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gridley/Valar dose rate check.ipynb

Created April 9, 2025 02:16
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Valar dose rate check.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "59e95140-ff10-43bb-b44e-aa45419e2d6c",
"metadata": {},
"outputs": [],
"source": [
"from math import pi\n",
"\n",
"import openmc\n",
"import openmc.deplete\n",
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "38549387-547b-4ca0-9764-12e5e9742006",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" %%%%%%%%%%%%%%%\n",
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" %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n",
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" ############### %%%%%%%%%%%%%%%%%%%%%%%%\n",
" ################## %%%%%%%%%%%%%%%%%%%%%%%\n",
" ################### %%%%%%%%%%%%%%%%%%%%%%%\n",
" #################### %%%%%%%%%%%%%%%%%%%%%%\n",
" ##################### %%%%%%%%%%%%%%%%%%%%%\n",
" ###################### %%%%%%%%%%%%%%%%%%%%\n",
" ####################### %%%%%%%%%%%%%%%%%%\n",
" ####################### %%%%%%%%%%%%%%%%%\n",
" ###################### %%%%%%%%%%%%%%%%%\n",
" #################### %%%%%%%%%%%%%%%%%\n",
" ################# %%%%%%%%%%%%%%%%%\n",
" ############### %%%%%%%%%%%%%%%%\n",
" ############ %%%%%%%%%%%%%%%\n",
" ######## %%%%%%%%%%%%%%\n",
" %%%%%%%%%%%\n",
"\n",
" | The OpenMC Monte Carlo Code\n",
" Copyright | 2011-2025 MIT, UChicago Argonne LLC, and contributors\n",
" License | https://docs.openmc.org/en/latest/license.html\n",
" Version | 0.15.1-dev149\n",
" Commit Hash | 239f7fed5e39eadfdad4f47c08f3f7b633862ab9\n",
" Date/Time | 2025-04-08 20:24:17\n",
" OpenMP Threads | 14\n",
"\n",
" Reading settings XML file...\n",
" Reading cross sections XML file...\n",
" Reading materials XML file...\n",
" Reading geometry XML file...\n",
" Reading O16 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/O16.h5\n",
" Reading O17 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/O17.h5\n",
" Reading O18 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/O18.h5\n",
" Reading U234 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U234.h5\n",
" Reading U235 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U235.h5\n",
" Reading U236 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U236.h5\n",
" Reading U238 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U238.h5\n",
" Reading He3 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/He3.h5\n",
" Reading He4 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/He4.h5\n",
" Reading Cr50 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cr50.h5\n",
" Reading Cr52 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cr52.h5\n",
" Reading Cr53 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cr53.h5\n",
" Reading Cr54 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cr54.h5\n",
" Reading Fe54 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fe54.h5\n",
" Reading Fe56 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fe56.h5\n",
" Reading Fe57 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fe57.h5\n",
" Reading Fe58 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fe58.h5\n",
" Reading Zr90 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr90.h5\n",
" Reading Zr91 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr91.h5\n",
" Reading Zr92 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr92.h5\n",
" Reading Zr94 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr94.h5\n",
" Reading Zr96 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr96.h5\n",
" Reading Sn112 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn112.h5\n",
" Reading Sn114 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn114.h5\n",
" Reading Sn115 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn115.h5\n",
" Reading Sn116 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn116.h5\n",
" Reading Sn117 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn117.h5\n",
" Reading Sn118 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn118.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Zr96 at 294K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Sn119 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn119.h5\n",
" Reading Sn120 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn120.h5\n",
" Reading Sn122 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn122.h5\n",
" Reading Sn124 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn124.h5\n",
" Reading H1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/H1.h5\n",
" Reading H2 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/H2.h5\n",
" Reading B10 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/B10.h5\n",
" Reading B11 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/B11.h5\n",
" Reading c_H_in_H2O from\n",
" /Users/gavin/Code/endfb-viii.0-hdf5/neutron/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=216000.0 s, source=174.0\n",
" Reading H3 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/H3.h5\n",
" Reading Li6 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Li6.h5\n",
" Reading Li7 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Li7.h5\n",
" Reading Be7 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Be7.h5\n",
" Reading Be9 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Be9.h5\n",
" Reading C12 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/C12.h5\n",
" Reading C13 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/C13.h5\n",
" Reading N14 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/N14.h5\n",
" Reading N15 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/N15.h5\n",
" Reading F19 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/F19.h5\n",
" Reading Ne20 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ne20.h5\n",
" Reading Ne21 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ne21.h5\n",
" Reading Ne22 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ne22.h5\n",
" Reading Na22 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Na22.h5\n",
" Reading Na23 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Na23.h5\n",
" Reading Mg24 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mg24.h5\n",
" Reading Mg25 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mg25.h5\n",
" Reading Mg26 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mg26.h5\n",
" Reading Al26_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Al26_m1.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Na22 at 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Al27 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Al27.h5\n",
" Reading Si28 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Si28.h5\n",
" Reading Si29 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Si29.h5\n",
" Reading Si30 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Si30.h5\n",
" Reading Si31 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Si31.h5\n",
" Reading Si32 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Si32.h5\n",
" Reading P31 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/P31.h5\n",
" Reading S32 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/S32.h5\n",
" Reading S33 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/S33.h5\n",
" Reading S34 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/S34.h5\n",
" Reading S35 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/S35.h5\n",
" Reading S36 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/S36.h5\n",
" Reading Cl35 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cl35.h5\n",
