.42480 +/- 0.01321\n", - " 27/1 1.46624 1.42724 +/- 0.01265\n", - " 28/1 1.42494 1.42711 +/- 0.01192\n", - " 29/1 1.41976 1.42672 +/- 0.01129\n", - " 30/1 1.40582 1.42568 +/- 0.01076\n", - " 31/1 1.34030 1.42161 +/- 0.01101\n", - " 32/1 1.38143 1.41979 +/- 0.01066\n", - " 33/1 1.47056 1.42199 +/- 0.01042\n", - " 34/1 1.45693 1.42345 +/- 0.01008\n", - " 35/1 1.47827 1.42564 +/- 0.00991\n", - " 36/1 1.34483 1.42253 +/- 0.01002\n", - " 37/1 1.42930 1.42278 +/- 0.00964\n", - " 38/1 1.38584 1.42147 +/- 0.00939\n", - " 39/1 1.43818 1.42204 +/- 0.00908\n", - " 40/1 1.38034 1.42065 +/- 0.00888\n", - " 41/1 1.38352 1.41945 +/- 0.00867\n", - " 42/1 1.44455 1.42024 +/- 0.00843\n", - " 43/1 1.54961 1.42416 +/- 0.00906\n", - " 44/1 1.42095 1.42406 +/- 0.00879\n", - " 45/1 1.39984 1.42337 +/- 0.00857\n", - " 46/1 1.50165 1.42555 +/- 0.00860\n", - " 47/1 1.52897 1.42834 +/- 0.00882\n", - " 48/1 1.41814 1.42807 +/- 0.00859\n", - " 49/1 1.49425 1.42977 +/- 0.00854\n", - " 50/1 1.39230 1.42883 +/- 0.00838\n", + " 1/1 1.35648\n", + " 2/1 1.41942\n", + " 3/1 1.36608\n", + " 4/1 1.46674\n", + " 5/1 1.47455\n", + " 6/1 1.40320\n", + " 7/1 1.36282\n", + " 8/1 1.41123\n", + " 9/1 1.45872\n", + " 10/1 1.43235\n", + " 11/1 1.43551\n", + " 12/1 1.42639 1.43095 +/- 0.00456\n", + " 13/1 1.38410 1.41533 +/- 0.01584\n", + " 14/1 1.40010 1.41152 +/- 0.01183\n", + " 15/1 1.45122 1.41946 +/- 0.01212\n", + " 16/1 1.46395 1.42688 +/- 0.01237\n", + " 17/1 1.50374 1.43786 +/- 0.01516\n", + " 18/1 1.41657 1.43520 +/- 0.01340\n", + " 19/1 1.39988 1.43127 +/- 0.01245\n", + " 20/1 1.48773 1.43692 +/- 0.01248\n", + " 21/1 1.50428 1.44304 +/- 0.01285\n", + " 22/1 1.40603 1.43996 +/- 0.01213\n", + " 23/1 1.44173 1.44009 +/- 0.01115\n", + " 24/1 1.47605 1.44266 +/- 0.01064\n", + " 25/1 1.41864 1.44106 +/- 0.01004\n", + " 26/1 1.42455 1.44003 +/- 0.00944\n", + " 27/1 1.43444 1.43970 +/- 0.00888\n", + " 28/1 1.39999 1.43749 +/- 0.00866\n", + " 29/1 1.45318 1.43832 +/- 0.00823\n", + " 30/1 1.46514 1.43966 +/- 0.00792\n", + " 31/1 1.49160 1.44213 +/- 0.00793\n", + " 32/1 1.34013 1.43750 +/- 0.00887\n", + " 33/1 1.48829 1.43971 +/- 0.00876\n", + " 34/1 1.47141 1.44103 +/- 0.00849\n", + " 35/1 1.39193 1.43906 +/- 0.00838\n", + " 36/1 1.39036 1.43719 +/- 0.00826\n", + " 37/1 1.44249 1.43739 +/- 0.00795\n", + " 38/1 1.48357 1.43904 +/- 0.00784\n", + " 39/1 1.40641 1.43791 +/- 0.00765\n", + " 40/1 1.42094 1.43734 +/- 0.00741\n", + " 41/1 1.40773 1.43639 +/- 0.00723\n", + " 42/1 1.45978 1.43712 +/- 0.00704\n", + " 43/1 1.42308 1.43669 +/- 0.00683\n", + " 44/1 1.47645 1.43786 +/- 0.00673\n", + " 45/1 1.51314 1.44001 +/- 0.00688\n", + " 46/1 1.48159 1.44117 +/- 0.00679\n", + " 47/1 1.48586 1.44238 +/- 0.00671\n", + " 48/1 1.38670 1.44091 +/- 0.00669\n", + " 49/1 1.53726 1.44338 +/- 0.00697\n", + " 50/1 1.44556 1.44344 +/- 0.00680\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.5356e+01 seconds\n", - " Time in transport only = 1.5345e+01 seconds\n", - " Time in inactive batches = 2.5600e+00 seconds\n", - " Time in active batches = 1.2796e+01 seconds\n", - " Time synchronizing fission bank = 4.8536e-03 seconds\n", - " Sampling source sites = 4.4341e-03 seconds\n", - " SEND/RECV source sites = 3.8411e-04 seconds\n", - " Time accumulating tallies = 3.1893e-04 seconds\n", - " Time writing statepoints = 2.9909e-03 seconds\n", - " Total time for finalization = 5.8300e-05 seconds\n", - " Total time elapsed = 1.5380e+01 seconds\n", - " Calculation Rate (inactive) = 3906.26 particles/second\n", - " Calculation Rate (active) = 3125.88 particles/second\n", + " Total time in simulation = 1.2995e+01 seconds\n", + " Time in transport only = 1.2986e+01 seconds\n", + " Time in inactive batches = 2.2152e+00 seconds\n", + " Time in active batches = 1.0780e+01 seconds\n", + " Time synchronizing fission bank = 4.3730e-03 seconds\n", + " Sampling source sites = 3.9823e-03 seconds\n", + " SEND/RECV source sites = 3.6477e-04 seconds\n", + " Time accumulating tallies = 2.3376e-04 seconds\n", + " Time writing statepoints = 2.6625e-03 seconds\n", + " Total time for finalization = 6.8176e-03 seconds\n", + " Total time elapsed = 1.3016e+01 seconds\n", + " Calculation Rate (inactive) = 4514.3 particles/second\n", + " Calculation Rate (active) = 3710.67 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.43006 +/- 0.00591\n", - " k-effective (Track-length) = 1.42883 +/- 0.00838\n", - " k-effective (Absorption) = 1.42863 +/- 0.00572\n", - " Combined k-effective = 1.42936 +/- 0.00514\n", + " k-effective (Collision) = 1.43781 +/- 0.00627\n", + " k-effective (Track-length) = 1.44344 +/- 0.00680\n", + " k-effective (Absorption) = 1.43243 +/- 0.00527\n", + " Combined k-effective = 1.43604 +/- 0.00493\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n2.h5...