diff --git a/docs/source/pythonapi/examples/mgxs-part-i.ipynb b/docs/source/pythonapi/examples/mgxs-part-i.ipynb index 7c5132100..4477e323d 100644 --- a/docs/source/pythonapi/examples/mgxs-part-i.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-i.ipynb @@ -214,7 +214,6 @@ "source": [ "# Instantiate a Materials collection and export to XML\n", "materials_file = openmc.Materials([inf_medium])\n", - "materials_file.default_xs = '71c'\n", "materials_file.export_to_xml()" ] }, @@ -499,23 +498,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-22 21:03:18\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:40:13\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -525,12 +538,12 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading H1.71c from /home/romano/openmc/data/nndc_hdf5/H1_71c.h5\n", - " Reading O16.71c from /home/romano/openmc/data/nndc_hdf5/O16_71c.h5\n", - " Reading U235.71c from /home/romano/openmc/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /home/romano/openmc/data/nndc_hdf5/U238_71c.h5\n", - " Reading Zr90.71c from /home/romano/openmc/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for H1.71c\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for H1\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -600,20 +613,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.2300E-01 seconds\n", - " Reading cross sections = 1.6900E-01 seconds\n", - " Total time in simulation = 1.9882E+01 seconds\n", - " Time in transport only = 1.9869E+01 seconds\n", - " Time in inactive batches = 2.6590E+00 seconds\n", - " Time in active batches = 1.7223E+01 seconds\n", + " Total time for initialization = 3.9900E-01 seconds\n", + " Reading cross sections = 2.6500E-01 seconds\n", + " Total time in simulation = 1.1488E+01 seconds\n", + " Time in transport only = 1.1152E+01 seconds\n", + " Time in inactive batches = 1.2180E+00 seconds\n", + " Time in active batches = 1.0270E+01 seconds\n", " Time synchronizing fission bank = 4.0000E-03 seconds\n", - " Sampling source sites = 4.0000E-03 seconds\n", - " SEND/RECV source sites = 0.0000E+00 seconds\n", + " Sampling source sites = 3.0000E-03 seconds\n", + " SEND/RECV source sites = 1.0000E-03 seconds\n", " Time accumulating tallies = 0.0000E+00 seconds\n", - " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 2.0217E+01 seconds\n", - " Calculation Rate (inactive) = 9402.03 neutrons/second\n", - " Calculation Rate (active) = 5806.19 neutrons/second\n", + " Total time for finalization = 1.0000E-03 seconds\n", + " Total time elapsed = 1.1901E+01 seconds\n", + " Calculation Rate (inactive) = 20525.5 neutrons/second\n", + " Calculation Rate (active) = 9737.10 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -894,7 +907,7 @@ " 6.250000e-07\n", " total\n", " (((total / flux) - (absorption / flux)) - (sca...\n", - " -3.774758e-15\n", + " -2.886580e-15\n", " 0.011292\n", " \n", " \n", @@ -904,7 +917,7 @@ " 2.000000e+01\n", " total\n", " (((total / flux) - (absorption / flux)) - (sca...\n", - " 1.443290e-15\n", + " -5.551115e-16\n", " 0.002570\n", " \n", " \n", @@ -917,8 +930,8 @@ "1 1 6.25e-07 2.00e+01 total \n", "\n", " score mean std. dev. \n", - "0 (((total / flux) - (absorption / flux)) - (sca... -3.77e-15 1.13e-02 \n", - "1 (((total / flux) - (absorption / flux)) - (sca... 1.44e-15 2.57e-03 " + "0 (((total / flux) - (absorption / flux)) - (sca... -2.89e-15 1.13e-02 \n", + "1 (((total / flux) - (absorption / flux)) - (sca... -5.55e-16 2.57e-03 " ] }, "execution_count": 22, @@ -1167,21 +1180,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb index ca4832809..341969fbd 100644 --- a/docs/source/pythonapi/examples/mgxs-part-ii.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-ii.ipynb @@ -34,9 +34,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.py:878: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n", - " warnings.warn(self.msg_depr % (key, alt_key))\n", - "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.py:1357: UserWarning: This call to matplotlib.use() has no effect\n", + "/home/romano/miniconda3/envs/default/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning: This call to matplotlib.use() has no effect\n", "because the backend has already been chosen;\n", "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", "or matplotlib.backends is imported for the first time.\n", @@ -134,7 +132,6 @@ "source": [ "# Instantiate a Materials collection\n", "materials_file = openmc.Materials((fuel, water, zircaloy))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -428,24 +425,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.8.0\n", - " Git SHA1: be7e6e035d22944a8c80ca32f99935b6822854c9\n", - " Date/Time: 2016-08-10 15:31:07\n", - " MPI Processes: 1\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:55:07\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -455,12 +465,12 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/O16_71c.h5\n", - " Reading H1.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/H1_71c.h5\n", - " Reading Zr90.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -521,7 +531,7 @@ " 48/1 1.21610 1.22612 +/- 0.00251\n", " 49/1 1.22199 1.22602 +/- 0.00245\n", " 50/1 1.20860 1.22558 +/- 0.00243\n", - " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10052\n", + " Triggers unsatisfied, max unc./thresh. is 1.25496 for flux in tally 10057\n", " The estimated number of batches is 73\n", " Creating state point statepoint.050.h5...\n", " 51/1 1.21850 1.22541 +/- 0.00237\n", @@ -547,7 +557,7 @@ " 71/1 1.19720 1.22444 +/- 0.00195\n", " 72/1 1.23770 1.22465 +/- 0.00193\n", " 73/1 1.23894 1.22488 +/- 0.00191\n", - " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10052\n", + " Triggers unsatisfied, max unc./thresh. is 1.00243 for flux in tally 10057\n", " The estimated number of batches is 74\n", " 74/1 1.22437 1.22487 +/- 0.00188\n", " Triggers satisfied for batch 74\n", @@ -560,20 +570,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.0400E-01 seconds\n", - " Reading cross sections = 2.1100E-01 seconds\n", - " Total time in simulation = 2.8243E+02 seconds\n", - " Time in transport only = 2.8236E+02 seconds\n", - " Time in inactive batches = 1.8781E+01 seconds\n", - " Time in active batches = 2.6365E+02 seconds\n", - " Time synchronizing fission bank = 2.7000E-02 seconds\n", - " Sampling source sites = 1.7000E-02 seconds\n", + " Total time for initialization = 4.0300E-01 seconds\n", + " Reading cross sections = 2.6000E-01 seconds\n", + " Total time in simulation = 1.3275E+02 seconds\n", + " Time in transport only = 1.3260E+02 seconds\n", + " Time in inactive batches = 8.2130E+00 seconds\n", + " Time in active batches = 1.2454E+02 seconds\n", + " Time synchronizing fission bank = 3.0000E-02 seconds\n", + " Sampling source sites = 2.2000E-02 seconds\n", " SEND/RECV source sites = 8.0000E-03 seconds\n", - " Time accumulating tallies = 2.0000E-03 seconds\n", - " Total time for finalization = 2.4000E-02 seconds\n", - " Total time elapsed = 2.8293E+02 seconds\n", - " Calculation Rate (inactive) = 5324.53 neutrons/second\n", - " Calculation Rate (active) = 1517.17 neutrons/second\n", + " Time accumulating tallies = 3.0000E-03 seconds\n", + " Total time for finalization = 1.5000E-02 seconds\n", + " Total time elapsed = 1.3324E+02 seconds\n", + " Calculation Rate (inactive) = 12175.8 neutrons/second\n", + " Calculation Rate (active) = 3211.92 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -772,14 +782,6 @@ "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/shape_base.py:873: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n", - " return c.reshape(shape_out)\n" - ] - }, { "data": { "text/html": [ @@ -1170,239 +1172,169 @@ "text": [ "[ NORMAL ] Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.423123\tres = 0.000E+00\n", - "[ NORMAL ] Iteration 1:\tk_eff = 0.475921\tres = 5.769E-01\n", - "[ NORMAL ] Iteration 2:\tk_eff = 0.491443\tres = 1.248E-01\n", - "[ NORMAL ] Iteration 3:\tk_eff = 0.487441\tres = 3.261E-02\n", - "[ NORMAL ] Iteration 4:\tk_eff = 0.483949\tres = 8.144E-03\n", - "[ NORMAL ] Iteration 5:\tk_eff = 0.477326\tres = 7.164E-03\n", - "[ NORMAL ] Iteration 6:\tk_eff = 0.469012\tres = 1.369E-02\n", - "[ NORMAL ] Iteration 7:\tk_eff = 0.460422\tres = 1.742E-02\n", - "[ NORMAL ] Iteration 8:\tk_eff = 0.450721\tres = 1.832E-02\n", - "[ NORMAL ] Iteration 9:\tk_eff = 0.441532\tres = 2.107E-02\n", - "[ NORMAL ] Iteration 10:\tk_eff = 0.432168\tres = 2.039E-02\n", - "[ NORMAL ] Iteration 11:\tk_eff = 0.423131\tres = 2.121E-02\n", - "[ NORMAL ] Iteration 12:\tk_eff = 0.414705\tres = 2.091E-02\n", - "[ NORMAL ] Iteration 13:\tk_eff = 0.406942\tres = 1.991E-02\n", - "[ NORMAL ] Iteration 14:\tk_eff = 0.399627\tres = 1.872E-02\n", - "[ NORMAL ] Iteration 15:\tk_eff = 0.393329\tres = 1.798E-02\n", - "[ NORMAL ] Iteration 16:\tk_eff = 0.387699\tres = 1.576E-02\n", - "[ NORMAL ] Iteration 17:\tk_eff = 0.382948\tres = 1.431E-02\n", - "[ NORMAL ] Iteration 18:\tk_eff = 0.379028\tres = 1.225E-02\n", - "[ NORMAL ] Iteration 19:\tk_eff = 0.375934\tres = 1.024E-02\n", - "[ NORMAL ] Iteration 20:\tk_eff = 0.373784\tres = 8.161E-03\n", - "[ NORMAL ] Iteration 21:\tk_eff = 0.372654\tres = 5.719E-03\n", - "[ NORMAL ] Iteration 22:\tk_eff = 0.372273\tres = 3.023E-03\n", - "[ NORMAL ] Iteration 23:\tk_eff = 0.372879\tres = 1.024E-03\n", - "[ NORMAL ] Iteration 24:\tk_eff = 0.374353\tres = 1.629E-03\n", - "[ NORMAL ] Iteration 25:\tk_eff = 0.376678\tres = 3.951E-03\n", - "[ NORMAL ] Iteration 26:\tk_eff = 0.379854\tres = 6.212E-03\n", - "[ NORMAL ] Iteration 27:\tk_eff = 0.383870\tres = 8.432E-03\n", - "[ NORMAL ] Iteration 28:\tk_eff = 0.388663\tres = 1.057E-02\n", - "[ NORMAL ] Iteration 29:\tk_eff = 0.394216\tres = 1.249E-02\n", - "[ NORMAL ] Iteration 30:\tk_eff = 0.400506\tres = 1.429E-02\n", - "[ NORMAL ] Iteration 31:\tk_eff = 0.407501\tres = 1.596E-02\n", - "[ NORMAL ] Iteration 32:\tk_eff = 0.415145\tres = 1.747E-02\n", - "[ NORMAL ] Iteration 33:\tk_eff = 0.423426\tres = 1.876E-02\n", - "[ NORMAL ] Iteration 34:\tk_eff = 0.432299\tres = 1.995E-02\n", - "[ NORMAL ] Iteration 35:\tk_eff = 0.441713\tres = 2.095E-02\n", - "[ NORMAL ] Iteration 36:\tk_eff = 0.451665\tres = 2.178E-02\n", - "[ NORMAL ] Iteration 37:\tk_eff = 0.462081\tres = 2.253E-02\n", - "[ NORMAL ] Iteration 38:\tk_eff = 0.472951\tres = 2.306E-02\n", - "[ NORMAL ] Iteration 39:\tk_eff = 0.484220\tres = 2.352E-02\n", - "[ NORMAL ] Iteration 40:\tk_eff = 0.495861\tres = 2.383E-02\n", - "[ NORMAL ] Iteration 41:\tk_eff = 0.507836\tres = 2.404E-02\n", - "[ NORMAL ] Iteration 42:\tk_eff = 0.520110\tres = 2.415E-02\n", - "[ NORMAL ] Iteration 43:\tk_eff = 0.532648\tres = 2.417E-02\n", - "[ NORMAL ] Iteration 44:\tk_eff = 0.545418\tres = 2.411E-02\n", - "[ NORMAL ] Iteration 45:\tk_eff = 0.558388\tres = 2.398E-02\n", - "[ NORMAL ] Iteration 46:\tk_eff = 0.571526\tres = 2.378E-02\n", - "[ NORMAL ] Iteration 47:\tk_eff = 0.584802\tres = 2.353E-02\n", - "[ NORMAL ] Iteration 48:\tk_eff = 0.598189\tres = 2.323E-02\n", - "[ NORMAL ] Iteration 49:\tk_eff = 0.611657\tres = 2.289E-02\n", - "[ NORMAL ] Iteration 50:\tk_eff = 0.625182\tres = 2.252E-02\n", - "[ NORMAL ] Iteration 51:\tk_eff = 0.638738\tres = 2.211E-02\n", - "[ NORMAL ] Iteration 52:\tk_eff = 0.652302\tres = 2.168E-02\n", - "[ NORMAL ] Iteration 53:\tk_eff = 0.665851\tres = 2.124E-02\n", - "[ NORMAL ] Iteration 54:\tk_eff = 0.679364\tres = 2.077E-02\n", - "[ NORMAL ] Iteration 55:\tk_eff = 0.692821\tres = 2.029E-02\n", - "[ NORMAL ] Iteration 56:\tk_eff = 0.706204\tres = 1.981E-02\n", - "[ NORMAL ] Iteration 57:\tk_eff = 0.719496\tres = 1.932E-02\n", - "[ NORMAL ] Iteration 58:\tk_eff = 0.732679\tres = 1.882E-02\n", - "[ NORMAL ] Iteration 59:\tk_eff = 0.745740\tres = 1.832E-02\n", - "[ NORMAL ] Iteration 60:\tk_eff = 0.758664\tres = 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Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.366907\tres = 0.000E+00\n", - "[ NORMAL ] Iteration 1:\tk_eff = 0.391217\tres = 6.331E-01\n", - "[ NORMAL ] Iteration 2:\tk_eff = 0.393027\tres = 6.626E-02\n", - "[ NORMAL ] Iteration 3:\tk_eff = 0.381142\tres = 4.627E-03\n", - "[ NORMAL ] Iteration 4:\tk_eff = 0.375065\tres = 3.024E-02\n", - "[ NORMAL ] Iteration 5:\tk_eff = 0.369645\tres = 1.594E-02\n", - "[ NORMAL ] Iteration 6:\tk_eff = 0.365597\tres = 1.445E-02\n", - "[ NORMAL ] Iteration 7:\tk_eff = 0.363111\tres = 1.095E-02\n", - "[ NORMAL ] Iteration 8:\tk_eff = 0.361532\tres = 6.802E-03\n", - "[ NORMAL ] Iteration 9:\tk_eff = 0.361339\tres = 4.349E-03\n", - "[ NORMAL ] Iteration 10:\tk_eff = 0.362062\tres = 5.322E-04\n", - "[ NORMAL ] Iteration 11:\tk_eff = 0.363777\tres = 2.001E-03\n", - "[ NORMAL ] Iteration 12:\tk_eff = 0.366395\tres = 4.735E-03\n", - "[ NORMAL ] Iteration 13:\tk_eff = 0.369859\tres 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1.630E-05\n", + "[ NORMAL ] Iteration 219:\tk_eff = 1.223067\tres = 1.572E-05\n", + "[ NORMAL ] Iteration 220:\tk_eff = 1.223084\tres = 1.507E-05\n", + "[ NORMAL ] Iteration 221:\tk_eff = 1.223101\tres = 1.427E-05\n", + "[ NORMAL ] Iteration 222:\tk_eff = 1.223117\tres = 1.394E-05\n", + "[ NORMAL ] Iteration 223:\tk_eff = 1.223133\tres = 1.330E-05\n", + "[ NORMAL ] Iteration 224:\tk_eff = 1.223148\tres = 1.298E-05\n", + "[ NORMAL ] Iteration 225:\tk_eff = 1.223163\tres = 1.241E-05\n", + "[ NORMAL ] Iteration 226:\tk_eff = 1.223177\tres = 1.167E-05\n", + "[ NORMAL ] Iteration 227:\tk_eff = 1.223190\tres = 1.151E-05\n", + "[ NORMAL ] Iteration 228:\tk_eff = 1.223203\tres = 1.073E-05\n", + "[ NORMAL ] Iteration 229:\tk_eff = 1.223215\tres = 1.050E-05\n", + "[ NORMAL ] Iteration 230:\tk_eff = 1.223227\tres = 1.000E-05\n" ] } ], @@ -1876,8 +1699,8 @@ "output_type": "stream", "text": [ "openmc keff = 1.223474\n", - "openmoc keff = 1.223039\n", - "bias [pcm]: -43.5\n" + "openmoc keff = 1.223227\n", + "bias [pcm]: -24.7\n" ] } ], @@ -1962,9 +1785,9 @@ }, { "data": { - "image/png": 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uGBMPja289qn74wJgnaq+B2wJHAN8FYe6mXagsemrDaesPv54ZtIlmou2+yja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\ndf37FYqK/PXGBBoGhXDS0qj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YY2pZUDDGGFPLgoIxxphaFhSMMcbUsqBgjDGmlgUFY4wx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\nYwHYAAAAAElFTkSuQmCC\n", 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s//SZaStbolLd0ZyNidDkt7hJQUQeUNXTRGQ2zn0J4e0AqGonmuHGpEqwvEub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\nMFCsqjsBE3BulItm/z4mpXw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JTJkS/6yfL3cgm47VCW45MaZz8nhgn31yb8Eck1mWFIzp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\nRK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1973,7 +1796,7 @@ ], "source": [ "# Create a loglog plot of the U-235 continuous-energy fission cross section \n", - "plt.loglog(fission.xs.x, fission.xs.y, color='b', linewidth=1)\n", + "plt.loglog(fission.xs['294K'].x, fission.xs['294K'].y, color='b', linewidth=1)\n", "\n", "# Extract energy group bounds and MGXS values to plot\n", "nufission = xs_library[fuel_cell.id]['fission']\n", @@ -1983,7 +1806,7 @@ "y = np.squeeze(y)\n", "\n", "# Fix low energy bound to the value defined by the ACE library\n", - "x[0] = fission.xs.x[0]\n", + "x[0] = fission.xs['294K'].x[0]\n", "\n", "# Extend the mgxs values array for matplotlib's step plot\n", "y = np.insert(y, 0, y[0])\n", @@ -2046,9 +1869,9 @@ "outputs": [ { "data": { - "image/png": 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PGk5EmdWAc9tqbcACL2nQp8YjYgHgHCCAWcA4SU8MNp5ZkQab285rq4qmBT4ftja9vEvS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\nZlZT/x9xJfW8VvykSgAAAABJRU5ErkJggg==\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2088,21 +1911,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/mgxs-part-iii.ipynb b/docs/source/pythonapi/examples/mgxs-part-iii.ipynb index af9f2878f..0c8b843be 100644 --- a/docs/source/pythonapi/examples/mgxs-part-iii.