" Reading Cl36 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cl36.h5\n",
" Reading Cl37 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cl37.h5\n",
" Reading Ar36 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar36.h5\n",
" Reading Ar37 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar37.h5\n",
" Reading Ar38 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar38.h5\n",
" Reading Ar39 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar39.h5\n",
" Reading Ar40 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar40.h5\n",
" Reading Ar41 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ar41.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ar36 at 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading K39 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/K39.h5\n",
" Reading K40 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/K40.h5\n",
" Reading K41 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/K41.h5\n",
" Reading Ca40 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca40.h5\n",
" Reading Ca41 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca41.h5\n",
" Reading Ca42 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca42.h5\n",
" Reading Ca43 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca43.h5\n",
" Reading Ca44 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca44.h5\n",
" Reading Ca45 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca45.h5\n",
" Reading Ca46 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca46.h5\n",
" Reading Ca47 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca47.h5\n",
" Reading Ca48 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ca48.h5\n",
" Reading Sc45 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sc45.h5\n",
" Reading Ti46 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ti46.h5\n",
" Reading Ti47 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ti47.h5\n",
" Reading Ti48 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ti48.h5\n",
" Reading Ti49 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ti49.h5\n",
" Reading Ti50 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ti50.h5\n",
" Reading V49 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/V49.h5\n",
" Reading V50 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/V50.h5\n",
" Reading V51 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/V51.h5\n",
" Reading Cr51 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cr51.h5\n",
" Reading Mn54 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mn54.h5\n",
" Reading Mn55 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mn55.h5\n",
" Reading Fe55 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fe55.h5\n",
" Reading Co58 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Co58.h5\n",
" Reading Co58_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Co58_m1.h5\n",
" Reading Co59 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Co59.h5\n",
" Reading Ni58 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni58.h5\n",
" Reading Ni59 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni59.h5\n",
" Reading Ni60 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni60.h5\n",
" Reading Ni61 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni61.h5\n",
" Reading Ni62 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni62.h5\n",
" Reading Ni63 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni63.h5\n",
" Reading Ni64 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ni64.h5\n",
" Reading Cu63 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cu63.h5\n",
" Reading Cu64 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cu64.h5\n",
" Reading Cu65 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cu65.h5\n",
" Reading Zn64 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn64.h5\n",
" Reading Zn65 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn65.h5\n",
" Reading Zn66 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn66.h5\n",
" Reading Zn67 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn67.h5\n",
" Reading Zn68 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn68.h5\n",
" Reading Zn69 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn69.h5\n",
" Reading Zn70 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zn70.h5\n",
" Reading Ga69 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ga69.h5\n",
" Reading Ga70 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ga70.h5\n",
" Reading Ga71 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ga71.h5\n",
" Reading Ge70 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge70.h5\n",
" Reading Ge71 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge71.h5\n",
" Reading Ge72 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge72.h5\n",
" Reading Ge73 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge73.h5\n",
" Reading Ge74 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge74.h5\n",
" Reading Ge75 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge75.h5\n",
" Reading Ge76 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ge76.h5\n",
" Reading As73 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/As73.h5\n",
" Reading As74 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/As74.h5\n",
" Reading As75 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/As75.h5\n",
" Reading Se74 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se74.h5\n",
" Reading Se75 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se75.h5\n",
" Reading Se76 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se76.h5\n",
" Reading Se77 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se77.h5\n",
" Reading Se78 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se78.h5\n",
" Reading Se79 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se79.h5\n",
" Reading Se80 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se80.h5\n",
" Reading Se81 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se81.h5\n",
" Reading Se82 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Se82.h5\n",
" Reading Br79 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Br79.h5\n",
" Reading Br80 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Br80.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Se79 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Se79 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Se79 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Se79 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Se79 at 1200K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Br81 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Br81.h5\n",
" Reading Kr78 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr78.h5\n",
" Reading Kr79 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr79.h5\n",
" Reading Kr80 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr80.h5\n",
" Reading Kr81 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr81.h5\n",
" Reading Kr82 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr82.h5\n",
" Reading Kr83 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr83.h5\n",
" Reading Kr84 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr84.h5\n",
" Reading Kr85 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr85.h5\n",
" Reading Kr86 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Kr86.h5\n",
" Reading Rb85 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rb85.h5\n",
" Reading Rb86 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rb86.h5\n",
" Reading Rb87 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rb87.h5\n",