\n", @@ -692,82 +682,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.44525\n", - " 2/1 1.39725\n", - " 3/1 1.49818\n", - " 4/1 1.43473\n", - " 5/1 1.55325\n", - " 6/1 1.49043\n", - " 7/1 1.44001\n", - " 8/1 1.47096\n", - " 9/1 1.33569\n", - " 10/1 1.43309\n", - " 11/1 1.40207\n", - " 12/1 1.40982 1.40594 +/- 0.00388\n", - " 13/1 1.46991 1.42727 +/- 0.02144\n", - " 14/1 1.27811 1.38998 +/- 0.04025\n", - " 15/1 1.41299 1.39458 +/- 0.03152\n", - " 16/1 1.44922 1.40369 +/- 0.02730\n", - " 17/1 1.40275 1.40355 +/- 0.02307\n", - " 18/1 1.40665 1.40394 +/- 0.01998\n", - " 19/1 1.46326 1.41053 +/- 0.01882\n", - " 20/1 1.40650 1.41013 +/- 0.01684\n", - " 21/1 1.37708 1.40712 +/- 0.01552\n", - " 22/1 1.40019 1.40655 +/- 0.01418\n", - " 23/1 1.42877 1.40826 +/- 0.01316\n", - " 24/1 1.37671 1.40600 +/- 0.01239\n", - " 25/1 1.40717 1.40608 +/- 0.01153\n", - " 26/1 1.46304 1.40964 +/- 0.01136\n", - " 27/1 1.37648 1.40769 +/- 0.01085\n", - " 28/1 1.36343 1.40523 +/- 0.01052\n", - " 29/1 1.52641 1.41161 +/- 0.01182\n", - " 30/1 1.32142 1.40710 +/- 0.01208\n", - " 31/1 1.48502 1.41081 +/- 0.01208\n", - " 32/1 1.40243 1.41043 +/- 0.01152\n", - " 33/1 1.48399 1.41363 +/- 0.01147\n", - " 34/1 1.49694 1.41710 +/- 0.01151\n", - " 35/1 1.46212 1.41890 +/- 0.01119\n", - " 36/1 1.50103 1.42206 +/- 0.01120\n", - " 37/1 1.47787 1.42413 +/- 0.01098\n", - " 38/1 1.40935 1.42360 +/- 0.01059\n", - " 39/1 1.42517 1.42365 +/- 0.01022\n", - " 40/1 1.39736 1.42277 +/- 0.00991\n", - " 41/1 1.41014 1.42237 +/- 0.00960\n", - " 42/1 1.45449 1.42337 +/- 0.00935\n", - " 43/1 1.38649 1.42225 +/- 0.00913\n", - " 44/1 1.40900 1.42186 +/- 0.00886\n", - " 45/1 1.50622 1.42427 +/- 0.00894\n", - " 46/1 1.43840 1.42467 +/- 0.00869\n", - " 47/1 1.41787 1.42448 +/- 0.00846\n", - " 48/1 1.39728 1.42377 +/- 0.00826\n", - " 49/1 1.44498 1.42431 +/- 0.00807\n", - " 50/1 1.43243 1.42451 +/- 0.00787\n", + " 1/1 1.52145\n", + " 2/1 1.45763\n", + " 3/1 1.38715\n", + " 4/1 1.49491\n", + " 5/1 1.45451\n", + " 6/1 1.41857\n", + " 7/1 1.36661\n", + " 8/1 1.35323\n", + " 9/1 1.32219\n", + " 10/1 1.45559\n", + " 11/1 1.56651\n", + " 12/1 1.37746 1.47198 +/- 0.09452\n", + " 13/1 1.41360 1.45252 +/- 0.05794\n", + " 14/1 1.46543 1.45575 +/- 0.04110\n", + " 15/1 1.36700 1.43800 +/- 0.03645\n", + " 16/1 1.41995 1.43499 +/- 0.02991\n", + " 17/1 1.48070 1.44152 +/- 0.02611\n", + " 18/1 1.46150 1.44402 +/- 0.02275\n", + " 19/1 1.34499 1.43302 +/- 0.02288\n", + " 20/1 1.47485 1.43720 +/- 0.02089\n", + " 21/1 1.50424 1.44329 +/- 0.01985\n", + " 22/1 1.41394 1.44085 +/- 0.01829\n", + " 23/1 1.43248 1.44020 +/- 0.01683\n", + " 24/1 1.38295 1.43611 +/- 0.01611\n", + " 25/1 1.42331 1.43526 +/- 0.01503\n", + " 26/1 1.44462 1.43585 +/- 0.01407\n", + " 27/1 1.43415 1.43575 +/- 0.01321\n", + " 28/1 1.48582 1.43853 +/- 0.01276\n", + " 29/1 1.44884 1.43907 +/- 0.01209\n", + " 30/1 1.34656 1.43444 +/- 0.01236\n", + " 31/1 1.44433 1.43492 +/- 0.01177\n", + " 32/1 1.48062 1.43699 +/- 0.01141\n", + " 33/1 1.37226 1.43418 +/- 0.01126\n", + " 34/1 1.31991 1.42942 +/- 0.01179\n", + " 35/1 1.48850 1.43178 +/- 0.01155\n", + " 36/1 1.47446 1.43342 +/- 0.01122\n", + " 37/1 1.49478 1.43569 +/- 0.01103\n", + " 38/1 1.35729 1.43289 +/- 0.01099\n", + " 39/1 1.37560 1.43092 +/- 0.01079\n", + " 40/1 1.41980 1.43055 +/- 0.01043\n", + " 41/1 1.36832 1.42854 +/- 0.01029\n", + " 42/1 1.41065 1.42798 +/- 0.00997\n", + " 43/1 1.36825 1.42617 +/- 0.00984\n", + " 44/1 1.37304 1.42461 +/- 0.00967\n", + " 45/1 1.40813 1.42414 +/- 0.00940\n", + " 46/1 1.39351 1.42329 +/- 0.00918\n", + " 47/1 1.46699 1.42447 +/- 0.00900\n", + " 48/1 1.41202 1.42414 +/- 0.00877\n", + " 49/1 1.45476 1.42493 +/- 0.00858\n", + " 50/1 1.38327 1.42388 +/- 0.00842\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.5938e+01 seconds\n", - " Time in transport only = 1.5926e+01 seconds\n", - " Time in inactive batches = 2.7348e+00 seconds\n", - " Time in active batches = 1.3203e+01 seconds\n", - " Time synchronizing fission bank = 4.8009e-03 seconds\n", - " Sampling source sites = 4.3574e-03 seconds\n", - " SEND/RECV source sites = 4.0496e-04 seconds\n", - " Time accumulating tallies = 3.4334e-04 seconds\n", - " Time writing statepoints = 3.1199e-03 seconds\n", - " Total time for finalization = 5.7181e-05 seconds\n", - " Total time elapsed = 1.5963e+01 seconds\n", - " Calculation Rate (inactive) = 3656.52 particles/second\n", - " Calculation Rate (active) = 3029.69 particles/second\n", + " Total time in simulation = 1.3031e+01 seconds\n", + " Time in transport only = 1.3022e+01 seconds\n", + " Time in inactive batches = 2.2077e+00 seconds\n", + " Time in active batches = 1.0824e+01 seconds\n", + " Time synchronizing fission bank = 4.5578e-03 seconds\n", + " Sampling source sites = 4.1598e-03 seconds\n", + " SEND/RECV source sites = 3.7168e-04 seconds\n", + " Time accumulating tallies = 2.3355e-04 