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-iii.ipynb @@ -32,7 +32,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.py:1357: UserWarning: This call to matplotlib.use() has no effect\n", + "/home/romano/miniconda3/envs/default/lib/python3.5/site-packages/matplotlib/__init__.py:1350: UserWarning: This call to matplotlib.use() has no effect\n", "because the backend has already been chosen;\n", "matplotlib.use() must be called *before* pylab, matplotlib.pyplot,\n", "or matplotlib.backends is imported for the first time.\n", @@ -135,7 +135,6 @@ "source": [ "# Instantiate a Materials object\n", "materials_file = openmc.Materials((fuel, water, zircaloy))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -458,7 +457,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -716,24 +715,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.8.0\n", - " Git SHA1: be7e6e035d22944a8c80ca32f99935b6822854c9\n", - " Date/Time: 2016-08-10 18:33:28\n", - " MPI Processes: 1\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:44:00\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -743,13 +755,13 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/O16_71c.h5\n", - " Reading H1.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/H1_71c.h5\n", - " Reading B10.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/B10_71c.h5\n", - " Reading Zr90.71c from /Users/sam/git/openmc-sam/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading B10 from /home/romano/openmc/data/nndc_hdf5/B10.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -784,32 +796,32 @@ " 22/1 1.04175 1.02516 +/- 0.00588\n", " 23/1 1.01909 1.02469 +/- 0.00543\n", " 24/1 1.07119 1.02801 +/- 0.00603\n", - " 25/1 0.97414 1.02442 +/- 0.00666\n", - " 26/1 1.04709 1.02584 +/- 0.00639\n", - " 27/1 1.05872 1.02777 +/- 0.00631\n", - " 28/1 1.03930 1.02841 +/- 0.00598\n", - " 29/1 1.01488 1.02770 +/- 0.00570\n", - " 30/1 1.04513 1.02857 +/- 0.00548\n", - " 31/1 0.99538 1.02699 +/- 0.00545\n", - " 32/1 1.00106 1.02581 +/- 0.00532\n", - " 33/1 0.99389 1.02442 +/- 0.00527\n", - " 34/1 0.99938 1.02338 +/- 0.00516\n", - " 35/1 1.02161 1.02331 +/- 0.00495\n", - " 36/1 1.04084 1.02398 +/- 0.00480\n", - " 37/1 0.98801 1.02265 +/- 0.00481\n", - " 38/1 1.01348 1.02232 +/- 0.00464\n", - " 39/1 1.06693 1.02386 +/- 0.00474\n", - " 40/1 1.07729 1.02564 +/- 0.00491\n", - " 41/1 1.03191 1.02585 +/- 0.00475\n", - " 42/1 1.05209 1.02667 +/- 0.00468\n", - " 43/1 1.02997 1.02677 +/- 0.00453\n", - " 44/1 1.07288 1.02812 +/- 0.00460\n", - " 45/1 1.01268 1.02768 +/- 0.00449\n", - " 46/1 1.03759 1.02796 +/- 0.00437\n", - " 47/1 1.02620 1.02791 +/- 0.00425\n", - " 48/1 1.02509 1.02783 +/- 0.00414\n", - " 49/1 1.01043 1.02739 +/- 0.00406\n", - " 50/1 1.01457 1.02707 +/- 0.00397\n", + " 25/1 0.97445 1.02444 +/- 0.00665\n", + " 26/1 1.04737 1.02588 +/- 0.00638\n", + " 27/1 1.04656 1.02709 +/- 0.00612\n", + " 28/1 1.03464 1.02751 +/- 0.00578\n", + " 29/1 1.02528 1.02739 +/- 0.00547\n", + " 30/1 1.02799 1.02742 +/- 0.00519\n", + " 31/1 1.05846 1.02890 +/- 0.00516\n", + " 32/1 1.03811 1.02932 +/- 0.00493\n", + " 33/1 1.00894 1.02843 +/- 0.00480\n", + " 34/1 1.02049 1.02810 +/- 0.00460\n", + " 35/1 1.00690 1.02726 +/- 0.00450\n", + " 36/1 1.03129 1.02741 +/- 0.00432\n", + " 37/1 0.98864 1.02597 +/- 0.00440\n", + " 38/1 1.00017 1.02505 +/- 0.00434\n", + " 39/1 1.03635 1.02544 +/- 0.00421\n", + " 40/1 1.07090 1.02696 +/- 0.00434\n", + " 41/1 1.03141 1.02710 +/- 0.00420\n", + " 42/1 1.02624 1.02707 +/- 0.00406\n", + " 43/1 1.02668 1.02706 +/- 0.00394\n", + " 44/1 1.05940 1.02801 +/- 0.00394\n", + " 45/1 1.01149 1.02754 +/- 0.00385\n", + " 46/1 1.06958 1.02871 +/- 0.00392\n", + " 47/1 1.02674 1.02866 +/- 0.00381\n", + " 48/1 1.02542 1.02857 +/- 0.00371\n", + " 49/1 1.03516 1.02874 +/- 0.00362\n", + " 50/1 1.06818 1.02973 +/- 0.00366\n", " Creating state point statepoint.50.h5...\n", "\n", " ===========================================================================\n", @@ -819,27 +831,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.3000E-01 seconds\n", - " Reading cross sections = 2.2800E-01 seconds\n", - " Total time in simulation = 6.1235E+01 seconds\n", - " Time in transport only = 6.1207E+01 seconds\n", - " Time in inactive batches = 5.0280E+00 seconds\n", - " Time in active batches = 5.6207E+01 seconds\n", - " Time synchronizing fission bank = 7.0000E-03 seconds\n", + " Total time for initialization = 6.4800E-01 seconds\n", + " Reading cross sections = 4.8000E-01 seconds\n", + " Total time in simulation = 3.2830E+01 seconds\n", + " Time in transport only = 3.2659E+01 seconds\n", + " Time in inactive batches = 2.7510E+00 seconds\n", + " Time in active batches = 3.0079E+01 seconds\n", + " Time synchronizing fission bank = 9.0000E-03 seconds\n", " Sampling source sites = 4.0000E-03 seconds\n", - " SEND/RECV source sites = 1.0000E-03 seconds\n", - " Time accumulating tallies = 2.0000E-03 seconds\n", + " SEND/RECV source sites = 5.0000E-03 seconds\n", + " Time accumulating tallies = 1.0000E-03 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 6.1689E+01 seconds\n", - " Calculation Rate (inactive) = 4972.16 neutrons/second\n", - " Calculation Rate (active) = 1779.14 neutrons/second\n", + " Total time elapsed = 3.3498E+01 seconds\n", + " Calculation Rate (inactive) = 9087.60 neutrons/second\n", + " Calculation Rate (active) = 3324.58 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02489 +/- 0.00308\n", - " k-effective (Track-length) = 1.02707 +/- 0.00397\n", - " k-effective (Absorption) = 1.02637 +/- 0.00325\n", - " Combined k-effective = 1.02581 +/- 0.00264\n", + " k-effective (Collision) = 1.02763 +/- 0.00343\n", + " k-effective (Track-length) = 1.02973 +/- 0.00366\n", + " k-effective (Absorption) = 1.02732 +/- 0.00319\n", + " Combined k-effective = 1.02826 +/- 0.00259\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -955,13 +967,6 @@ "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sam/.local/lib/python2.7/site-packages/openmc-0.8.0-py2.7.egg/openmc/tallies.py:1944: RuntimeWarning: invalid value encountered in true_divide\n" - ] - }, { "data": { "text/html": [ @@ -983,16 +988,16 @@ " 10000\n", " 1\n", " U235\n", - " 8.046809e-03\n", - " 2.697198e-05\n", + " 8.055246e-03\n", + " 2.857567e-05\n", " \n", " \n", " 4\n", " 10000\n", " 1\n", " U238\n", - " 7.366624e-03\n", - " 4.255197e-05\n", + " 7.339215e-03\n", + " 4.349466e-05\n", " \n", " \n", " 5\n", @@ -1007,16 +1012,16 @@ " 10000\n", " 2\n", " U235\n", - " 3.614917e-01\n", - " 2.135233e-03\n", + " 3.615565e-01\n", + " 2.050486e-03\n", " \n", " \n", " 1\n", " 10000\n", " 2\n", " U238\n", - " 6.741607e-07\n", - " 3.924924e-09\n", + " 6.742638e-07\n", + " 3.795256e-09\n", " \n", " \n", " 2\n", @@ -1032,11 +1037,11 @@ ], "text/plain": [ " cell group in nuclide mean std. dev.