" Reading Sr84 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr84.h5\n",
" Reading Sr85 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr85.h5\n",
" Reading Sr86 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr86.h5\n",
" Reading Sr87 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr87.h5\n",
" Reading Sr88 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr88.h5\n",
" Reading Sr89 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr89.h5\n",
" Reading Sr90 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sr90.h5\n",
" Reading Y89 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Y89.h5\n",
" Reading Y90 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Y90.h5\n",
" Reading Y91 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Y91.h5\n",
" Reading Zr93 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr93.h5\n",
" Reading Zr95 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Zr95.h5\n",
" Reading Nb93 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nb93.h5\n",
" Reading Nb94 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nb94.h5\n",
" Reading Nb95 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nb95.h5\n",
" Reading Mo92 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo92.h5\n",
" Reading Mo93 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo93.h5\n",
" Reading Mo94 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo94.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb94 at 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb95 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb95 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb95 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb95 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Nb95 at 1200K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Mo95 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo95.h5\n",
" Reading Mo96 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo96.h5\n",
" Reading Mo97 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo97.h5\n",
" Reading Mo98 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo98.h5\n",
" Reading Mo99 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo99.h5\n",
" Reading Mo100 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Mo100.h5\n",
" Reading Tc98 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tc98.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Mo99 at 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Tc99 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tc99.h5\n",
" Reading Ru96 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru96.h5\n",
" Reading Ru97 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru97.h5\n",
" Reading Ru98 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru98.h5\n",
" Reading Ru99 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru99.h5\n",
" Reading Ru100 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru100.h5\n",
" Reading Ru101 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru101.h5\n",
" Reading Ru102 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru102.h5\n",
" Reading Ru103 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru103.h5\n",
" Reading Ru104 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru104.h5\n",
" Reading Ru105 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru105.h5\n",
" Reading Ru106 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ru106.h5\n",
" Reading Rh103 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rh103.h5\n",
" Reading Rh104 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rh104.h5\n",
" Reading Rh105 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Rh105.h5\n",
" Reading Pd102 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd102.h5\n",
" Reading Pd103 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd103.h5\n",
" Reading Pd104 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd104.h5\n",
" Reading Pd105 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd105.h5\n",
" Reading Pd106 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd106.h5\n",
" Reading Pd107 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd107.h5\n",
" Reading Pd108 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd108.h5\n",
" Reading Pd109 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd109.h5\n",
" Reading Pd110 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pd110.h5\n",
" Reading Ag107 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag107.h5\n",
" Reading Ag108 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag108.h5\n",
" Reading Ag109 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag109.h5\n",
" Reading Ag110_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag110_m1.h5\n",
" Reading Ag111 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag111.h5\n",
" Reading Ag112 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag112.h5\n",
" Reading Ag113 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag113.h5\n",
" Reading Ag114 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag114.h5\n",
" Reading Ag115 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag115.h5\n",
" Reading Ag116 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag116.h5\n",
" Reading Ag117 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag117.h5\n",
" Reading Ag118_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ag118_m1.h5\n",
" Reading Cd106 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd106.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Ag118_m1 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cd106 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Cd107 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd107.h5\n",
" Reading Cd108 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd108.h5\n",
" Reading Cd109 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd109.h5\n",
" Reading Cd110 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd110.h5\n",
" Reading Cd111 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd111.h5\n",
" Reading Cd112 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd112.h5\n",
" Reading Cd113 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd113.h5\n",
" Reading Cd114 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd114.h5\n",
" Reading Cd115_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd115_m1.h5\n",
" Reading Cd116 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cd116.h5\n",
" Reading In113 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/In113.h5\n",
" Reading In114 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/In114.h5\n",
" Reading In115 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/In115.h5\n",
" Reading Sn113 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn113.h5\n",
" Reading Sn121_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn121_m1.h5\n",
" Reading Sn123 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn123.h5\n",
" Reading Sn125 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn125.h5\n",
" Reading Sn126 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sn126.h5\n",
" Reading Sb121 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb121.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Sn123 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Sb122 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb122.h5\n",
" Reading Sb123 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb123.h5\n",
" Reading Sb124 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb124.h5\n",
" Reading Sb125 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb125.h5\n",