seconds\n", + " Time writing statepoints = 2.7490e-03 seconds\n", + " Total time for finalization = 4.9850e-05 seconds\n", + " Total time elapsed = 1.3045e+01 seconds\n", + " Calculation Rate (inactive) = 4529.68 particles/second\n", + " Calculation Rate (active) = 3695.64 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.42805 +/- 0.00568\n", - " k-effective (Track-length) = 1.42451 +/- 0.00787\n", - " k-effective (Absorption) = 1.42588 +/- 0.00400\n", - " Combined k-effective = 1.42628 +/- 0.00367\n", + " k-effective (Collision) = 1.42700 +/- 0.00561\n", + " k-effective (Track-length) = 1.42388 +/- 0.00842\n", + " k-effective (Absorption) = 1.43128 +/- 0.00502\n", + " Combined k-effective = 1.42959 +/- 0.00429\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n3.h5...\n", @@ -779,82 +769,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.42372\n", - " 2/1 1.36392\n", - " 3/1 1.56019\n", - " 4/1 1.41091\n", - " 5/1 1.44355\n", - " 6/1 1.42948\n", - " 7/1 1.43458\n", - " 8/1 1.42146\n", - " 9/1 1.35445\n", - " 10/1 1.42498\n", - " 11/1 1.43976\n", - " 12/1 1.42404 1.43190 +/- 0.00786\n", - " 13/1 1.38913 1.41764 +/- 0.01496\n", - " 14/1 1.43466 1.42190 +/- 0.01140\n", - " 15/1 1.48155 1.43383 +/- 0.01484\n", - " 16/1 1.37786 1.42450 +/- 0.01529\n", - " 17/1 1.46886 1.43084 +/- 0.01440\n", - " 18/1 1.38946 1.42566 +/- 0.01350\n", - " 19/1 1.41925 1.42495 +/- 0.01193\n", - " 20/1 1.38620 1.42108 +/- 0.01135\n", - " 21/1 1.35242 1.41484 +/- 0.01201\n", - " 22/1 1.48247 1.42047 +/- 0.01233\n", - " 23/1 1.44192 1.42212 +/- 0.01146\n", - " 24/1 1.34402 1.41654 +/- 0.01199\n", - " 25/1 1.44718 1.41859 +/- 0.01135\n", - " 26/1 1.47729 1.42225 +/- 0.01123\n", - " 27/1 1.52300 1.42818 +/- 0.01210\n", - " 28/1 1.41466 1.42743 +/- 0.01143\n", - " 29/1 1.51501 1.43204 +/- 0.01175\n", - " 30/1 1.47697 1.43429 +/- 0.01138\n", - " 31/1 1.45582 1.43531 +/- 0.01087\n", - " 32/1 1.44561 1.43578 +/- 0.01037\n", - " 33/1 1.45486 1.43661 +/- 0.00995\n", - " 34/1 1.40667 1.43536 +/- 0.00960\n", - " 35/1 1.54290 1.43966 +/- 0.01017\n", - " 36/1 1.35465 1.43639 +/- 0.01030\n", - " 37/1 1.43986 1.43652 +/- 0.00991\n", - " 38/1 1.40741 1.43548 +/- 0.00961\n", - " 39/1 1.35348 1.43265 +/- 0.00969\n", - " 40/1 1.34159 1.42962 +/- 0.00984\n", - " 41/1 1.47708 1.43115 +/- 0.00964\n", - " 42/1 1.49474 1.43314 +/- 0.00955\n", - " 43/1 1.40445 1.43227 +/- 0.00929\n", - " 44/1 1.36593 1.43032 +/- 0.00922\n", - " 45/1 1.38073 1.42890 +/- 0.00907\n", - " 46/1 1.42638 1.42883 +/- 0.00881\n", - " 47/1 1.40671 1.42823 +/- 0.00859\n", - " 48/1 1.36251 1.42650 +/- 0.00854\n", - " 49/1 1.43370 1.42669 +/- 0.00832\n", - " 50/1 1.39115 1.42580 +/- 0.00816\n", + " 1/1 1.38925\n", + " 2/1 1.42976\n", + " 3/1 1.41226\n", + " 4/1 1.39211\n", + " 5/1 1.50564\n", + " 6/1 1.47182\n", + " 7/1 1.40604\n", + " 8/1 1.47053\n", + " 9/1 1.38703\n", + " 10/1 1.40210\n", + " 11/1 1.49465\n", + " 12/1 1.38331 1.43898 +/- 0.05567\n", + " 13/1 1.36733 1.41510 +/- 0.04004\n", + " 14/1 1.43836 1.42091 +/- 0.02891\n", + " 15/1 1.28111 1.39295 +/- 0.03582\n", + " 16/1 1.46121 1.40433 +/- 0.03138\n", + " 17/1 1.33978 1.39511 +/- 0.02808\n", + " 18/1 1.41161 1.39717 +/- 0.02440\n", + " 19/1 1.39461 1.39689 +/- 0.02152\n", + " 20/1 1.47066 1.40426 +/- 0.02062\n", + " 21/1 1.42437 1.40609 +/- 0.01874\n", + " 22/1 1.46622 1.41110 +/- 0.01782\n", + " 23/1 1.37032 1.40797 +/- 0.01669\n", + " 24/1 1.41432 1.40842 +/- 0.01546\n", + " 25/1 1.38921 1.40714 +/- 0.01445\n", + " 26/1 1.40164 1.40679 +/- 0.01352\n", + " 27/1 1.42757 1.40802 +/- 0.01276\n", + " 28/1 1.32544 1.40343 +/- 0.01288\n", + " 29/1 1.45468 1.40613 +/- 0.01247\n", + " 30/1 1.49292 1.41047 +/- 0.01261\n", + " 31/1 1.38744 1.40937 +/- 0.01204\n", + " 32/1 1.46078 1.41171 +/- 0.01171\n", + " 33/1 1.42757 1.41240 +/- 0.01122\n", + " 34/1 1.44109 1.41359 +/- 0.01080\n", + " 35/1 1.39698 1.41293 +/- 0.01038\n", + " 36/1 1.47438 1.41529 +/- 0.01025\n", + " 37/1 1.45001 1.41658 +/- 0.00995\n", + " 38/1 1.42864 1.41701 +/- 0.00960\n", + " 39/1 1.44516 1.41798 +/- 0.00931\n", + " 40/1 1.46250 1.41946 +/- 0.00912\n", + " 41/1 1.36719 1.41778 +/- 0.00898\n", + " 42/1 1.32118 1.41476 +/- 0.00920\n", + " 43/1 1.48217 1.41680 +/- 0.00915\n", + " 44/1 1.46043 1.41808 +/- 0.00897\n", + " 45/1 1.47425 1.41969 +/- 0.00886\n", + " 46/1 1.46925 1.42107 +/- 0.00872\n", + " 47/1 1.46076 1.42214 +/- 0.00854\n", + " 48/1 1.34478 1.42010 +/- 0.00856\n", + " 49/1 1.38493 1.41920 +/- 0.00839\n", + " 50/1 1.34114 1.41725 +/- 0.00841\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.5839e+01 seconds\n", - " Time in transport only = 1.5827e+01 seconds\n", - " Time in inactive batches = 2.7033e+00 seconds\n", - " Time in active batches = 1.3136e+01 seconds\n", - " Time synchronizing fission bank = 4.9757e-03 seconds\n", - " Sampling source sites = 