\n", - "3 10000 1 U235 8.046809e-03 2.697198e-05\n", - "4 10000 1 U238 7.366624e-03 4.255197e-05\n", + "3 10000 1 U235 8.055246e-03 2.857567e-05\n", + "4 10000 1 U238 7.339215e-03 4.349466e-05\n", "5 10000 1 O16 0.000000e+00 0.000000e+00\n", - "0 10000 2 U235 3.614917e-01 2.135233e-03\n", - "1 10000 2 U238 6.741607e-07 3.924924e-09\n", + "0 10000 2 U235 3.615565e-01 2.050486e-03\n", + "1 10000 2 U238 6.742638e-07 3.795256e-09\n", "2 10000 2 O16 0.000000e+00 0.000000e+00" ] }, @@ -1074,13 +1079,13 @@ "\tDomain ID =\t10000\n", "\tNuclide =\tU235\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t8.05e-03 +/- 3.35e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t3.61e-01 +/- 5.91e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t8.06e-03 +/- 3.55e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t3.62e-01 +/- 5.67e-01%\n", "\n", "\tNuclide =\tU238\n", "\tCross Sections [cm^-1]:\n", - " Group 1 [6.25e-07 - 20.0 MeV]:\t7.37e-03 +/- 5.78e-01%\n", - " Group 2 [0.0 - 6.25e-07 MeV]:\t6.74e-07 +/- 5.82e-01%\n", + " Group 1 [6.25e-07 - 20.0 MeV]:\t7.34e-03 +/- 5.93e-01%\n", + " Group 2 [0.0 - 6.25e-07 MeV]:\t6.74e-07 +/- 5.63e-01%\n", "\n", "\tNuclide =\tO16\n", "\tCross Sections [cm^-1]:\n", @@ -1196,16 +1201,16 @@ " 10000\n", " 1\n", " U235\n", - " 0.074734\n", - " 0.000325\n", + " 0.074860\n", + " 0.000303\n", " \n", " \n", " 1\n", " 10000\n", " 1\n", " U238\n", - " 0.005977\n", - " 0.000034\n", + " 0.005952\n", + " 0.000035\n", " \n", " \n", " 2\n", @@ -1221,8 +1226,8 @@ ], "text/plain": [ " cell group in nuclide mean std. dev.\n", - "0 10000 1 U235 0.074734 0.000325\n", - "1 10000 1 U238 0.005977 0.000034\n", + "0 10000 1 U235 0.074860 0.000303\n", + "1 10000 1 U238 0.005952 0.000035\n", "2 10000 1 O16 0.000000 0.000000" ] }, @@ -1305,131 +1310,124 @@ "text": [ "[ NORMAL ] Importing ray tracing data from file...\n", "[ NORMAL ] Computing the eigenvalue...\n", - "[ NORMAL ] Iteration 0:\tk_eff = 0.823582\tres = 0.000E+00\n", - "[ NORMAL ] Iteration 1:\tk_eff = 0.780361\tres = 1.940E-01\n", - "[ NORMAL ] Iteration 2:\tk_eff = 0.739500\tres = 6.545E-02\n", - "[ NORMAL ] Iteration 3:\tk_eff = 0.710868\tres = 5.284E-02\n", - "[ NORMAL ] Iteration 4:\tk_eff = 0.689663\tres = 3.926E-02\n", - "[ NORMAL ] Iteration 5:\tk_eff = 0.675035\tres = 3.007E-02\n", - "[ NORMAL ] Iteration 6:\tk_eff = 0.665831\tres = 2.137E-02\n", - "[ NORMAL ] Iteration 7:\tk_eff = 0.661179\tres = 1.377E-02\n", - "[ NORMAL ] Iteration 8:\tk_eff = 0.660309\tres = 7.167E-03\n", - "[ NORMAL ] Iteration 9:\tk_eff = 0.662566\tres = 1.972E-03\n", - "[ NORMAL ] Iteration 10:\tk_eff = 0.667383\tres = 3.708E-03\n", - "[ NORMAL ] Iteration 11:\tk_eff = 0.674274\tres = 7.412E-03\n", - "[ NORMAL ] Iteration 12:\tk_eff = 0.682821\tres = 1.043E-02\n", - "[ NORMAL ] Iteration 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Iteration 66:\tk_eff = 1.020857\tres = 6.980E-04\n", + "[ NORMAL ] Iteration 67:\tk_eff = 1.021464\tres = 6.443E-04\n", + "[ NORMAL ] Iteration 68:\tk_eff = 1.022024\tres = 5.947E-04\n", + "[ NORMAL ] Iteration 69:\tk_eff = 1.022540\tres = 5.488E-04\n", + "[ NORMAL ] Iteration 70:\tk_eff = 1.023017\tres = 5.063E-04\n", + "[ NORMAL ] Iteration 71:\tk_eff = 1.023457\tres = 4.670E-04\n", + "[ NORMAL ] Iteration 72:\tk_eff = 1.023863\tres = 4.308E-04\n", + "[ NORMAL ] Iteration 73:\tk_eff = 1.024238\tres = 3.972E-04\n", + "[ NORMAL ] Iteration 74:\tk_eff = 1.024583\tres = 3.663E-04\n", + "[ NORMAL ] Iteration 75:\tk_eff = 1.024902\tres = 3.376E-04\n", + "[ NORMAL ] Iteration 76:\tk_eff = 1.025195\tres = 3.112E-04\n", + "[ NORMAL ] Iteration 77:\tk_eff = 1.025466\tres = 2.868E-04\n", + "[ NORMAL ] Iteration 78:\tk_eff = 1.025715\tres = 2.643E-04\n", + "[ NORMAL ] Iteration 79:\tk_eff = 1.025945\tres = 2.435E-04\n", + "[ NORMAL ] Iteration 80:\tk_eff = 1.026157\tres = 2.244E-04\n", + "[ NORMAL ] Iteration 81:\tk_eff = 1.026352\tres = 2.067E-04\n", + "[ NORMAL ] Iteration 82:\tk_eff = 1.026531\tres = 1.904E-04\n", + "[ NORMAL ] Iteration 83:\tk_eff = 1.026697\tres = 1.753E-04\n", + "[ NORMAL ] Iteration 84:\tk_eff = 1.026849\tres = 1.614E-04\n", + "[ NORMAL ] Iteration 85:\tk_eff = 1.026989\tres = 1.487E-04\n", + "[ NORMAL ] Iteration 86:\tk_eff = 1.027118\tres = 1.368E-04\n", + "[ NORMAL ] Iteration 87:\tk_eff = 1.027237\tres = 1.260E-04\n", + "[ NORMAL ] Iteration 88:\tk_eff = 1.027346\tres = 1.159E-04\n", + "[ NORMAL ] Iteration 89:\tk_eff = 1.027447\tres = 1.067E-04\n", + "[ NORMAL ] Iteration 90:\tk_eff = 1.027540\tres = 9.821E-05\n", + "[ NORMAL ] Iteration 91:\tk_eff = 1.027625\tres = 9.040E-05\n", + "[ NORMAL ] Iteration 92:\tk_eff = 1.027703\tres = 8.316E-05\n", + "[ NORMAL ] Iteration 93:\tk_eff = 1.027775\tres = 7.652E-05\n", + "[ NORMAL ] Iteration 94:\tk_eff = 1.027842\tres = 7.039E-05\n", + "[ NORMAL ] Iteration 95:\tk_eff = 1.027903\tres = 6.480E-05\n", + "[ NORMAL ] Iteration 96:\tk_eff = 1.027959\tres = 5.959E-05\n", + "[ NORMAL ] Iteration 97:\tk_eff = 1.028011\tres = 5.479E-05\n", + "[ NORMAL ] Iteration 98:\tk_eff = 1.028058\tres = 5.043E-05\n", + "[ NORMAL ] Iteration 99:\tk_eff = 1.028102\tres = 4.633E-05\n", + "[ NORMAL ] Iteration 100:\tk_eff = 1.028142\tres = 4.265E-05\n", + "[ NORMAL ] Iteration 101:\tk_eff = 1.028180\tres = 3.921E-05\n", + "[ NORMAL ] Iteration 102:\tk_eff = 1.028214\tres = 3.605E-05\n", + "[ NORMAL ] Iteration 103:\tk_eff = 1.028245\tres = 3.315E-05\n", + "[ NORMAL ] Iteration 104:\tk_eff = 1.028273\tres = 3.047E-05\n", + "[ NORMAL ] Iteration 105:\tk_eff = 1.028300\tres = 2.800E-05\n", + "[ NORMAL ] Iteration 106:\tk_eff = 1.028324\tres = 2.575E-05\n", + "[ NORMAL ] Iteration 107:\tk_eff = 1.028346\tres = 2.368E-05\n", + "[ NORMAL ] Iteration 108:\tk_eff = 1.028367\tres = 2.176E-05\n", + "[ NORMAL ] Iteration 109:\tk_eff = 1.028386\tres = 2.003E-05\n", + "[ NORMAL ] Iteration 110:\tk_eff = 1.028403\tres = 1.837E-05\n", + "[ NORMAL ] Iteration 111:\tk_eff = 1.028419\tres = 1.690E-05\n", + "[ NORMAL ] Iteration 112:\tk_eff = 1.028434\tres = 1.553E-05\n", + "[ NORMAL ] Iteration 113:\tk_eff = 1.028447\tres = 1.426E-05\n", + "[ NORMAL ] Iteration 114:\tk_eff = 1.028459\tres = 1.309E-05\n", + "[ NORMAL ] Iteration 115:\tk_eff = 1.028471\tres = 1.202E-05\n", + "[ NORMAL ] Iteration 116:\tk_eff = 1.028481\tres = 1.107E-05\n", + "[ NORMAL ] Iteration 117:\tk_eff = 1.028491\tres = 1.015E-05\n" ] } ], @@ -1461,9 +1459,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "openmc keff = 1.025806\n", - "openmoc keff = 1.026471\n", - "bias [pcm]: 66.5\n" + "openmc keff = 1.028263\n", + "openmoc keff = 1.028491\n", + "bias [pcm]: 22.8\n" ] } ], @@ -1571,7 +1569,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 43, @@ -1580,9 +1578,9 @@ }, { "data": { - "image/png": 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Pz0sEdLwMbA1M+1J4m80jEZEkgAIAfUVkrYh8B8D9AM4TkSUAvuqWCYkV9G0S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\nQkiM+D/axcWYV0AhpgAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1608,21 +1606,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.12" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/mgxs-part-iv.ipynb b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb index eaae92f7c..301bbf015 100644 --- a/docs/source/pythonapi/examples/mgxs-part-iv.ipynb +++ b/docs/source/pythonapi/examples/mgxs-part-iv.ipynb @@ -119,7 +119,6 @@ "source": [ "# Instantiate a Materials object\n", "materials_file = openmc.Materials((fuel, zircaloy, water))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -432,7 +431,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -578,7 +577,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "/home/romano/openmc/openmc/mgxs/library.py:312: RuntimeWarning: The P0 correction will be ignored since the scattering order 0 is greater than zero\n", + "/home/romano/openmc/openmc/mgxs/library.py:373: RuntimeWarning: The P0 correction will be ignored since the scattering order 0 is greater than zero\n", " warn(msg, RuntimeWarning)\n" ] } @@ -707,23 +706,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-23 16:50:57\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:48:01\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -733,13 +746,13 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /home/romano/openmc/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /home/romano/openmc/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /home/romano/openmc/data/nndc_hdf5/O16_71c.h5\n", - " Reading Zr90.71c from /home/romano/openmc/data/nndc_hdf5/Zr90_71c.h5\n", - " Reading H1.71c from /home/romano/openmc/data/nndc_hdf5/H1_71c.h5\n", - " Reading B10.71c from /home/romano/openmc/data/nndc_hdf5/B10_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading B10 from /home/romano/openmc/data/nndc_hdf5/B10.