" Reading Sb126 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sb126.h5\n",
" Reading Te120 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te120.h5\n",
" Reading Te121 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te121.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Te120 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Te120 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Te120 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Te120 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Te121_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te121_m1.h5\n",
" Reading Te122 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te122.h5\n",
" Reading Te123 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te123.h5\n",
" Reading Te124 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te124.h5\n",
" Reading Te125 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te125.h5\n",
" Reading Te126 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te126.h5\n",
" Reading Te127_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te127_m1.h5\n",
" Reading Te128 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te128.h5\n",
" Reading Te129_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te129_m1.h5\n",
" Reading Te130 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te130.h5\n",
" Reading Te131 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te131.h5\n",
" Reading Te131_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te131_m1.h5\n",
" Reading Te132 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Te132.h5\n",
" Reading I127 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I127.h5\n",
" Reading I128 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I128.h5\n",
" Reading I129 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I129.h5\n",
" Reading I130 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I130.h5\n",
" Reading I131 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I131.h5\n",
" Reading I132 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I132.h5\n",
" Reading I132_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I132_m1.h5\n",
" Reading I133 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I133.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide I131 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide I131 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide I131 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide I131 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide I131 at 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide I131 at 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading I134 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I134.h5\n",
" Reading I135 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/I135.h5\n",
" Reading Xe123 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe123.h5\n",
" Reading Xe124 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe124.h5\n",
" Reading Xe125 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe125.h5\n",
" Reading Xe126 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe126.h5\n",
" Reading Xe127 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe127.h5\n",
" Reading Xe128 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe128.h5\n",
" Reading Xe129 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe129.h5\n",
" Reading Xe130 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe130.h5\n",
" Reading Xe131 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe131.h5\n",
" Reading Xe132 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe132.h5\n",
" Reading Xe133 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe133.h5\n",
" Reading Xe134 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe134.h5\n",
" Reading Xe135 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe135.h5\n",
" Reading Xe136 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Xe136.h5\n",
" Reading Cs133 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cs133.h5\n",
" Reading Cs134 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cs134.h5\n",
" Reading Cs135 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cs135.h5\n",
" Reading Cs136 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cs136.h5\n",
" Reading Cs137 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cs137.h5\n",
" Reading Ba130 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba130.h5\n",
" Reading Ba131 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba131.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Xe133 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cs136 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Ba132 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba132.h5\n",
" Reading Ba133 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba133.h5\n",
" Reading Ba134 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba134.h5\n",
" Reading Ba135 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba135.h5\n",
" Reading Ba136 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba136.h5\n",
" Reading Ba137 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba137.h5\n",
" Reading Ba138 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba138.h5\n",
" Reading Ba139 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba139.h5\n",
" Reading Ba140 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ba140.h5\n",
" Reading La138 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/La138.h5\n",
" Reading La139 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/La139.h5\n",
" Reading La140 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/La140.h5\n",
" Reading Ce136 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce136.h5\n",
" Reading Ce137 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce137.h5\n",
" Reading Ce137_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce137_m1.h5\n",
" Reading Ce138 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce138.h5\n",
" Reading Ce139 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce139.h5\n",
" Reading Ce140 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce140.h5\n",
" Reading Ce141 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce141.h5\n",
" Reading Ce142 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce142.h5\n",
" Reading Ce143 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce143.h5\n",
" Reading Ce144 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ce144.h5\n",
" Reading Pr141 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pr141.h5\n",
" Reading Pr142 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pr142.h5\n",
" Reading Pr143 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pr143.h5\n",
" Reading Nd142 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd142.h5\n",
" Reading Nd143 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd143.h5\n",
" Reading Nd144 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd144.h5\n",
" Reading Nd145 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd145.h5\n",
" Reading Nd146 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd146.h5\n",
" Reading Nd147 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd147.h5\n",
" Reading Nd148 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd148.h5\n",
" Reading Nd149 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd149.h5\n",
" Reading Nd150 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Nd150.h5\n",
" Reading Pm143 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm143.h5\n",
" Reading Pm144 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm144.h5\n",