4.5464e-03 seconds\n", - " SEND/RECV source sites = 3.9214e-04 seconds\n", - " Time accumulating tallies = 3.2820e-04 seconds\n", - " Time writing statepoints = 3.0288e-03 seconds\n", - " Total time for finalization = 5.6741e-05 seconds\n", - " Total time elapsed = 1.5865e+01 seconds\n", - " Calculation Rate (inactive) = 3699.13 particles/second\n", - " Calculation Rate (active) = 3045.12 particles/second\n", + " Total time in simulation = 1.3126e+01 seconds\n", + " Time in transport only = 1.3116e+01 seconds\n", + " Time in inactive batches = 2.2380e+00 seconds\n", + " Time in active batches = 1.0888e+01 seconds\n", + " Time synchronizing fission bank = 4.1247e-03 seconds\n", + " Sampling source sites = 3.7224e-03 seconds\n", + " SEND/RECV source sites = 3.7812e-04 seconds\n", + " Time accumulating tallies = 2.2789e-04 seconds\n", + " Time writing statepoints = 3.0614e-03 seconds\n", + " Total time for finalization = 5.4060e-05 seconds\n", + " Total time elapsed = 1.3140e+01 seconds\n", + " Calculation Rate (inactive) = 4468.2 particles/second\n", + " Calculation Rate (active) = 3673.84 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.41659 +/- 0.00659\n", - " k-effective (Track-length) = 1.42580 +/- 0.00816\n", - " k-effective (Absorption) = 1.40992 +/- 0.00492\n", - " Combined k-effective = 1.41334 +/- 0.00460\n", + " k-effective (Collision) = 1.41574 +/- 0.00666\n", + " k-effective (Track-length) = 1.41725 +/- 0.00841\n", + " k-effective (Absorption) = 1.42868 +/- 0.00429\n", + " Combined k-effective = 1.42755 +/- 0.00464\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n4.h5...\n", @@ -866,82 +856,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.50840\n", - " 2/1 1.37871\n", - " 3/1 1.44147\n", - " 4/1 1.37502\n", - " 5/1 1.51166\n", - " 6/1 1.36480\n", - " 7/1 1.37474\n", - " 8/1 1.50120\n", - " 9/1 1.48437\n", - " 10/1 1.43839\n", - " 11/1 1.42606\n", - " 12/1 1.36163 1.39384 +/- 0.03222\n", - " 13/1 1.43083 1.40617 +/- 0.02232\n", - " 14/1 1.43214 1.41266 +/- 0.01706\n", - " 15/1 1.39529 1.40919 +/- 0.01367\n", - " 16/1 1.40656 1.40875 +/- 0.01117\n", - " 17/1 1.45853 1.41586 +/- 0.01182\n", - " 18/1 1.38835 1.41242 +/- 0.01080\n", - " 19/1 1.37392 1.40814 +/- 0.01044\n", - " 20/1 1.44311 1.41164 +/- 0.00997\n", - " 21/1 1.37689 1.40848 +/- 0.00955\n", - " 22/1 1.44170 1.41125 +/- 0.00915\n", - " 23/1 1.42896 1.41261 +/- 0.00853\n", - " 24/1 1.40808 1.41229 +/- 0.00790\n", - " 25/1 1.38138 1.41023 +/- 0.00764\n", - " 26/1 1.47825 1.41448 +/- 0.00831\n", - " 27/1 1.50549 1.41983 +/- 0.00947\n", - " 28/1 1.44024 1.42097 +/- 0.00900\n", - " 29/1 1.55001 1.42776 +/- 0.01089\n", - " 30/1 1.45065 1.42890 +/- 0.01039\n", - " 31/1 1.44314 1.42958 +/- 0.00991\n", - " 32/1 1.53581 1.43441 +/- 0.01061\n", - " 33/1 1.34584 1.43056 +/- 0.01085\n", - " 34/1 1.46262 1.43189 +/- 0.01047\n", - " 35/1 1.40896 1.43098 +/- 0.01008\n", - " 36/1 1.43938 1.43130 +/- 0.00969\n", - " 37/1 1.42939 1.43123 +/- 0.00933\n", - " 38/1 1.36832 1.42898 +/- 0.00927\n", - " 39/1 1.41975 1.42866 +/- 0.00895\n", - " 40/1 1.44832 1.42932 +/- 0.00867\n", - " 41/1 1.42290 1.42911 +/- 0.00839\n", - " 42/1 1.39116 1.42793 +/- 0.00821\n", - " 43/1 1.51719 1.43063 +/- 0.00840\n", - " 44/1 1.37441 1.42898 +/- 0.00832\n", - " 45/1 1.40624 1.42833 +/- 0.00810\n", - " 46/1 1.43779 1.42859 +/- 0.00788\n", - " 47/1 1.46176 1.42949 +/- 0.00771\n", - " 48/1 1.35875 1.42763 +/- 0.00773\n", - " 49/1 1.47829 1.42893 +/- 0.00765\n", - " 50/1 1.45400 1.42955 +/- 0.00748\n", + " 1/1 1.41046\n", + " 2/1 1.38415\n", + " 3/1 1.41886\n", + " 4/1 1.49276\n", + " 5/1 1.51088\n", + " 6/1 1.47652\n", + " 7/1 1.35478\n", + " 8/1 1.35145\n", + " 9/1 1.49048\n", + " 10/1 1.44388\n", + " 11/1 1.46152\n", + " 12/1 1.46663 1.46408 +/- 0.00255\n", + " 13/1 1.47189 1.46668 +/- 0.00299\n", + " 14/1 1.39703 1.44927 +/- 0.01754\n", + " 15/1 1.41472 1.44236 +/- 0.01524\n", + " 16/1 1.42886 1.44011 +/- 0.01265\n", + " 17/1 1.45836 1.44272 +/- 0.01100\n", + " 18/1 1.44504 1.44301 +/- 0.00953\n", + " 19/1 1.35868 1.43364 +/- 0.01259\n", + " 20/1 1.36823 1.42710 +/- 0.01302\n", + " 21/1 1.44284 1.42853 +/- 0.01186\n", + " 22/1 1.52754 1.43678 +/- 0.01362\n", + " 23/1 1.44989 1.43779 +/- 0.01257\n", + " 24/1 1.48022 1.44082 +/- 0.01202\n", + " 25/1 1.40460 1.43840 +/- 0.01145\n", + " 26/1 1.36586 1.43387 +/- 0.01163\n", + " 27/1 1.35671 1.42933 +/- 0.01183\n", + " 28/1 1.54670 1.43585 +/- 0.01292\n", + " 29/1 1.41323 1.43466 +/- 0.01228\n", + " 30/1 1.41355 1.43361 +/- 0.01170\n", + " 31/1 1.56992 1.44010 +/- 0.01288\n", + " 32/1 1.35745 1.43634 +/- 0.01284\n", + " 33/1 1.42131 1.43569 +/- 0.01229\n", + " 34/1 1.45210 1.43637 +/- 0.01179\n", + " 35/1 1.36098 1.43335 +/- 0.01170\n", + " 36/1 1.45621 1.43423 +/- 0.01128\n", + " 37/1 1.47355 1.43569 +/- 0.01095\n", + " 38/1 1.44393 1.43598 +/- 0.01055\n", + " 39/1 1.52203 1.43895 +/- 0.01061\n", + " 40/1 1.43143 1.43870 +/- 0.01025\n", + " 41/1 1.44187 1.43880 +/- 0.00991\n", + " 42/1 1.27834 1.43379 +/- 0.01083\n", + " 43/1 1.38906 1.43243 +/- 0.01058\n", + " 44/1 1.41543 1.43193 +/- 0.01028\n", + " 45/1 1.39747 1.43095 +/- 0.01003\n", + " 46/1 1.38755 1.42974 +/- 0.00982\n", + " 47/1 1.40362 1.42904 +/- 0.00958\n", + " 48/1 1.32535 1.42631 +/- 0.00971\n", + " 49/1 1.38622 1.42528 +/- 0.00952\n", + " 50/1 1.40968 1.42489 +/- 0.00928\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.5879e+01 seconds\n", - " Time in transport only = 1.5868e+01 seconds\n", - " Time in inactive batches = 2.7260e+00 seconds\n", - " Time in active batches = 1.3153e+01 seconds\n", - " Time synchronizing fission bank = 4.7604e-03 seconds\n", - " Sampling source sites = 4.3338e-03 seconds\n", - " SEND/RECV source sites = 3.9159e-04 seconds\n", - " Time accumulating tallies = 3.6340e-04 seconds\n", - " Time writing statepoints = 2.9921e-03 seconds\n", - " Total time for finalization = 5.7621e-05 seconds\n", - " Total time elapsed = 1.5905e+01 seconds\n", - " Calculation Rate (inactive) = 3668.45 particles/second\n", - " Calculation Rate (active) = 3041.07 particles/second\n", + " Total time in simulation = 1.3098e+01 seconds\n", + " Time in transport only = 1.3089e+01 seconds\n", + " Time in inactive batches = 2.2179e+00 seconds\n", + " Time in active batches = 1.0881e+01 seconds\n", + " Time synchronizing fission bank = 4.5930e-03 seconds\n", + " Sampling source sites = 4.1842e-03 seconds\n", + " SEND/RECV source sites = 3.7955e-04 seconds\n", + " Time accumulating tallies = 2.4737e-04 seconds\n", + " Time writing statepoints = 2.7292e-03 seconds\n", + " Total time for finalization = 5.2371e-05 seconds\n", + " Total time elapsed = 1.3112e+01 seconds\n", + " Calculation Rate (inactive) = 4508.68 particles/second\n", + " Calculation Rate (active) = 3676.29 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.42351 +/- 0.00647\n", - " k-effective (Track-length) = 1.42955 +/- 0.00748\n", - " k-effective (Absorption) = 1.42123 +/- 0.00460\n", - " Combined k-effective = 1.42301 +/- 0.00453\n", + " k-effective (Collision) = 1.42490 +/- 0.00784\n", + " k-effective (Track-length) = 1.42489 +/- 0.00928\n", + " k-effective (Absorption) = 1.42584 +/- 0.00494\n", + " Combined k-effective = 1.42575 +/- 0.00483\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n5.h5...\n", @@ -953,82 +943,82 @@ "\n", " Bat./Gen. k Average k\n", " ========= ======== ====================\n", - " 1/1 1.45179\n", - " 2/1 1.33474\n", - " 3/1 1.40530\n", - " 4/1 1.34120\n", - " 5/1 1.46186\n", - " 6/1 1.48744\n", - " 7/1 1.47086\n", - " 8/1 1.40613\n", - " 9/1 1.42509\n", - " 10/1 1.41891\n", - " 11/1 1.37455\n", - " 12/1 1.41770 1.39613 +/- 0.02158\n", - " 13/1 1.43778 1.41001 +/- 0.01865\n", - " 14/1 1.38670 1.40418 +/- 0.01442\n", - " 15/1 1.53620 1.43059 +/- 0.02867\n", - " 16/1 1.34925 1.41703 +/- 0.02705\n", - " 17/1 1.29340 1.39937 +/- 0.02889\n", - " 18/1 1.46871 1.40804 +/- 0.02648\n", - " 19/1 1.43752 1.41131 +/- 0.02358\n", - " 20/1 1.44796 1.41498 +/- 0.02141\n", - " 21/1 1.35480 1.40951 +/- 0.02012\n", - " 22/1 1.41545 1.41000 +/- 0.01837\n", - " 23/1 1.38735 1.40826 +/- 0.01699\n", - " 24/1 1.31729 1.40176 +/- 0.01702\n", - " 25/1 1.35917 1.39892 +/- 0.01610\n", - " 26/1 1.45585 1.40248 +/- 0.01547\n", - " 27/1 1.44240 1.40483 +/- 0.01472\n", - " 28/1 1.37028 1.40291 +/- 0.01401\n", - " 29/1 1.40159 1.40284 +/- 0.01325\n", - " 30/1 1.44674 1.40503 +/- 0.01276\n", - " 31/1 1.40583 1.40507 +/- 0.01214\n", - " 32/1 1.35239 1.40268 +/- 0.01182\n", - " 33/1 1.42400 1.40360 +/- 0.01133\n", - " 34/1 1.47846 1.40672 +/- 0.01129\n", - " 35/1 1.40109 1.40650 +/- 0.01083\n", - " 36/1 1.39432 1.40603 +/- 0.01042\n", - " 37/1 1.29680 1.40198 +/- 0.01081\n", - " 38/1 1.42088 1.40266 +/- 0.01044\n", - " 39/1 1.39365 1.40235 +/- 0.01008\n", - " 40/1 1.44057 1.40362 +/- 0.00982\n", - " 41/1 1.37402 1.40267 +/- 0.00954\n", - " 42/1 1.40850 1.40285 +/- 0.00924\n", - " 43/1 1.49684 1.40570 +/- 0.00940\n", - " 44/1 1.35129 1.40410 +/- 0.00926\n", - " 45/1 1.48278 1.40635 +/- 0.00927\n", - " 46/1 1.43966 1.40727 +/- 0.00905\n", - " 47/1 1.47286 1.40904 +/- 0.00898\n", - " 48/1 1.37405 1.40812 +/- 0.00879\n", - " 49/1 1.40086 1.40794 +/- 0.00856\n", - " 50/1 1.45317 1.40907 +/- 0.00842\n", + " 1/1 1.46692\n", + " 2/1 1.42016\n", + " 3/1 1.35815\n", + " 4/1 1.38064\n", + " 5/1 1.44504\n", + " 6/1 1.36182\n", + " 7/1 1.31279\n", + " 8/1 1.47632\n", + " 9/1 1.48287\n", + " 10/1 1.40492\n", + " 11/1 1.34730\n", + " 12/1 1.46660 1.40695 +/- 0.05965\n", + " 13/1 1.47009 1.42800 +/- 0.04036\n", + " 14/1 1.41037 1.42359 +/- 0.02888\n", + " 15/1 1.35040 1.40895 +/- 0.02673\n", + " 16/1 1.41945 1.41070 +/- 0.02190\n", + " 17/1 