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -809,20 +822,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.6600E-01 seconds\n", - " Reading cross sections = 2.1400E-01 seconds\n", - " Total time in simulation = 7.0360E+01 seconds\n", - " Time in transport only = 7.0341E+01 seconds\n", - " Time in inactive batches = 9.6400E+00 seconds\n", - " Time in active batches = 6.0720E+01 seconds\n", - " Time synchronizing fission bank = 7.0000E-03 seconds\n", - " Sampling source sites = 5.0000E-03 seconds\n", - " SEND/RECV source sites = 2.0000E-03 seconds\n", + " Total time for initialization = 4.2200E-01 seconds\n", + " Reading cross sections = 2.8800E-01 seconds\n", + " Total time in simulation = 4.1409E+01 seconds\n", + " Time in transport only = 4.1265E+01 seconds\n", + " Time in inactive batches = 4.6120E+00 seconds\n", + " Time in active batches = 3.6797E+01 seconds\n", + " Time synchronizing fission bank = 9.0000E-03 seconds\n", + " Sampling source sites = 6.0000E-03 seconds\n", + " SEND/RECV source sites = 3.0000E-03 seconds\n", " Time accumulating tallies = 0.0000E+00 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 7.0764E+01 seconds\n", - " Calculation Rate (inactive) = 5186.72 neutrons/second\n", - " Calculation Rate (active) = 3293.81 neutrons/second\n", + " Total time elapsed = 4.1869E+01 seconds\n", + " Calculation Rate (inactive) = 10841.3 neutrons/second\n", + " Calculation Rate (active) = 5435.23 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -960,24 +973,10 @@ "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/romano/openmc/openmc/tallies.py:1941: RuntimeWarning: invalid value encountered in true_divide\n", - " self_rel_err = data['self']['std. dev.'] / data['self']['mean']\n", - "/home/romano/openmc/openmc/tallies.py:1942: RuntimeWarning: invalid value encountered in true_divide\n", - " other_rel_err = data['other']['std. dev.'] / data['other']['mean']\n", - "/home/romano/openmc/openmc/tallies.py:1943: RuntimeWarning: invalid value encountered in true_divide\n", - " new_tally._mean = data['self']['mean'] / data['other']['mean']\n" - ] - } - ], + "outputs": [], "source": [ "# 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", - " xs_ids='2m')\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.xml`\n", "mgxs_file.export_to_xml()" @@ -991,7 +990,7 @@ "\n", "Since this example is using material-wise macroscopic cross sections without considering that the neutron energy spectra and thus cross sections may be changing in space, we only need to modify the materials.xml and settings.xml files. If the material names and ids are not otherwise changed, then the geometry.xml file does not need to be modified from its continuous-energy form. The tallies.xml file will be left untouched as it currently contains the tally types that we will need to perform our comparison. \n", "\n", - "First we will create the new materials.xml file. Continuous-energy cross section nuclidic data sets are named with the nuclide name followed by a cross section identifier. For example, the data for hydrogen is accessed in OpenMC by the name `H-1.71c`. The cross-section identifier (in this case, `71c`) can be used to distinguish between different variants of `H-1` data, such as for different evaluations or temperatures. OpenMC multi-group libraries use the same convention of a name followed by a xs identifier. We will use a cross section identifier here of `2m`. Similar to how continuous-energy cross section libraries are named, the `openmc.Macroscopic` quantities below can either have their `xs_id` included (i.e., `'fuel.2m'`). An alternative is to leave this extension off and simply change the `default_xs` parameter to `.2m`." + "First we will create the new materials.xml file." ] }, { @@ -1023,7 +1022,6 @@ "\n", "# Finally, instantiate our Materials object\n", "materials_file = openmc.Materials((fuel, zircaloy, water))\n", - "materials_file.default_xs = '2m'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()\n" @@ -1082,23 +1080,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-23 16:52:09\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:48:43\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -1111,9 +1123,9 @@ " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Loading Cross Section Data...\n", - " Loading fuel.2m Data...\n", - " Loading zircaloy.2m Data...\n", - " Loading water.2m Data...\n", + " Loading fuel Data...\n", + " Loading zircaloy Data...\n", + " Loading water Data...\n", " Initializing source particles...\n", "\n", " ===========================================================================\n", @@ -1122,56 +1134,56 @@ "\n", " Bat./Gen. k Average k \n", " ========= ======== ==================== \n", - " 1/1 0.99367 \n", - " 2/1 1.03173 \n", - " 3/1 1.01999 \n", - " 4/1 1.01421 \n", - " 5/1 1.03980 \n", - " 6/1 1.04540 \n", - " 7/1 1.04199 \n", - " 8/1 1.02680 \n", - " 9/1 1.01267 \n", - " 10/1 1.03420 \n", - " 11/1 1.05773 \n", - " 12/1 1.03475 1.04624 +/- 0.01149\n", - " 13/1 1.03632 1.04293 +/- 0.00741\n", - " 14/1 0.99297 1.03044 +/- 0.01355\n", - " 15/1 1.02413 1.02918 +/- 0.01057\n", - " 16/1 1.02359 1.02825 +/- 0.00868\n", - " 17/1 0.99913 1.02409 +/- 0.00843\n", - " 18/1 1.01493 1.02294 +/- 0.00739\n", - " 19/1 1.03010 1.02374 +/- 0.00657\n", - " 20/1 1.04890 1.02626 +/- 0.00639\n", - " 21/1 1.01267 1.02502 +/- 0.00591\n", - " 22/1 1.02637 1.02513 +/- 0.00540\n", - " 23/1 1.01374 1.02426 +/- 0.00504\n", - " 24/1 1.06661 1.02728 +/- 0.00556\n", - " 25/1 1.03212 1.02760 +/- 0.00519\n", - " 26/1 1.05433 1.02927 +/- 0.00513\n", - " 27/1 0.99891 1.02749 +/- 0.00514\n", - " 28/1 1.00616 1.02630 +/- 0.00499\n", - " 29/1 1.04583 1.02733 +/- 0.00483\n", - " 30/1 1.01512 1.02672 +/- 0.00462\n", - " 31/1 0.98104 1.02455 +/- 0.00491\n", - " 32/1 1.04202 1.02534 +/- 0.00474\n", - " 33/1 1.00779 1.02458 +/- 0.00460\n", - " 34/1 1.02450 1.02457 +/- 0.00440\n", - " 35/1 0.98882 1.02314 +/- 0.00446\n", - " 36/1 1.01541 1.02285 +/- 0.00429\n", - " 37/1 1.02050 1.02276 +/- 0.00413\n", - " 38/1 1.03573 1.02322 +/- 0.00401\n", - " 39/1 1.03649 1.02368 +/- 0.00389\n", - " 40/1 1.01434 1.02337 +/- 0.00378\n", - " 41/1 1.02345 1.02337 +/- 0.00365\n", - " 42/1 1.01900 1.02323 +/- 0.00354\n", - " 43/1 1.01450 1.02297 +/- 0.00344\n", - " 44/1 1.03127 1.02321 +/- 0.00335\n", - " 45/1 1.01598 1.02301 +/- 0.00326\n", - " 46/1 1.00851 1.02260 +/- 0.00319\n", - " 47/1 1.03406 1.02291 +/- 0.00312\n", - " 48/1 1.02373 1.02294 +/- 0.00303\n", - " 49/1 1.04066 1.02339 +/- 0.00299\n", - " 50/1 1.02011 1.02331 +/- 0.00292\n", + " 1/1 0.99122 \n", + " 2/1 1.03963 \n", + " 3/1 1.01551 \n", + " 4/1 1.03582 \n", + " 5/1 0.99023 \n", + " 6/1 1.00419 \n", + " 7/1 1.02047 \n", + " 8/1 1.05456 \n", + " 9/1 1.01063 \n", + " 10/1 1.03370 \n", + " 11/1 1.04616 \n", + " 12/1 1.04458 1.04537 +/- 0.00079\n", + " 13/1 1.02171 1.03748 +/- 0.00790\n", + " 14/1 1.02060 1.03326 +/- 0.00700\n", + " 15/1 1.01653 1.02992 +/- 0.00637\n", + " 16/1 1.02956 1.02986 +/- 0.00520\n", + " 17/1 1.01145 1.02723 +/- 0.00512\n", + " 18/1 1.03774 1.02854 +/- 0.00463\n", + " 19/1 1.00829 1.02629 +/- 0.00466\n", + " 20/1 1.03624 1.02729 +/- 0.00429\n", + " 21/1 1.03296 1.02780 +/- 0.00391\n", + " 22/1 0.99315 1.02491 +/- 0.00459\n", + " 23/1 0.99628 1.02271 +/- 0.00476\n", + " 24/1 1.04034 1.02397 +/- 0.00459\n", + " 25/1 1.02523 1.02406 +/- 0.00427\n", + " 26/1 1.07905 1.02749 +/- 0.00527\n", + " 27/1 1.01678 1.02686 +/- 0.00499\n", + " 28/1 1.01817 1.02638 +/- 0.00473\n", + " 29/1 1.03293 1.02672 +/- 0.00449\n", + " 30/1 1.01224 1.02600 +/- 0.00432\n", + " 31/1 1.01524 1.02549 +/- 0.00414\n", + " 32/1 1.00996 1.02478 +/- 0.00401\n", + " 33/1 1.05545 1.02612 +/- 0.00406\n", + " 34/1 1.02082 1.02589 +/- 0.00389\n", + " 35/1 0.99120 1.02451 +/- 0.00398\n", + " 36/1 1.03012 1.02472 +/- 0.00383\n", + " 37/1 1.01179 1.02424 +/- 0.00372\n", + " 38/1 1.04023 1.02481 +/- 0.00363\n", + " 39/1 1.05876 1.02598 +/- 0.00369\n", + " 40/1 0.99332 1.02490 +/- 0.00373\n", + " 41/1 1.05319 1.02581 +/- 0.00372\n", + " 42/1 1.03381 1.02606 +/- 0.00361\n", + " 43/1 1.00607 1.02545 +/- 0.00355\n", + " 44/1 1.03957 1.02587 +/- 0.00347\n", + " 45/1 1.02472 1.02584 +/- 0.00337\n", + " 46/1 1.00948 1.02538 +/- 0.00331\n", + " 47/1 1.02380 1.02534 +/- 0.00322\n", + " 48/1 1.05392 1.02609 +/- 0.00322\n", + " 49/1 1.01171 1.02572 +/- 0.00316\n", + " 50/1 1.03942 1.02606 +/- 0.00310\n", " Creating state point statepoint.50.h5...