" Reading Pm145 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm145.h5\n",
" Reading Pm146 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm146.h5\n",
" Reading Pm147 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm147.h5\n",
" Reading Pm148 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm148.h5\n",
" Reading Pm148_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm148_m1.h5\n",
" Reading Pm149 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm149.h5\n",
" Reading Pm150 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm150.h5\n",
" Reading Pm151 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pm151.h5\n",
" Reading Sm144 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm144.h5\n",
" Reading Sm145 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm145.h5\n",
" Reading Sm146 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm146.h5\n",
" Reading Sm147 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm147.h5\n",
" Reading Sm148 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm148.h5\n",
" Reading Sm149 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm149.h5\n",
" Reading Sm150 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm150.h5\n",
" Reading Sm151 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm151.h5\n",
" Reading Sm152 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm152.h5\n",
" Reading Sm153 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm153.h5\n",
" Reading Sm154 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Sm154.h5\n",
" Reading Eu151 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu151.h5\n",
" Reading Eu152 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu152.h5\n",
" Reading Eu153 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu153.h5\n",
" Reading Eu154 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu154.h5\n",
" Reading Eu155 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu155.h5\n",
" Reading Eu156 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu156.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Eu156 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Eu157 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Eu157.h5\n",
" Reading Gd152 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd152.h5\n",
" Reading Gd153 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd153.h5\n",
" Reading Gd154 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd154.h5\n",
" Reading Gd155 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd155.h5\n",
" Reading Gd156 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd156.h5\n",
" Reading Gd157 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd157.h5\n",
" Reading Gd158 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd158.h5\n",
" Reading Gd159 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd159.h5\n",
" Reading Gd160 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Gd160.h5\n",
" Reading Tb158 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tb158.h5\n",
" Reading Tb159 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tb159.h5\n",
" Reading Tb160 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tb160.h5\n",
" Reading Tb161 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tb161.h5\n",
" Reading Dy154 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy154.h5\n",
" Reading Dy155 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy155.h5\n",
" Reading Dy156 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy156.h5\n",
" Reading Dy157 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy157.h5\n",
" Reading Dy158 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy158.h5\n",
" Reading Dy159 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy159.h5\n",
" Reading Dy160 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy160.h5\n",
" Reading Dy161 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy161.h5\n",
" Reading Dy162 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy162.h5\n",
" Reading Dy163 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy163.h5\n",
" Reading Dy164 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Dy164.h5\n",
" Reading Ho165 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ho165.h5\n",
" Reading Ho166_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ho166_m1.h5\n",
" Reading Er162 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er162.h5\n",
" Reading Er163 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er163.h5\n",
" Reading Er164 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er164.h5\n",
" Reading Er165 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er165.h5\n",
" Reading Er166 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er166.h5\n",
" Reading Er167 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er167.h5\n",
" Reading Er168 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er168.h5\n",
" Reading Er169 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er169.h5\n",
" Reading Er170 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Er170.h5\n",
" Reading Tm168 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tm168.h5\n",
" Reading Tm169 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tm169.h5\n",
" Reading Tm170 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tm170.h5\n",
" Reading Tm171 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tm171.h5\n",
" Reading Yb168 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb168.h5\n",
" Reading Yb169 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb169.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb168 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Yb170 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb170.h5\n",
" Reading Yb171 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb171.h5\n",
" Reading Yb172 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb172.h5\n",
" Reading Yb173 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb173.h5\n",
" Reading Yb174 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb174.h5\n",
" Reading Yb175 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb175.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb170 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb171 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb172 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb173 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb174 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Yb176 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Yb176.h5\n",
" Reading Lu175 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Lu175.h5\n",
" Reading Lu176 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Lu176.h5\n",
" Reading Hf174 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf174.h5\n",
" Reading Hf175 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf175.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Yb176 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Hf176 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf176.h5\n",
" Reading Hf177 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf177.h5\n",
" Reading Hf178 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf178.h5\n",
" Reading Hf179 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf179.h5\n",
" Reading Hf180 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf180.h5\n",
" Reading Hf181 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf181.h5\n",
" Reading Hf182 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hf182.h5\n",
" Reading Ta180 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ta180.h5\n",