1.54521 1.42992 +/- 0.02668\n", + " 18/1 1.45638 1.43322 +/- 0.02334\n", + " 19/1 1.38313 1.42766 +/- 0.02132\n", + " 20/1 1.48971 1.43386 +/- 0.02006\n", + " 21/1 1.43673 1.43412 +/- 0.01814\n", + " 22/1 1.38255 1.42983 +/- 0.01711\n", + " 23/1 1.47338 1.43318 +/- 0.01609\n", + " 24/1 1.43212 1.43310 +/- 0.01490\n", + " 25/1 1.47334 1.43578 +/- 0.01413\n", + " 26/1 1.44139 1.43613 +/- 0.01322\n", + " 27/1 1.47399 1.43836 +/- 0.01262\n", + " 28/1 1.45271 1.43916 +/- 0.01192\n", + " 29/1 1.41352 1.43781 +/- 0.01136\n", + " 30/1 1.40013 1.43593 +/- 0.01094\n", + " 31/1 1.44858 1.43653 +/- 0.01042\n", + " 32/1 1.38137 1.43402 +/- 0.01025\n", + " 33/1 1.37217 1.43133 +/- 0.01015\n", + " 34/1 1.36865 1.42872 +/- 0.01007\n", + " 35/1 1.35863 1.42592 +/- 0.01005\n", + " 36/1 1.41942 1.42567 +/- 0.00966\n", + " 37/1 1.47196 1.42738 +/- 0.00945\n", + " 38/1 1.50806 1.43026 +/- 0.00956\n", + " 39/1 1.38029 1.42854 +/- 0.00938\n", + " 40/1 1.32528 1.42510 +/- 0.00969\n", + " 41/1 1.43717 1.42549 +/- 0.00938\n", + " 42/1 1.40786 1.42494 +/- 0.00910\n", + " 43/1 1.45468 1.42584 +/- 0.00887\n", + " 44/1 1.32809 1.42296 +/- 0.00907\n", + " 45/1 1.37289 1.42153 +/- 0.00892\n", + " 46/1 1.39638 1.42083 +/- 0.00870\n", + " 47/1 1.45351 1.42172 +/- 0.00851\n", + " 48/1 1.37909 1.42059 +/- 0.00836\n", + " 49/1 1.41817 1.42053 +/- 0.00814\n", + " 50/1 1.36996 1.41927 +/- 0.00803\n", " Creating state point statepoint.50.h5...\n", "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", " Total time for initialization = 0.0000e+00 seconds\n", " Reading cross sections = 0.0000e+00 seconds\n", - " Total time in simulation = 1.4969e+01 seconds\n", - " Time in transport only = 1.4958e+01 seconds\n", - " Time in inactive batches = 2.7192e+00 seconds\n", - " Time in active batches = 1.2250e+01 seconds\n", - " Time synchronizing fission bank = 5.2067e-03 seconds\n", - " Sampling source sites = 4.8368e-03 seconds\n", - " SEND/RECV source sites = 3.3899e-04 seconds\n", - " Time accumulating tallies = 2.7359e-04 seconds\n", - " Time writing statepoints = 2.8293e-03 seconds\n", - " Total time for finalization = 5.0560e-05 seconds\n", - " Total time elapsed = 1.5008e+01 seconds\n", - " Calculation Rate (inactive) = 3677.55 particles/second\n", - " Calculation Rate (active) = 3265.28 particles/second\n", + " Total time in simulation = 1.3234e+01 seconds\n", + " Time in transport only = 1.3225e+01 seconds\n", + " Time in inactive batches = 2.2456e+00 seconds\n", + " Time in active batches = 1.0989e+01 seconds\n", + " Time synchronizing fission bank = 4.2442e-03 seconds\n", + " Sampling source sites = 3.8368e-03 seconds\n", + " SEND/RECV source sites = 3.8075e-04 seconds\n", + " Time accumulating tallies = 2.4804e-04 seconds\n", + " Time writing statepoints = 2.7128e-03 seconds\n", + " Total time for finalization = 5.0970e-05 seconds\n", + " Total time elapsed = 1.3248e+01 seconds\n", + " Calculation Rate (inactive) = 4453.13 particles/second\n", + " Calculation Rate (active) = 3640.13 particles/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.41453 +/- 0.00635\n", - " k-effective (Track-length) = 1.40907 +/- 0.00842\n", - " k-effective (Absorption) = 1.41404 +/- 0.00479\n", - " Combined k-effective = 1.41418 +/- 0.00459\n", + " k-effective (Collision) = 1.42429 +/- 0.00588\n", + " k-effective (Track-length) = 1.41927 +/- 0.00803\n", + " k-effective (Absorption) = 1.42275 +/- 0.00472\n", + " Combined k-effective = 1.42368 +/- 0.00460\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n", " Creating state point openmc_simulation_n6.h5...\n" @@ -1079,36 +1069,18 @@ "cell_type": "code", "execution_count": 17, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/pshriwise/.pyenv/versions/3.9.1/lib/python3.9/site-packages/openmc/deplete/results.py:87: FutureWarning: The ResultsList.from_hdf5(...) method is no longer necessary and will be removed in a future version of OpenMC. Use Results(...) instead.\n", - " warn(\n" - ] - } - ], + "outputs": [], "source": [ - "results = openmc.deplete.ResultsList.from_hdf5(\"./depletion_results.h5\")" + "results = openmc.deplete.Results(\"./depletion_results.h5\")" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/pshriwise/.pyenv/versions/3.9.1/lib/python3.9/site-packages/openmc/deplete/results.py:240: FutureWarning: The get_eigenvalue(...) function has been renamed get_keff and will be removed in a future version of OpenMC.