\n", "\n", " ===========================================================================\n", @@ -1181,27 +1193,27 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.6000E-02 seconds\n", - " Reading cross sections = 8.0000E-03 seconds\n", - " Total time in simulation = 5.5889E+01 seconds\n", - " Time in transport only = 5.5863E+01 seconds\n", - " Time in inactive batches = 7.1040E+00 seconds\n", - " Time in active batches = 4.8785E+01 seconds\n", - " Time synchronizing fission bank = 1.6000E-02 seconds\n", - " Sampling source sites = 1.0000E-02 seconds\n", - " SEND/RECV source sites = 6.0000E-03 seconds\n", - " Time accumulating tallies = 1.0000E-03 seconds\n", + " Total time for initialization = 4.1000E-02 seconds\n", + " Reading cross sections = 4.0000E-03 seconds\n", + " Total time in simulation = 3.1713E+01 seconds\n", + " Time in transport only = 3.1522E+01 seconds\n", + " Time in inactive batches = 3.8940E+00 seconds\n", + " Time in active batches = 2.7819E+01 seconds\n", + " Time synchronizing fission bank = 2.1000E-02 seconds\n", + " Sampling source sites = 1.2000E-02 seconds\n", + " SEND/RECV source sites = 9.0000E-03 seconds\n", + " Time accumulating tallies = 0.0000E+00 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 5.5976E+01 seconds\n", - " Calculation Rate (inactive) = 7038.29 neutrons/second\n", - " Calculation Rate (active) = 4099.62 neutrons/second\n", + " Total time elapsed = 3.1791E+01 seconds\n", + " Calculation Rate (inactive) = 12840.3 neutrons/second\n", + " Calculation Rate (active) = 7189.33 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", - " k-effective (Collision) = 1.02638 +/- 0.00260\n", - " k-effective (Track-length) = 1.02331 +/- 0.00292\n", - " k-effective (Absorption) = 1.02579 +/- 0.00132\n", - " Combined k-effective = 1.02558 +/- 0.00136\n", + " k-effective (Collision) = 1.02474 +/- 0.00282\n", + " k-effective (Track-length) = 1.02606 +/- 0.00310\n", + " k-effective (Absorption) = 1.02589 +/- 0.00165\n", + " Combined k-effective = 1.02601 +/- 0.00170\n", " Leakage Fraction = 0.00000 +/- 0.00000\n", "\n" ] @@ -1283,8 +1295,8 @@ "output_type": "stream", "text": [ "Continuous-Energy keff = 1.024295\n", - "Multi-Group keff = 1.025577\n", - "bias [pcm]: -128.2\n" + "Multi-Group keff = 1.026013\n", + "bias [pcm]: -171.8\n" ] } ], @@ -1381,7 +1393,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 40, @@ -1390,9 +1402,9 @@ }, { "data": { - "image/png": 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PBUnjPw0t8/dB0FX2r1zO7JUlNqAPyV97dMAOUWcGXyHqBHb8zSkbZC/vSzld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\nT9CAriiK4hP+P9HijwlUNymtAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1437,21 +1449,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/docs/source/pythonapi/examples/pandas-dataframes.ipynb b/docs/source/pythonapi/examples/pandas-dataframes.ipynb index 412013f2f..f913e941a 100644 --- a/docs/source/pythonapi/examples/pandas-dataframes.ipynb +++ b/docs/source/pythonapi/examples/pandas-dataframes.ipynb @@ -111,7 +111,6 @@ "source": [ "# Instantiate a Materials collection\n", "materials_file = openmc.Materials((fuel, water, zircaloy))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -370,7 +369,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -539,23 +538,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-23 16:36:04\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:39:27\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -565,13 +578,13 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /home/romano/openmc/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /home/romano/openmc/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /home/romano/openmc/data/nndc_hdf5/O16_71c.h5\n", - " Reading H1.71c from /home/romano/openmc/data/nndc_hdf5/H1_71c.h5\n", - " Reading B10.71c from /home/romano/openmc/data/nndc_hdf5/B10_71c.h5\n", - " Reading Zr90.71c from /home/romano/openmc/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading B10 from /home/romano/openmc/data/nndc_hdf5/B10.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -618,20 +631,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 4.2600E-01 seconds\n", - " Reading cross sections = 2.9500E-01 seconds\n", - " Total time in simulation = 1.1986E+01 seconds\n", - " Time in transport only = 1.1977E+01 seconds\n", - " Time in inactive batches = 1.8370E+00 seconds\n", - " Time in active batches = 1.0149E+01 seconds\n", - " Time synchronizing fission bank = 2.0000E-03 seconds\n", + " Total time for initialization = 4.4100E-01 seconds\n", + " Reading cross sections = 3.1500E-01 seconds\n", + " Total time in simulation = 5.7690E+00 seconds\n", + " Time in transport only = 5.7370E+00 seconds\n", + " Time in inactive batches = 7.9400E-01 seconds\n", + " Time in active batches = 4.9750E+00 seconds\n", + " Time synchronizing fission bank = 1.0000E-03 seconds\n", " Sampling source sites = 1.0000E-03 seconds\n", - " SEND/RECV source sites = 1.0000E-03 seconds\n", - " Time accumulating tallies = 0.0000E+00 seconds\n", + " SEND/RECV source sites = 0.0000E+00 seconds\n", + " Time accumulating tallies = 1.0000E-03 seconds\n", " Total time for finalization = 0.0000E+00 seconds\n", - " Total time elapsed = 1.2431E+01 seconds\n", - " Calculation Rate (inactive) = 6804.57 neutrons/second\n", - " Calculation Rate (active) = 3694.95 neutrons/second\n", + " Total time elapsed = 6.2280E+00 seconds\n", + " Calculation Rate (inactive) = 15743.1 neutrons/second\n", + " Calculation Rate (active) = 7537.69 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -744,10 +757,10 @@ "text": [ "[[[ 0.1501735 ]]\n", "\n", - " [[ 0.05936257]]\n", - "\n", " [[ 0.21402727]]\n", "\n", + " [[ 0.05936257]]\n", + "\n", " [[ 0.13436703]]]\n" ] } @@ -848,8 +861,8 @@ " 0.00e+00\n", " 6.25e-07\n", " fission\n", - " 3.52e-04\n", - " 3.39e-05\n", + " 2.32e-04\n", + " 4.97e-05\n", " \n", " \n", " 5\n", @@ -859,8 +872,8 @@ " 0.00e+00\n", " 6.25e-07\n", " nu-fission\n", - " 8.57e-04\n", - " 8.26e-05\n", + " 5.65e-04\n", + " 1.21e-04\n", " \n", " \n", " 6\n", @@ -870,8 +883,8 @@ " 6.25e-07\n", " 2.00e+01\n", " fission\n", - " 1.02e-04\n", - " 6.16e-06\n", + " 6.96e-05\n", + " 6.90e-06\n", " \n", " \n", " 7\n", @@ -881,8 +894,8 @@ " 6.25e-07\n", " 2.00e+01\n", " nu-fission\n", - " 2.70e-04\n", - " 1.61e-05\n", + " 1.86e-04\n", + " 1.90e-05\n", " \n", " \n", " 8\n", @@ -892,8 +905,8 @@ " 0.00e+00\n", " 6.25e-07\n", " fission\n", - " 6.09e-04\n", - " 6.55e-05\n", + " 2.43e-04\n", + " 3.24e-05\n", " \n", " \n", " 9\n", @@ -903,8 +916,8 @@ " 0.00e+00\n", " 6.25e-07\n", " nu-fission\n", - " 1.48e-03\n", - " 1.60e-04\n", + " 5.91e-04\n", + " 7.90e-05\n", " \n", " \n", " 10\n", @@ -914,8 +927,8 @@ " 