" Reading Ta181 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ta181.h5\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf181 at\n",
" 2500K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at 600K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at\n",
" 1200K\n",
" WARNING: Negative value(s) found on probability table for nuclide Hf182 at\n",
" 2500K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Reading Ta182 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ta182.h5\n",
" Reading W180 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W180.h5\n",
" Reading W181 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W181.h5\n",
" Reading W182 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W182.h5\n",
" Reading W183 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W183.h5\n",
" Reading W184 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W184.h5\n",
" Reading W185 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W185.h5\n",
" Reading W186 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/W186.h5\n",
" Reading Re185 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Re185.h5\n",
" Reading Re186_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Re186_m1.h5\n",
" Reading Re187 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Re187.h5\n",
" Reading Os184 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os184.h5\n",
" Reading Os185 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os185.h5\n",
" Reading Os186 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os186.h5\n",
" Reading Os187 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os187.h5\n",
" Reading Os188 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os188.h5\n",
" Reading Os189 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os189.h5\n",
" Reading Os190 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os190.h5\n",
" Reading Os191 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os191.h5\n",
" Reading Os192 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Os192.h5\n",
" Reading Ir191 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ir191.h5\n",
" Reading Ir192 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ir192.h5\n",
" Reading Ir193 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ir193.h5\n",
" Reading Ir194_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ir194_m1.h5\n",
" Reading Pt190 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt190.h5\n",
" Reading Pt191 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt191.h5\n",
" Reading Pt192 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt192.h5\n",
" Reading Pt193 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt193.h5\n",
" Reading Pt194 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt194.h5\n",
" Reading Pt195 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt195.h5\n",
" Reading Pt196 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt196.h5\n",
" Reading Pt197 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt197.h5\n",
" Reading Pt198 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pt198.h5\n",
" Reading Au197 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Au197.h5\n",
" Reading Hg196 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg196.h5\n",
" Reading Hg197 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg197.h5\n",
" Reading Hg197_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg197_m1.h5\n",
" Reading Hg198 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg198.h5\n",
" Reading Hg199 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg199.h5\n",
" Reading Hg200 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg200.h5\n",
" Reading Hg201 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg201.h5\n",
" Reading Hg202 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg202.h5\n",
" Reading Hg203 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg203.h5\n",
" Reading Hg204 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Hg204.h5\n",
" Reading Tl203 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tl203.h5\n",
" Reading Tl204 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tl204.h5\n",
" Reading Tl205 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Tl205.h5\n",
" Reading Pb204 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pb204.h5\n",
" Reading Pb205 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pb205.h5\n",
" Reading Pb206 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pb206.h5\n",
" Reading Pb207 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pb207.h5\n",
" Reading Pb208 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pb208.h5\n",
" Reading Bi209 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bi209.h5\n",
" Reading Bi210_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bi210_m1.h5\n",
" Reading Po208 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Po208.h5\n",
" Reading Po209 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Po209.h5\n",
" Reading Po210 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Po210.h5\n",
" Reading Ra223 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ra223.h5\n",
" Reading Ra224 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ra224.h5\n",
" Reading Ra225 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ra225.h5\n",
" Reading Ra226 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ra226.h5\n",
" Reading Ac225 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ac225.h5\n",
" Reading Ac226 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ac226.h5\n",
" Reading Ac227 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Ac227.h5\n",
" Reading Th227 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th227.h5\n",
" Reading Th228 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th228.h5\n",
" Reading Th229 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th229.h5\n",
" Reading Th230 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th230.h5\n",
" Reading Th231 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th231.h5\n",
" Reading Th232 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th232.h5\n",
" Reading Th233 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th233.h5\n",
" Reading Th234 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Th234.h5\n",
" Reading Pa229 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pa229.h5\n",
" Reading Pa230 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pa230.h5\n",
" Reading Pa231 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pa231.h5\n",
" Reading Pa232 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pa232.h5\n",
" Reading Pa233 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pa233.h5\n",
" Reading U230 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U230.h5\n",
" Reading U231 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U231.h5\n",
" Reading U232 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U232.h5\n",
" Reading U233 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U233.h5\n",
" Reading U237 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U237.h5\n",
" Reading U239 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U239.h5\n",
" Reading U240 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U240.h5\n",
" Reading U241 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/U241.h5\n",
" Reading Np234 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np234.h5\n",
" Reading Np235 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np235.h5\n",
" Reading Np236 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np236.h5\n",
" Reading Np236_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np236_m1.h5\n",