\n", - " warn(\"The get_eigenvalue(...) function has been renamed get_keff and \"\n" - ] - } - ], + "outputs": [], "source": [ - "time, k = results.get_eigenvalue()" + "time, k = results.get_keff()" ] }, { @@ -1128,13 +1100,13 @@ { "data": { "text/plain": [ - "array([[1.4618427 , 0.00459795],\n", - " [1.43996612, 0.00407154],\n", - " [1.4293619 , 0.0051392 ],\n", - " [1.4262837 , 0.00367395],\n", - " [1.41334423, 0.00460271],\n", - " [1.42301155, 0.0045317 ],\n", - " [1.41417596, 0.0045945 ]])" + "array([[1.46477526, 0.00392422],\n", + " [1.43890826, 0.00465543],\n", + " [1.43604211, 0.00493173],\n", + " [1.42958815, 0.00429288],\n", + " [1.42754967, 0.00463556],\n", + " [1.42575323, 0.00483288],\n", + " [1.42368305, 0.00459654]])" ] }, "execution_count": 20, @@ -1169,7 +1141,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", + "image/png": 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STzjp0pbJ8pJ1y6mrrjzxwSIiMYmyroCZ2X+fHilkZmvN7JL4QytvXYNj7DnYp/UHRCRxUUYNXQ9sBd4evu4HvhxbRClxT8f0spSqD4hIsqKMWbzU3S8ys/sAwsVpokwxIQW0ZbI01FTywjVNSYciIikXpUUwbmaVgAOYWSswFWtUKdCW6eSSDS1UV57srRwiIgsjym+hLwLfAk4zs78C/hP4TKxRlbkjfSNkjg6qPiAiReGEXUPufpuZ7QReTXAz2ZuAJ2KOq6y1T9cHtD6xiBSBQiuUfcfM1gG4+6Pu/mV3/xLBUpL3L1J8Zaltb5ZldVWcd+aypEMRESnYNXQH8FMz+5iZVZvZmWb2L8BfAe9cnPDKU1tHJ1s2rqCyouAs3SIiiyJvInD32wgWnF8L7AHaCdYh2OLuOxcnvPLzTNcQz3QNa1lKESkaJyoWnwdcAtwLjAKriDbkVPKYrg9o/QERKRaFagQ3Edw49sfu/lsErYMm4AEz+41Fiq/stGeyrFhSw7mrliYdiogIULhF8BDB7KPtAO4+6O4fBn4T+PhiBFdu3J32TJatm1ZgpvqAiBSHQpPO/V2e/buBl8cWURl7snOQQ30jqg+ISFHRba2LqC2j+oCIFB8lgkXU3pHljKY61q9oSDoUEZEZSgSLZGrK2ZbJsnWj6gMiUlzmlQjMbFdcgZS7x4/0kx0cU31ARIrOfFsE+lP2JLVnptcfUCIQkeIy30Tw77FEkQJtmSxrWxpYs1z1AREpLvNKBIXWMZb8JqecbR1ZTTstIkVJxeJF8PCzvfSPTKhbSESKkhLBIlB9QESK2XxHDS03sxfGFUy5astkOfu0pZzWWJd0KCIiz3HCRGBmPzOzZWbWAuwC/tHMPh/hczeb2REzeyjP+680s14zuz98fGL+4Re/8ckptu/rUn1ARIpWlBZBk7v3AW8GvurulwK/HuFztwCvO8Exv3T3F4ePT0U4Z8l5cH8PQ2OTSgQiUrSiJIIqMzsDeBvw3agndvdfAF0nG1i5aNubxQwu3aBEICLFKUoi+BTwA2Cvu283s40s3OL1W83sATP7npmdn+8gM7vWzHaY2Y6jR48u0FcvjrZMll85fRnLl9QkHYqIyJxOmAjc/Rvu/kJ3/+PwdYe7v2UBvnsXsM7dXwT8PfDtAjHc6O6b3X1za2vrAnz14hgZn2Tn093qFhKRonbCZSfNbAPwfmB97vHufuWpfHFYd5jevtvMrjezle7eeSrnLSa7nu5mbGJKw0ZFpKhFWX/428BNwHeAqYX6YjM7HTjs7m5mlxC0TrILdf5i0J7JUllhXLKhJelQRETyipIIRtz9i/M9sZndDrwSWGlm+4HrgGoAd78BuBp4j5lNAMPANe7u8/2eYtaWyXLB6iYa66qTDkVEJK8oieALZnYd8ENgdHqnuxecktrd336C978EfClKkKVocHSCB57p4dpXbEw6FBGRgqIkgguAdwCv4ljXkIevJY/t+7qYmHLVB0Sk6EVJBG8FNrr7WNzBlJP2TJbqSmPzOtUHRKS4RbmP4CGgOeY4yk57R5YL1y6nvqYy6VBERAqK0iJoBh41s+0cXyM4peGj5ax3aJyHDvTy/ledk3QoIiInFCURXBd7FGXmniezTDm6kUxESsIJE4G7/9zMVgEXh7vudfcj8YZV2to7stRVV/Ditc1JhyIickJRpqF+G3AvQdH4bcA9ZnZ13IGVsvZMls3rWqitUn1ARIpflK6hjwEXT7cCzKwV+DFwZ5yBlarswCiPHurnT197ZtKhiIhEEmXUUMWsrqBsxM+l0raOYOZt1QdEpFREaRF838x+ANwevv5N4HvxhVTa2jKdLK2t4oLVTUmHIiISSZRi8Z+a2ZuBl4W7bnT3b8UbVulqz2S5ZEMLVZVqNIlIaYgyDfVn3f0jwDfn2Cc5DvWO0NE5yG9dujbpUEREIovyZ+tr5th3+UIHUg7aO4KlFDS/kIiUkrwtAjN7D/DHwEYzezDnrUbgv+IOrBS17c3S3FDNr5y+LOlQREQiK9Q19DWCovBngI/m7O9399QvSj+XtkyWLRtWUFFhSYciIhJZ3q4hd+91933u/nZ3f4pg8RgHlpqZOsFneaZriAM9w1x2trqFRKS0RLmz+I1m9gTwJPBzYB8aPvocbZmwPrBRiUBESkuUYvFfAluAx919A/BqYFusUZWgtkyWlUtrOfu0pUmHIiIyL1ESwbi7Z4EKM6tw958Cm2OOq6S4O+2ZLJdtWoGZ6gMiUlqi3FncY2ZLgV8At5nZEWAw3rBKS+boIEf6RzVsVERKUpQWwVXAEPAnwPeBDPDGOIMqNe1hfUDzC4lIKYoyxcT0X/9TwK3xhlOa2jJZVjfXs7alIelQRETmTRPinKKpKWdbR5atqg+ISIlSIjhFjx7qp3toXMNGRaRk5U0EZvYf4fNnFy+c0jNz/4DqAyJSogrVCM4ws8uAK83sDuC4fg933xVrZCViW0eWDSuXcGZzfdKhiIiclEKJ4BPAx4E1wOdnvefAq+IKqlRMTE5xT0cXb3iRlqUUkdKVNxG4+53AnWb2cXf/9CLGVDIeeraP/tEJDRsVkZIWZfjop83sSuAV4a6fuft34w2rNLRnsgBsUaFYREpYlEnnPgN8AHgkfHzAzP46wuduNrMjZvZQnvfNzL5oZnvN7EEzu2i+wSetLdPJuauW0tpYm3QoIiInLcrw0dcDr3H3m939ZuB1wBsifO6W8Nh8LgfOCR/XAl+JcM6iMTYxxY593Vy2aWXSoYiInJKo9xE052w3RfmAu/8CKLSAzVXAVz2wDWg2szMixpO4B/b3MDw+qWGjIlLyokw69xngPjP7KcEQ0ldw/IplJ2s18EzO6/3hvoMLcO7Yte3NYgZbNigRiEhpi1Isvt3MfgZcHO76iLsfijWqWczsWoLuI9auLY7F0doynZx/5jKaGqqTDkVE5JRE6hpy94Puflf4WKgkcAA4K+f1mnDfXN9/o7tvdvfNra2tC/T1J29kfJL7nu5RfUBEykKScw3dBfxOOHpoC9Dr7iXRLbTzqW7GJqdUHxCRshClRnBSzOx24JXASjPbD1wHVAO4+w3A3cAVwF6C9Q7eHVcsC60t00llhXHx+pakQxEROWUFE4GZVQIPu/vz53tid3/7Cd534L3zPW8xaMtkedGaJpbWxpZHRUQWTcGuIXefBB4zs+Ko0BaBgdEJHtzfq/qAiJSNKH/SLgceNrN7yVmr2N2vjC2qIrb9yS4mp1z1AREpG1ESwcdjj6KEtGU6qams4CXrlicdiojIgohyH8HPzWwdcI67/9jMGoDK+EMrTu0dWS5a10xddWovgYiUmSiTzv0BcCfwD+Gu1cC3Y4ypaPUMjfHws31s3aj6gIiUjyj3EbwXeCnQB+DuTwCnxRlUsdrW0YU7XHa26gMiUj6iJIJRdx+bfmFmVQQrlKVOe6aT+upKXrSmOelQREQWTJRE8HMz+3Og3sxeA3wD+E68YRWn9o4sF29ooaYqyRuyRUQWVpTfaB8FjgK7gT8kuCP4L+IMqhgd7R/l8cMDbNVqZCJSZqKMGpoys1uBewi6hB4L7wpOlfaOYFlKrU8sIuXmhInAzF4P3ABkCNYj2GBmf+ju34s7uGLSnsnSWFfF+WcuSzoUEZEFFeWGss8Bv+buewHMbBPw70DKEkEnl25ooapS9QERKS9Rfqv1TyeBUAfQH1M8RenZnmH2ZYfYqvmFRKQM5W0RmNmbw80dZnY38C8ENYK3AtsXIbai0Z5RfUBEylehrqE35mwfBn413D4K1McWURFqy2RZ3lDN81Y1Jh2KiMiCy5sI3L1kFoqJk7vTnulk66YVVFRY0uGIiCy4KKOGNgDvB9bnHp+Waaif7hri2d4R3qP6gIiUqSijhr4N3ERwN/FUrNEUobawPqAbyUSkXEVJBCPu/sXYIylSbZkspzXWsql1SdKhiIjEIkoi+IKZXQf8EBid3unuu2KLqkgE9YEsLzt7BWaqD4hIeYqSCC4A3gG8imNdQx6+Lmt7jwzQOTCq9YlFpKxFSQRvBTbmTkWdFjP1Ad0/ICJlLMqdxQ8BzTHHUZTaMp2sWV7PWS0NSYciIhKbKC2CZuBRM9vO8TWCsh4+OjXlbOvo4rXnr0o6FBGRWEVJBNfFHkUReuRgH73D4+oWEpGyF2U9gp8vRiDFpn3m/gEVikWkvEW5s7ifY2sU1wDVwKC7l/XE/O0dWTa2LuH0prqkQxERiVWUFsHMTGsWDKa/CtgSZ1BJG5+c4p6OLG+6cHXSoYiIxG5eq6x44NvAa+MJpzjsPtDL4Nik7h8QkVSI0jX05pyXFcBmYCS2iIrAdH1gy8aWhCMREYlflBbBG3MeryVYneyqKCc3s9eZ2WNmttfMPjrH++8ys6Nmdn/4+P35BB+X9kyW55/eyIqltUmHIiISuyg1gpNal8DMKoEvA68B9gPbzewud39k1qFfd/f3ncx3xGF0YpLt+7r4rUvXJh2KiMiiKLRU5ScKfM7d/dMnOPclwF537wjPdwdBS2J2Iigq9z3dw+jElOoDIpIahbqGBud4APwe8JEI514NPJPzen+4b7a3mNmDZnanmZ0114nM7Foz22FmO44ePRrhq09eeyZLhcElG1QfEJF0yJsI3P1z0w/gRoJ1it8N3AFsXKDv/w6w3t1fCPwIuDVPLDe6+2Z339za2rpAXz239kyWF6xuoqm+OtbvEREpFgWLxWbWYmZ/CTxI0I10kbt/xN2PRDj3ASD3L/w14b4Z7p519+n5i/4v8JLIkcdgeGyS+57p1rQSIpIqeROBmf0tsJ1glNAF7v5Jd++ex7m3A+eY2QYzqwGuAe6a9R1n5Ly8Etgzj/MvuB1PdTE+6aoPiEiqFBo19CGC2Ub/AvhYzgpdRlAsLjjFhLtPmNn7gB8AlcDN7v6wmX0K2OHudwH/w8yuBCaALuBdp/Ifc6raMlmqKozN65YnGYaIyKLKmwjcfV53Hec5x93A3bP2fSJn+8+APzvV71kobZksLz6rmSW1USZlFREpD6f8y75c9I2Ms3t/D5epPiAiKaNEENr+ZBdTDltVHxCRlFEiCLVlstRUVXDh2uakQxERWVRKBKG2TJbN65ZTV12ZdCgiIotKiQDoHhxjz8E+1QdEJJWUCIBtHeGylEoEIpJCSgQE3UINNZW8cE1z0qGIiCw6JQKC9Ykv2dBCdaUuh4ikT+p/8x3pG2HvkQG2blS3kIikU+oTQXtYH9D8QiKSVkoEmSzL6qo478yCUyeJiJSt1CeCtkyWSzeuoLLCTnywiEgZSnUieKZriKe7hnT/gIikWqoTgeoDIiIpTwTbMllWLKnh3FVLkw5FRCQxqU0E7k5bJsuWTSvIWXRHRCR1UpsInuwc5FDfiOoDIpJ6qU0Eqg+IiARSmwjaMllOX1bH+hUNSYciIpKoVCYCd2dbJstlqg+IiKQzETx+eIDs4JimnRYRIaWJoC3TCWj9ARERSG0iyLK2pYE1y1UfEBFJXSKYnHK2dWQ1bFREJJS6RPDIs330j0yoW0hEJJS6RDBTH9BCNCIiQCoTQZazT1vKacvqkg5FRKQopCoRjE9OsX1fl+oDIiI5UpUIHtzfw9DYpLqFRERypCoRtO0N5hfaokQgIjIj1kRgZq8zs8fMbK+ZfXSO92vN7Ovh+/eY2fo442nvyHLeGctYvqQmzq8RESkpsSUCM6sEvgxcDpwHvN3Mzpt12O8B3e5+NvB3wGfjimdkfJIdT3Vr2KiIyCxxtgguAfa6e4e7jwF3AFfNOuYq4NZw+07g1RbTLHC7nu5mbGJKhWIRkVniTASrgWdyXu8P9815jLtPAL3Ac35Tm9m1ZrbDzHYcPXr0pIKprqzg157XysUbWk7q8yIi5aokisXufqO7b3b3za2trSd1jovXt/D/3n0Jy+qqFzg6EZHSFmciOACclfN6TbhvzmPMrApoArIxxiQiIrPEmQi2A+eY2QYzqwGuAe6adcxdwDvD7auBn7i7xxiTiIjMUhXXid19wszeB/wAqARudveHzexTwA53vwu4CfgnM9sLdBEkCxERWUSxJQIAd78buHvWvk/kbI8Ab40zBhERKawkisUiIhIfJQIRkZRTIhARSTklAhGRlLNSG61pZkeBp07y4yuBzgUMJ06lEqviXHilEqviXFhxx7nO3ee8I7fkEsGpMLMd7r456TiiKJVYFefCK5VYFefCSjJOdQ2JiKScEoGISMqlLRHcmHQA81AqsSrOhVcqsSrOhZVYnKmqEYiIyHOlrUUgIiKzKBGIiKRcahKBmb3OzB4zs71m9tGk45lmZmeZ2U/N7BEze9jMPhDu/6SZHTCz+8PHFUUQ6z4z2x3GsyPc12JmPzKzJ8Ln5UUQ5/Nyrtv9ZtZnZh8shmtqZjeb2REzeyhn35zX0AJfDP/NPmhmFyUc59+a2aNhLN8ys+Zw/3ozG865rjcsVpwFYs37szazPwuv6WNm9tqE4/x6Toz7zOz+cP/iXlN3L/sHwTTYGWAjUAM8AJyXdFxhbGcAF4XbjcDjwHnAJ4EPJx3frFj3AStn7fsb4KPh9keBzyYd5xw/+0PAumK4psArgIuAh050DYErgO8BBmwB7kk4zt8AqsLtz+bEuT73uCK5pnP+rMP/tx4AaoEN4e+FyqTinPX+54BPJHFN09IiuATY6+4d7j4G3AFclXBMALj7QXffFW73A3t47trOxewq4NZw+1bgTcmFMqdXAxl3P9m70ReUu/+CYO2NXPmu4VXAVz2wDWg2szOSitPdf+jB2uIA2whWHUxcnmuaz1XAHe4+6u5PAnsJfj/ErlCcZmbA24DbFyOW2dKSCFYDz+S83k8R/rI1s/XAhcA94a73hc3wm4uhywVw4IdmttPMrg33rXL3g+H2IWBVMqHldQ3H/89VbNcU8l/DYv53+7sErZVpG8zsPjP7uZm9PKmgZpnrZ12s1/TlwGF3fyJn36Jd07QkgqJnZkuBfwU+6O59wFeATcCLgYMEzcakvczdLwIuB95rZq/IfdODNm3RjEcOl0i9EvhGuKsYr+lxiu0azsXMPgZMALeFuw4Ca939QuB/Al8zs2VJxRcq+p/1LG/n+D9YFvWapiURHADOynm9JtxXFMysmiAJ3Obu3wRw98PuPunuU8A/skjN10Lc/UD4fAT4FkFMh6e7K8LnI8lF+ByXA7vc/TAU5zUN5buGRffv1szeBbwB+O0waRF2s2TD7Z0E/e7nJhYkBX/WxXhNq4A3A1+f3rfY1zQtiWA7cI6ZbQj/SrwGuCvhmICZvsGbgD3u/vmc/bl9wf8NeGj2ZxeTmS0xs8bpbYLC4UME1/Gd4WHvBP4tmQjndNxfWcV2TXPku4Z3Ab8Tjh7aAvTmdCEtOjN7HfC/gCvdfShnf6uZVYbbG4FzgI5kopyJKd/P+i7gGjOrNbMNBLHeu9jxzfLrwKPuvn96x6Jf08WqSif9IBiB8ThBZv1Y0vHkxPUygq6AB4H7w8cVwD8Bu8P9dwFnJBznRoLRFg8AD09fQ2AF8B/AE8CPgZakr2kY1xIgCzTl7Ev8mhIkpoPAOEH/9O/lu4YEo4W+HP6b3Q1sTjjOvQT969P/Tm8Ij31L+G/ifmAX8MYiuKZ5f9bAx8Jr+hhweZJxhvtvAf5o1rGLek01xYSISMqlpWtIRETyUCIQEUk5JQIRkZRTIhARSTklAhGRlFMiEBFJOSUCSS0zW5Ezze+hnGmLB8zs+hi+7xYze9LM/ijP+wPh86bpOBY6BpG56D4CEYL564EBd//fMX7HLcB33f3OPO8PuPvSfK9F4qIWgcgsZvZKM/tuuP1JM7vVzH5pZk+Z2ZvN7G8sWKDn++E8UZjZS8JZInea2Q+iTBcdTnnSHp7rL+P+7xLJR4lA5MQ2Aa8imMn0n4GfuvsFwDDw+jAZ/D1wtbu/BLgZ+KsI5/0C8JXwXInNISRSlXQAIiXge+4+bma7CVY8+364fzfBSlLPA14A/CiYQ5BKov1ifynBnDIQzI3z2QWMWSQyJQKRExsFcPcpMxv3Y4W1KYL/hwx42N23nsS5VaSTxKlrSOTUPQa0mtlWCNaXMLPzI3zuvwimRAf47biCEzkRJQKRU+TBOthXA581swcIpg6+LMJHP0Cw0ttuimO5REkpDR8VWSQnGj46x/EaPiqLQi0CkcXTC3w63w1l06ZvKAMOL0pUknpqEYiIpJxaBCIiKadEICKSckoEIiIpp0QgIpJy/x90PU0BFQzRMAAAAABJRU5ErkJggg==\n", 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" ] @@ -1281,7 +1253,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1331,7 +1303,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 29, @@ -1429,19 +1401,10 @@ "cell_type": "code", "execution_count": 34, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/pshriwise/.pyenv/versions/3.9.1/lib/python3.9/site-packages/openmc/deplete/coupled_operator.py:546: FutureWarning: The Operator(...) class has been renamed and will be removed in a future version of OpenMC. Use CoupledOperator(...) instead.\n", - " warn(\n" - ] - } - ], + "outputs": [], "source": [ "model = openmc.Model(geometry=geometry, settings=settings)\n", - "new_op = openmc.deplete.Operator(model, \"./chain_simple.xml\")" + "new_op = openmc.deplete.CoupledOperator(model, \"./chain_simple.xml\")" ] }, {