6.25e-07\n", " 2.00e+01\n", " fission\n", - " 1.38e-04\n", - " 6.74e-06\n", + " 7.27e-05\n", + " 4.76e-06\n", " \n", " \n", " 11\n", @@ -925,8 +938,8 @@ " 6.25e-07\n", " 2.00e+01\n", " nu-fission\n", - " 3.65e-04\n", - " 1.88e-05\n", + " 1.93e-04\n", + " 1.14e-05\n", " \n", " \n", " 12\n", @@ -936,8 +949,8 @@ " 0.00e+00\n", " 6.25e-07\n", " fission\n", - " 6.23e-04\n", - " 5.16e-05\n", + " 2.61e-04\n", + " 4.48e-05\n", " \n", " \n", " 13\n", @@ -947,8 +960,8 @@ " 0.00e+00\n", " 6.25e-07\n", " nu-fission\n", - " 1.52e-03\n", - " 1.26e-04\n", + " 6.35e-04\n", + " 1.09e-04\n", " \n", " \n", " 14\n", @@ -958,8 +971,8 @@ " 6.25e-07\n", " 2.00e+01\n", " fission\n", - " 1.74e-04\n", - " 9.99e-06\n", + " 6.00e-05\n", + " 4.53e-06\n", " \n", " \n", " 15\n", @@ -969,8 +982,8 @@ " 6.25e-07\n", " 2.00e+01\n", " nu-fission\n", - " 4.58e-04\n", - " 2.68e-05\n", + " 1.59e-04\n", + " 1.17e-05\n", " \n", " \n", " 16\n", @@ -980,8 +993,8 @@ " 0.00e+00\n", " 6.25e-07\n", " fission\n", - " 6.94e-04\n", - " 8.68e-05\n", + " 2.23e-04\n", + " 2.89e-05\n", " \n", " \n", " 17\n", @@ -991,8 +1004,8 @@ " 0.00e+00\n", " 6.25e-07\n", " nu-fission\n", - " 1.69e-03\n", - " 2.12e-04\n", + " 5.43e-04\n", + " 7.04e-05\n", " \n", " \n", " 18\n", @@ -1002,8 +1015,8 @@ " 6.25e-07\n", " 2.00e+01\n", " fission\n", - " 1.75e-04\n", - " 1.10e-05\n", + " 7.93e-05\n", + " 7.77e-06\n", " \n", " \n", " 19\n", @@ -1013,8 +1026,8 @@ " 6.25e-07\n", " 2.00e+01\n", " nu-fission\n", - " 4.55e-04\n", - " 2.80e-05\n", + " 2.07e-04\n", + " 1.94e-05\n", " \n", " \n", "\n", @@ -1027,22 +1040,22 @@ "1 1 1 1 0.00e+00 6.25e-07 nu-fission 5.37e-04 \n", "2 1 1 1 6.25e-07 2.00e+01 fission 7.43e-05 \n", "3 1 1 1 6.25e-07 2.00e+01 nu-fission 1.97e-04 \n", - "4 1 2 1 0.00e+00 6.25e-07 fission 3.52e-04 \n", - "5 1 2 1 0.00e+00 6.25e-07 nu-fission 8.57e-04 \n", - "6 1 2 1 6.25e-07 2.00e+01 fission 1.02e-04 \n", - "7 1 2 1 6.25e-07 2.00e+01 nu-fission 2.70e-04 \n", - "8 1 3 1 0.00e+00 6.25e-07 fission 6.09e-04 \n", - "9 1 3 1 0.00e+00 6.25e-07 nu-fission 1.48e-03 \n", - "10 1 3 1 6.25e-07 2.00e+01 fission 1.38e-04 \n", - "11 1 3 1 6.25e-07 2.00e+01 nu-fission 3.65e-04 \n", - "12 1 4 1 0.00e+00 6.25e-07 fission 6.23e-04 \n", - "13 1 4 1 0.00e+00 6.25e-07 nu-fission 1.52e-03 \n", - "14 1 4 1 6.25e-07 2.00e+01 fission 1.74e-04 \n", - "15 1 4 1 6.25e-07 2.00e+01 nu-fission 4.58e-04 \n", - "16 1 5 1 0.00e+00 6.25e-07 fission 6.94e-04 \n", - "17 1 5 1 0.00e+00 6.25e-07 nu-fission 1.69e-03 \n", - "18 1 5 1 6.25e-07 2.00e+01 fission 1.75e-04 \n", - "19 1 5 1 6.25e-07 2.00e+01 nu-fission 4.55e-04 \n", + "4 1 2 1 0.00e+00 6.25e-07 fission 2.32e-04 \n", + "5 1 2 1 0.00e+00 6.25e-07 nu-fission 5.65e-04 \n", + "6 1 2 1 6.25e-07 2.00e+01 fission 6.96e-05 \n", + "7 1 2 1 6.25e-07 2.00e+01 nu-fission 1.86e-04 \n", + "8 1 3 1 0.00e+00 6.25e-07 fission 2.43e-04 \n", + "9 1 3 1 0.00e+00 6.25e-07 nu-fission 5.91e-04 \n", + "10 1 3 1 6.25e-07 2.00e+01 fission 7.27e-05 \n", + "11 1 3 1 6.25e-07 2.00e+01 nu-fission 1.93e-04 \n", + "12 1 4 1 0.00e+00 6.25e-07 fission 2.61e-04 \n", + "13 1 4 1 0.00e+00 6.25e-07 nu-fission 6.35e-04 \n", + "14 1 4 1 6.25e-07 2.00e+01 fission 6.00e-05 \n", + "15 1 4 1 6.25e-07 2.00e+01 nu-fission 1.59e-04 \n", + "16 1 5 1 0.00e+00 6.25e-07 fission 2.23e-04 \n", + "17 1 5 1 0.00e+00 6.25e-07 nu-fission 5.43e-04 \n", + "18 1 5 1 6.25e-07 2.00e+01 fission 7.93e-05 \n", + "19 1 5 1 6.25e-07 2.00e+01 nu-fission 2.07e-04 \n", "\n", " std. dev. \n", " \n", @@ -1050,22 +1063,22 @@ "1 8.06e-05 \n", "2 7.91e-06 \n", "3 1.96e-05 \n", - "4 3.39e-05 \n", - "5 8.26e-05 \n", - "6 6.16e-06 \n", - "7 1.61e-05 \n", - "8 6.55e-05 \n", - "9 1.60e-04 \n", - "10 6.74e-06 \n", - "11 1.88e-05 \n", - "12 5.16e-05 \n", - "13 1.26e-04 \n", - "14 9.99e-06 \n", - "15 2.68e-05 \n", - "16 8.68e-05 \n", - "17 2.12e-04 \n", - "18 1.10e-05 \n", - "19 2.80e-05 " + "4 4.97e-05 \n", + "5 1.21e-04 \n", + "6 6.90e-06 \n", + "7 1.90e-05 \n", + "8 3.24e-05 \n", + "9 7.90e-05 \n", + "10 4.76e-06 \n", + "11 1.14e-05 \n", + "12 4.48e-05 \n", + "13 1.09e-04 \n", + "14 4.53e-06 \n", + "15 1.17e-05 \n", + "16 2.89e-05 \n", + "17 7.04e-05 \n", + "18 7.77e-06 \n", + "19 1.94e-05 " ] }, "execution_count": 24, @@ -1095,7 +1108,7 @@ "data": { "image/png": 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xwMqm96uysk7qdBI7UHurB4oZAjeRzGzIGvxhTG1PuXc2J1Azq053w5hWA81r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\nJ/KLgSwAAAAASUVORK5CYII=\n", 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yPftC/PgVFScqRPv9PwjSxlxiduaWYrHTvXcO/F6fcaUTIhsN/A3wt8DfAYfn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\nyRsDKQZIfYpODDv5Ee+Ily6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WDt9JxAMVCEm4Wetn0a1FN98xJBo/NYbvgPYTfScRD1QgJOFmrZvFSS10BXWl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\nEpEKhIiIRPT/Abz6PSTJ+oGTAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, diff --git a/docs/source/pythonapi/examples/post-processing.ipynb b/docs/source/pythonapi/examples/post-processing.ipynb index 19182aa7a..a68ebb604 100644 --- a/docs/source/pythonapi/examples/post-processing.ipynb +++ b/docs/source/pythonapi/examples/post-processing.ipynb @@ -106,7 +106,6 @@ "source": [ "# Instantiate a Materials collection\n", "materials_file = openmc.Materials((fuel, water, zircaloy))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -339,7 +338,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -433,23 +432,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-22 21:40:25\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:30:57\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -459,13 +472,13 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /home/romano/openmc/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /home/romano/openmc/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /home/romano/openmc/data/nndc_hdf5/O16_71c.h5\n", - " Reading H1.71c from /home/romano/openmc/data/nndc_hdf5/H1_71c.h5\n", - " Reading B10.71c from /home/romano/openmc/data/nndc_hdf5/B10_71c.h5\n", - " Reading Zr90.71c from /home/romano/openmc/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading B10 from /home/romano/openmc/data/nndc_hdf5/B10.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -585,20 +598,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.5100E-01 seconds\n", - " Reading cross sections = 1.8600E-01 seconds\n", - " Total time in simulation = 3.1672E+02 seconds\n", - " Time in transport only = 3.1667E+02 seconds\n", - " Time in inactive batches = 1.0782E+01 seconds\n", - " Time in active batches = 3.0594E+02 seconds\n", - " Time synchronizing fission bank = 2.1000E-02 seconds\n", - " Sampling source sites = 1.2000E-02 seconds\n", - " SEND/RECV source sites = 9.0000E-03 seconds\n", - " Time accumulating tallies = 1.7000E-02 seconds\n", - " Total time for finalization = 1.8100E-01 seconds\n", - " Total time elapsed = 3.1729E+02 seconds\n", - " Calculation Rate (inactive) = 4637.36 neutrons/second\n", - " Calculation Rate (active) = 1470.89 neutrons/second\n", + " Total time for initialization = 4.4800E-01 seconds\n", + " Reading cross sections = 3.1000E-01 seconds\n", + " Total time in simulation = 3.4103E+02 seconds\n", + " Time in transport only = 3.4086E+02 seconds\n", + " Time in inactive batches = 4.8890E+00 seconds\n", + " Time in active batches = 3.3614E+02 seconds\n", + " Time synchronizing fission bank = 1.5000E-02 seconds\n", + " Sampling source sites = 1.1000E-02 seconds\n", + " SEND/RECV source sites = 4.0000E-03 seconds\n", + " Time accumulating tallies = 1.9000E-02 seconds\n", + " Total time for finalization = 1.8200E-01 seconds\n", + " Total time elapsed = 3.4170E+02 seconds\n", + " Calculation Rate (inactive) = 10227.0 neutrons/second\n", + " Calculation Rate (active) = 1338.71 