" Reading Np237 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np237.h5\n",
" Reading Np238 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np238.h5\n",
" Reading Np239 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Np239.h5\n",
" Reading Pu236 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu236.h5\n",
" Reading Pu237 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu237.h5\n",
" Reading Pu238 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu238.h5\n",
" Reading Pu239 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu239.h5\n",
" Reading Pu240 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu240.h5\n",
" Reading Pu241 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu241.h5\n",
" Reading Pu242 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu242.h5\n",
" Reading Pu243 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu243.h5\n",
" Reading Pu244 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu244.h5\n",
" Reading Pu245 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu245.h5\n",
" Reading Pu246 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Pu246.h5\n",
" Reading Am240 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am240.h5\n",
" Reading Am241 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am241.h5\n",
" Reading Am242 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am242.h5\n",
" Reading Am242_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am242_m1.h5\n",
" Reading Am243 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am243.h5\n",
" Reading Am244 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am244.h5\n",
" Reading Am244_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Am244_m1.h5\n",
" Reading Cm240 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm240.h5\n",
" Reading Cm241 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm241.h5\n",
" Reading Cm242 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm242.h5\n",
" Reading Cm243 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm243.h5\n",
" Reading Cm244 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm244.h5\n",
" Reading Cm245 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm245.h5\n",
" Reading Cm246 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm246.h5\n",
" Reading Cm247 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm247.h5\n",
" Reading Cm248 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm248.h5\n",
" Reading Cm249 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm249.h5\n",
" Reading Cm250 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cm250.h5\n",
" Reading Bk245 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk245.h5\n",
" Reading Bk246 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk246.h5\n",
" Reading Bk247 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk247.h5\n",
" Reading Bk248 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk248.h5\n",
" Reading Bk249 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk249.h5\n",
" Reading Bk250 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Bk250.h5\n",
" Reading Cf246 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf246.h5\n",
" Reading Cf247 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf247.h5\n",
" Reading Cf248 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf248.h5\n",
" Reading Cf249 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf249.h5\n",
" Reading Cf250 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf250.h5\n",
" Reading Cf251 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf251.h5\n",
" Reading Cf252 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf252.h5\n",
" Reading Cf253 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf253.h5\n",
" Reading Cf254 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Cf254.h5\n",
" Reading Es251 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es251.h5\n",
" Reading Es252 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es252.h5\n",
" Reading Es253 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es253.h5\n",
" Reading Es254 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es254.h5\n",
" Reading Es254_m1 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es254_m1.h5\n",
" Reading Es255 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Es255.h5\n",
" Reading Fm255 from /Users/gavin/Code/endfb-viii.0-hdf5/neutron/Fm255.h5\n",
" Maximum neutron transport energy: 20000000 eV for O17\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
" WARNING: Negative value(s) found on probability table for nuclide Cf250 at 250K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cf250 at 294K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cf250 at 900K\n",
" WARNING: Negative value(s) found on probability table for nuclide Cf250 at\n",
" 1200K\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" Initializing source particles...\n",
"\n",
" ====================> K EIGENVALUE SIMULATION <====================\n",
"\n",
" Bat./Gen. k Entropy Average k \n",
" ========= ======== ======== ====================\n",
" 1/1 1.13515 6.31221\n",
" 2/1 1.23567 6.33398\n",
" 3/1 1.10746 6.33302\n",
" 4/1 1.17868 6.33778\n",
" 5/1 1.22383 6.30577\n",
" 6/1 1.11532 6.28119\n",
" 7/1 1.14560 6.31203\n",
" 8/1 1.22794 6.29805\n",
" 9/1 1.22619 6.27210\n",
" 10/1 1.18885 6.25098\n",
" 11/1 1.20384 6.30412\n",
" 12/1 1.19473 6.31072 1.19929 +/- 0.00456\n",
" 13/1 1.09315 6.27599 1.16391 +/- 0.03548\n",
" 14/1 1.18642 6.32664 1.16953 +/- 0.02571\n",
" 15/1 1.11187 6.32334 1.15800 +/- 0.02301\n",
" 16/1 1.18055 6.31479 1.16176 +/- 0.01916\n",
" 17/1 1.14219 6.30009 1.15896 +/- 0.01643\n",
" 18/1 1.16379 6.27525 1.15957 +/- 0.01425\n",
" 19/1 1.11727 6.29558 1.15487 +/- 0.01341\n",
" 20/1 1.17127 6.28222 1.15651 +/- 0.01211\n",
" 21/1 1.22453 6.33310 1.16269 +/- 0.01258\n",
" 22/1 1.20218 6.26412 1.16598 +/- 0.01194\n",
" 23/1 1.20903 6.27578 1.16929 +/- 0.01148\n",
" 24/1 1.17629 6.27245 1.16979 +/- 0.01064\n",
" 25/1 1.22855 6.31175 1.17371 +/- 0.01065\n",
" 26/1 1.07581 6.28558 1.16759 +/- 0.01169\n",
" 27/1 1.21510 6.28977 1.17039 +/- 0.01133\n",
" 28/1 1.17498 6.28089 1.17064 +/- 0.01069\n",
" 29/1 1.22600 6.33154 1.17355 +/- 0.01052\n",
" 30/1 1.19228 6.30010 1.17449 +/- 0.01002\n",
" 31/1 1.23843 6.27710 1.17754 +/- 0.01001\n",
" 32/1 1.15996 6.31017 1.17674 +/- 0.00958\n",
" 33/1 1.16004 6.32706 1.17601 +/- 0.00918\n",
" 34/1 1.21513 6.27838 1.17764 +/- 0.00894\n",
" 35/1 1.09600 6.29838 1.17437 +/- 0.00917\n",
" 36/1 1.07378 6.29224 1.17051 +/- 0.00963\n",
" 37/1 1.10926 6.26250 1.16824 +/- 0.00954\n",
" 38/1 1.23849 6.25134 1.17075 +/- 0.00953\n",
" 39/1 1.20812 6.26535 1.17204 +/- 0.00928\n",
" 40/1 1.19754 6.27826 1.17289 +/- 0.00901\n",
" 41/1 1.20007 6.28269 1.17376 +/- 0.00876\n",
" 42/1 1.13638 6.29448 1.17259 +/- 0.00856\n",
" 43/1 1.17032 6.30454 1.17253 +/- 0.00829\n",
" 44/1 1.11147 6.26202 1.17073 +/- 0.00824\n",
" 45/1 1.23575 6.29243 1.17259 +/- 0.00822\n",
" 46/1 1.14638 6.33180 1.17186 +/- 0.00802\n",
" 47/1 1.17072 6.30503 1.17183 +/- 0.00780\n",
" 48/1 1.09923 6.31459 1.16992 +/- 0.00783\n",
" 49/1 1.19846 6.29880 1.17065 +/- 0.00766\n",
" 50/1 1.18657 6.29587 1.17105 +/- 0.00748\n",
" 51/1 1.11648 6.32617 1.16972 +/- 0.00741\n",
" 52/1 1.12616 6.30184 1.16868 +/- 0.00731\n",
" 53/1 1.14422 6.28598 1.16811 +/- 0.00716\n",
" 54/1 1.10286 6.27149 1.16663 +/- 0.00715\n",
" 55/1 1.21172 6.27648 1.16763 +/- 0.00706\n",
" 56/1 1.11847 6.28588 1.16656 +/- 0.00699\n",
" 57/1 1.13817 6.28801 1.16596 +/- 0.00686\n",
" 58/1 1.13254 6.30868 1.16526 +/- 0.00676\n",
" 59/1 1.15852 6.33815 1.16512 +/- 0.00662\n",