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n", @@ -707,14 +720,14 @@ "text/plain": [ "array([[[ 0.40945685, 0. ]],\n", "\n", - " [[ 0.40939021, 0. ]],\n", + " [[ 0.41078582, 0. ]],\n", "\n", - " [[ 0.410625 , 0. ]],\n", + " [[ 0.40926432, 0. ]],\n", "\n", " ..., \n", - " [[ 0.41130501, 0. ]],\n", + " [[ 0.41362317, 0. ]],\n", "\n", - " [[ 0.41228849, 0. ]],\n", + " [[ 0.41335428, 0. ]],\n", "\n", " [[ 0.41420317, 0. ]]])" ] @@ -754,26 +767,26 @@ "text/plain": [ "(array([[[ 0.00454952, 0. ]],\n", " \n", - " [[ 0.00454878, 0. ]],\n", + " [[ 0.00456429, 0. ]],\n", " \n", - " [[ 0.0045625 , 0. ]],\n", + " [[ 0.00454738, 0. ]],\n", " \n", " ..., \n", - " [[ 0.00457006, 0. ]],\n", + " [[ 0.00459581, 0. ]],\n", " \n", - " [[ 0.00458098, 0. ]],\n", + " [[ 0.00459283, 0. ]],\n", " \n", " [[ 0.00460226, 0. ]]]),\n", " array([[[ 1.64748193e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.70922989e-05, 0.00000000e+00]],\n", + " [[ 1.74996463e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.67622385e-05, 0.00000000e+00]],\n", + " [[ 1.74392771e-05, 0.00000000e+00]],\n", " \n", " ..., \n", - " [[ 1.69274948e-05, 0.00000000e+00]],\n", + " [[ 1.73541566e-05, 0.00000000e+00]],\n", " \n", - " [[ 1.57842763e-05, 0.00000000e+00]],\n", + " [[ 1.67854889e-05, 0.00000000e+00]],\n", " \n", " [[ 2.06590062e-05, 0.00000000e+00]]]))" ] @@ -855,7 +868,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 24, @@ -864,9 +877,9 @@ }, { "data": { - "image/png": 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5wWkCkSo++wGPu8scNqZo1ELYKYlKIcad965Tdkbw+Ft87h/9CVtjs+QPn6N+K4qRVFAm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\na8T1IhU9TBs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YtwP0jil49TYSNiYaC8xiI1ElTHMjRPtWCGdBoe2X6OYihMs6jiLRroX4A/1X+VA6RYQK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\nl8J4Cpe/SdR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qUWM9BKc/isdYh6muBNGcDzU6CErINWJzbqCHr4R7tq6hJPpEDCk7MK2qwx/f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qYxdsNyiiu3cKbqMY5G3EC/3cmxqy+nwGQlO3geid4iCp77AqkoG0U6hdrgxxm5BlUvZBMfMkFc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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, diff --git a/docs/source/pythonapi/examples/tally-arithmetic.ipynb b/docs/source/pythonapi/examples/tally-arithmetic.ipynb index dfd493f16..763e80d20 100644 --- a/docs/source/pythonapi/examples/tally-arithmetic.ipynb +++ b/docs/source/pythonapi/examples/tally-arithmetic.ipynb @@ -105,7 +105,6 @@ "source": [ "# Instantiate a Materials collection\n", "materials_file = openmc.Materials((fuel, water, zircaloy))\n", - "materials_file.default_xs = '71c'\n", "\n", "# Export to \"materials.xml\"\n", "materials_file.export_to_xml()" @@ -339,7 +338,7 @@ "outputs": [ { "data": { - "image/png": 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+ "image/png": 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"text/plain": [ "" ] @@ -527,23 +526,37 @@ "output_type": "stream", "text": [ "\n", - " .d88888b. 888b d888 .d8888b.\n", - " d88P\" \"Y88b 8888b d8888 d88P Y88b\n", - " 888 888 88888b.d88888 888 888\n", - " 888 888 88888b. .d88b. 88888b. 888Y88888P888 888 \n", - " 888 888 888 \"88b d8P Y8b 888 \"88b 888 Y888P 888 888 \n", - " 888 888 888 888 88888888 888 888 888 Y8P 888 888 888\n", - " Y88b. .d88P 888 d88P Y8b. 888 888 888 \" 888 Y88b d88P\n", - " \"Y88888P\" 88888P\" \"Y8888 888 888 888 888 \"Y8888P\"\n", - "__________________888______________________________________________________\n", - " 888\n", - " 888\n", + " %%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%%%%%%%%%\n", + " ################## %%%%%%%%%%%%%%%%%%%%%%%\n", + " ################### %%%%%%%%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%%%%%%\n", + " ##################### %%%%%%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%%\n", + " ####################### %%%%%%%%%%%%%%%%%\n", + " ###################### %%%%%%%%%%%%%%%%%\n", + " #################### %%%%%%%%%%%%%%%%%\n", + " ################# %%%%%%%%%%%%%%%%%\n", + " ############### %%%%%%%%%%%%%%%%\n", + " ############ %%%%%%%%%%%%%%%\n", + " ######## %%%%%%%%%%%%%%\n", + " %%%%%%%%%%%\n", "\n", - " Copyright: 2011-2016 Massachusetts Institute of Technology\n", - " License: http://openmc.readthedocs.io/en/latest/license.html\n", - " Version: 0.7.1\n", - " Git SHA1: 3d68c07625e33cd64188df03ee03e9c31b3d4b74\n", - " Date/Time: 2016-07-22 21:39:46\n", + " | The OpenMC Monte Carlo Code\n", + " Copyright | 2011-2016 Massachusetts Institute of Technology\n", + " License | http://openmc.readthedocs.io/en/latest/license.html\n", + " Version | 0.8.0\n", + " Git SHA1 | fbebf7bf709fe2fe1813af95bff9b29c0d59312c\n", + " Date/Time | 2016-08-31 10:29:51\n", + " OpenMP Threads | 4\n", "\n", " ===========================================================================\n", " ========================> INITIALIZATION <=========================\n", @@ -553,13 +566,13 @@ " Reading geometry XML file...\n", " Reading cross sections XML file...\n", " Reading materials XML file...\n", - " Reading U235.71c from /home/romano/openmc/data/nndc_hdf5/U235_71c.h5\n", - " Reading U238.71c from /home/romano/openmc/data/nndc_hdf5/U238_71c.h5\n", - " Reading O16.71c from /home/romano/openmc/data/nndc_hdf5/O16_71c.h5\n", - " Reading H1.71c from /home/romano/openmc/data/nndc_hdf5/H1_71c.h5\n", - " Reading B10.71c from /home/romano/openmc/data/nndc_hdf5/B10_71c.h5\n", - " Reading Zr90.71c from /home/romano/openmc/data/nndc_hdf5/Zr90_71c.h5\n", - " Maximum neutron transport energy: 20.0000 MeV for U235.71c\n", + " Reading U235 from /home/romano/openmc/data/nndc_hdf5/U235.h5\n", + " Reading U238 from /home/romano/openmc/data/nndc_hdf5/U238.h5\n", + " Reading O16 from /home/romano/openmc/data/nndc_hdf5/O16.h5\n", + " Reading H1 from /home/romano/openmc/data/nndc_hdf5/H1.h5\n", + " Reading B10 from /home/romano/openmc/data/nndc_hdf5/B10.h5\n", + " Reading Zr90 from /home/romano/openmc/data/nndc_hdf5/Zr90.h5\n", + " Maximum neutron transport energy: 20.0000 MeV for U235\n", " Reading tallies XML file...\n", " Building neighboring cells lists for each surface...\n", " Initializing source particles...\n", @@ -599,20 +612,20 @@ "\n", " =======================> TIMING STATISTICS <=======================\n", "\n", - " Total time for initialization = 3.5600E-01 seconds\n", - " Reading cross sections = 2.3400E-01 seconds\n", - " Total time in simulation = 1.8333E+01 seconds\n", - " Time in transport only = 1.8325E+01 seconds\n", - " Time in inactive batches = 2.6950E+00 seconds\n", - " Time in active batches = 1.5638E+01 seconds\n", - " Time synchronizing fission bank = 1.0000E-03 seconds\n", - " Sampling source sites = 0.0000E+00 seconds\n", - " SEND/RECV source sites = 1.0000E-03 seconds\n", + " Total time for initialization = 4.3100E-01 seconds\n", + " Reading cross sections = 3.0500E-01 seconds\n", + " Total time in simulation = 8.9870E+00 seconds\n", + " Time in transport only = 8.9500E+00 seconds\n", + " Time in inactive batches = 1.1950E+00 seconds\n", + " Time in active batches = 7.7920E+00 seconds\n", + " Time synchronizing fission bank = 5.0000E-03 seconds\n", + " Sampling source sites = 5.0000E-03 seconds\n", + " SEND/RECV source sites = 0.0000E+00 seconds\n", " Time accumulating tallies = 0.0000E+00 seconds\n", " Total time for finalization = 1.0000E-03 seconds\n", - " Total time elapsed = 1.8711E+01 seconds\n", - " Calculation Rate (inactive) = 4638.22 neutrons/second\n", - " Calculation Rate (active) = 2398.00 neutrons/second\n", + " Total time elapsed = 9.4370E+00 seconds\n", + " Calculation Rate (inactive) = 10460.3 neutrons/second\n", + " Calculation Rate (active) = 4812.63 neutrons/second\n", "\n", " ============================> RESULTS <============================\n", "\n",