" 60/1 1.18190 6.33472 1.16546 +/- 0.00649\n",
" 61/1 1.11297 6.27006 1.16443 +/- 0.00645\n",
" 62/1 1.14497 6.25103 1.16406 +/- 0.00633\n",
" 63/1 1.10999 6.31873 1.16304 +/- 0.00630\n",
" 64/1 1.14922 6.29550 1.16278 +/- 0.00618\n",
" 65/1 1.10422 6.27970 1.16171 +/- 0.00616\n",
" 66/1 1.18547 6.28694 1.16214 +/- 0.00607\n",
" 67/1 1.11737 6.33244 1.16135 +/- 0.00601\n",
" 68/1 1.11576 6.30863 1.16057 +/- 0.00596\n",
" 69/1 1.22090 6.32913 1.16159 +/- 0.00594\n",
" 70/1 1.19294 6.31418 1.16211 +/- 0.00587\n",
" 71/1 1.18485 6.30694 1.16249 +/- 0.00578\n",
" 72/1 1.10875 6.30869 1.16162 +/- 0.00575\n",
" 73/1 1.18690 6.29154 1.16202 +/- 0.00568\n",
" 74/1 1.19165 6.26900 1.16248 +/- 0.00561\n",
" 75/1 1.18472 6.29326 1.16283 +/- 0.00553\n",
" 76/1 1.18983 6.29440 1.16323 +/- 0.00546\n",
" 77/1 1.13811 6.31385 1.16286 +/- 0.00539\n",
" 78/1 1.08608 6.31068 1.16173 +/- 0.00543\n",
" 79/1 1.14379 6.30074 1.16147 +/- 0.00536\n",
" 80/1 1.08427 6.27948 1.16037 +/- 0.00539\n",
" 81/1 1.16806 6.30431 1.16048 +/- 0.00532\n",
" 82/1 1.10230 6.25912 1.15967 +/- 0.00531\n",
" 83/1 1.21253 6.31837 1.16039 +/- 0.00528\n",
" 84/1 1.19291 6.31089 1.16083 +/- 0.00523\n",
" 85/1 1.22098 6.31316 1.16163 +/- 0.00522\n",
" 86/1 1.15955 6.30648 1.16161 +/- 0.00515\n",
" 87/1 1.08297 6.31863 1.16058 +/- 0.00519\n",
" 88/1 1.16933 6.28037 1.16070 +/- 0.00512\n",
" 89/1 1.11405 6.30378 1.16011 +/- 0.00509\n",
" 90/1 1.18019 6.29194 1.16036 +/- 0.00503\n",
" 91/1 1.20654 6.27569 1.16093 +/- 0.00500\n",
" 92/1 1.17587 6.30682 1.16111 +/- 0.00494\n",
" 93/1 1.17157 6.32658 1.16124 +/- 0.00489\n",
" 94/1 1.13358 6.33333 1.16091 +/- 0.00484\n",
" 95/1 1.14844 6.30577 1.16076 +/- 0.00478\n",
" 96/1 1.19190 6.31013 1.16112 +/- 0.00474\n",
" 97/1 1.12725 6.31480 1.16073 +/- 0.00470\n",
" 98/1 1.23983 6.30820 1.16163 +/- 0.00474\n",
" 99/1 1.16010 6.32694 1.16161 +/- 0.00468\n",
" 100/1 1.19825 6.31614 1.16202 +/- 0.00465\n",
" Creating state point statepoint.100.h5...\n",
"\n",
" =======================> TIMING STATISTICS <=======================\n",
"\n",
" Total time for initialization = 1.3767e+00 seconds\n",
" Reading cross sections = 1.3721e+00 seconds\n",
" Total time in simulation = 2.4631e+01 seconds\n",
" Time in transport only = 2.4617e+01 seconds\n",
" Time in inactive batches = 9.7695e-02 seconds\n",
" Time in active batches = 2.4533e+01 seconds\n",
" Time synchronizing fission bank = 1.7502e-03 seconds\n",
" Sampling source sites = 1.4962e-03 seconds\n",
" SEND/RECV source sites = 1.8812e-04 seconds\n",
" Time accumulating tallies = 5.8706e-03 seconds\n",
" Time writing statepoints = 1.6753e-03 seconds\n",
" Total time for finalization = 8.7125e-05 seconds\n",
" Total time elapsed = 2.6248e+01 seconds\n",
" Calculation Rate (inactive) = 102360 particles/second\n",
" Calculation Rate (active) = 3668.48 particles/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.15973 +/- 0.00415\n",
" k-effective (Track-length) = 1.16202 +/- 0.00465\n",
" k-effective (Absorption) = 1.16339 +/- 0.00314\n",
" Combined k-effective = 1.16253 +/- 0.00290\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n",
" Creating state point openmc_simulation_n0.h5...\n",
"[openmc.deplete] t=216000.0 s, dt=1944000.0 s, source=174.0\n",
" Maximum neutron transport energy: 20000000 eV for O17\n",
" Initializing source particles...\n",
"\n",
" ====================> K EIGENVALUE SIMULATION <====================\n",
"\n",
" Bat./Gen. k Entropy Average k \n",
" ========= ======== ======== ====================\n",
" 1/1 1.09906 6.32288\n",
" 2/1 1.05653 6.28738\n",
" 3/1 1.16425 6.27078\n",
" 4/1 1.17444 6.32136\n",
" 5/1 1.18502 6.30598\n",
" 6/1 1.10220 6.29541\n",
" 7/1 1.17119 6.34572\n",
" 8/1 1.02189 6.26607\n",
" 9/1 1.14080 6.30556\n",
" 10/1 1.01963 6.31330\n",
" 11/1 1.09063 6.28811\n",
" 12/1 1.15671 6.31509 1.12367 +/- 0.03304\n",
" 13/1 1.09279 6.29556 1.11338 +/- 0.02167\n",
" 14/1 1.07675 6.29874 1.10422 +/- 0.01785\n",
" 15/1 1.20569 6.34421 1.12451 +/- 0.02456\n",
" 16/1 1.12260 6.30993 1.12420 +/- 0.02005\n",
" 17/1 1.17140 6.30938 1.13094 +/- 0.01824\n",
" 18/1 1.12433 6.31709 1.13011 +/- 0.01582\n",
" 19/1 1.13486 6.29561 1.13064 +/- 0.01396\n",
" 20/1 1.14168 6.33579 1.13174 +/- 0.01254\n",
" 21/1 1.09040 6.26951 1.12799 +/- 0.01195\n",
" 22/1 1.09817 6.32972 1.12550 +/- 0.01118\n",
" 23/1 1.12439 6.27874 1.12541 +/- 0.01029\n",
" 24/1 1.09740 6.30852 1.12341 +/- 0.00973\n",
" 25/1 1.13816 6.30450 1.12440 +/- 0.00911\n",
" 26/1 1.13767 6.31661 1.12523 +/- 0.00857\n",
" 27/1 1.11870 6.26214 1.12484 +/- 0.00806\n",
" 28/1 1.14699 6.33868 1.12607 +/- 0.00769\n",
" 29/1 1.07035 6.31522 1.12314 +/- 0.00785\n",
" 30/1 1.04614 6.28179 1.11929 +/- 0.00838\n",
" 31/1 1.09988 6.27939 1.11837 +/- 0.00802\n",
" 32/1 1.14919 6.29748 1.11977 +/- 0.00778\n",
" 33/1 1.11116 6.30749 1.11939 +/- 0.00744\n",
" 34/1 1.05671 6.29429 1.11678 +/- 0.00759\n",
" 35/1 1.15120 6.30750 1.11816 +/- 0.00741\n",
" 36/1 1.05510 6.30158 1.11573 +/- 0.00752\n",
" 37/1 1.14249 6.27245 1.11672 +/- 0.00730\n",
" 38/1 1.10410 6.24994 1.11627 +/- 0.00705\n",
" 39/1 1.13965 6.30087 1.11708 +/- 0.00685\n",
" 40/1 1.13447 6.30753 1.11766 +/- 0.00664\n",
" 41/1 1.13547 6.26663 1.11823 +/- 0.00645\n",
" 42/1 1.05235 6.29267 1.11617 +/- 0.00658\n",
" 43/1 1.19772 6.31091 1.11865 +/- 0.00684\n",
" 44/1 1.14575 6.27517 1.11944 +/- 0.00668\n",
" 45/1 1.12349 6.30818 1.11956 +/- 0.00649\n",
" 46/1 1.13727 6.28275 1.12005 +/- 0.00633\n",
" 47/1 1.08503 6.29676 1.11910 +/- 0.00622\n",
" 48/1 1.06817 6.29178 1.11776 +/- 0.00620\n",
" 49/1 1.07407 6.29778 1.11664 +/- 0.00615\n",
" 50/1 1.08040 6.29412 1.11574 +/- 0.00606\n",
" 51/1 1.19239 6.35017 1.11761 +/- 0.00620\n",
" 52/1 1.15682 6.28558 1.11854 +/- 0.00612\n",
" 53/1 1.20711 6.30846 1.12060 +/- 0.00632\n",
" 54/1 1.20705 6.29331 1.12256 +/- 0.00648\n",
" 55/1 1.12789 6.30289 1.12268 +/- 0.00634\n",
" 56/1 1.04906 6.31762 1.12108 +/- 0.00640\n",
" 57/1 1.08769 6.31970 1.12037 +/- 0.00630\n",
" 58/1 1.09744 6.28967 1.11989 +/- 0.00619\n",
" 59/1 1.12827 6.25912 1.12007 +/- 0.00606\n",
" 60/1 1.14679 6.33747 1.12060 +/- 0.00596\n",
" 61/1 1.07137 6.31680 1.11963 +/- 0.00593\n",
" 62/1 1.08775 6.31553 1.11902 +/- 0.00584\n",
" 63/1 1.08730 6.28327 1.11842 +/- 0.00576\n",
" 64/1 1.09925 6.29071 1.11807 +/- 0.00567\n",
" 65/1 1.13857 6.30750 1.11844 +/- 0.00557\n",
" 66/1 1.13142 6.32027 1.11867 +/- 0.00548\n",
" 67/1 1.19169 6.31633 1.11995 +/- 0.00553\n",
" 68/1 1.10446 6.29142 1.11969 +/- 0.00544\n",
" 69/1 1.12217 6.33088 1.11973 +/- 0.00535\n",
" 70/1 1.12190 6.31637 1.11976 +/- 0.00526\n",
" 71/1 1.07419 6.31151 1.11902 +/- 0.00523\n",
" 72/1 1.15328 6.29424 1.11957 +/- 0.00517\n",
" 73/1 1.10717 6.28237 1.11937 +/- 0.00509\n",
" 74/1 1.12341 6.28691 1.11944 +/- 0.00501\n",
" 75/1 1.09010 6.30830 1.11898 +/- 0.00496\n",
" 76/1 1.15934 6.28654 1.11960 +/- 0.00492\n",
" 77/1 1.14826 6.30996 1.12002 +/- 0.00486\n",
" 78/1 1.05648 6.29199 1.11909 +/- 0.00488\n",
" 79/1 1.16163 6.29889 1.11971 +/- 0.00485\n",
" 80/1 1.03429 6.33676 1.11849 +/- 0.00493\n",
" 81/1 1.09847 6.30386 1.11820 +/- 0.00487\n",
" 82/1 1.13013 6.31018 1.11837 +/- 0.00481\n",
" 83/1 1.12874 6.26761 1.11851 +/- 0.00474\n",
" 84/1 1.19748 6.30271 1.11958 +/- 0.00480\n",
" 85/1 1.10156 6.25979 1.11934 +/- 0.00474\n",
" 86/1 1.13734 6.29593 1.11958 +/- 0.00468\n",
" 87/1 1.06502 6.28702 1.11887 +/- 0.00468\n",
" 88/1 1.10497 6.31457 1.11869 +/- 0.00462\n",
" 89/1 1.10790 6.29572 1.11855 +/- 0.00456\n",
" 90/1 1.15089 6.28569 1.11896 +/- 0.00452\n",
" 91/1 1.11045 6.28323 1.11885 +/- 0.00447\n",
" 92/1 1.11278 6.29055 1.11878 +/- 0.00441\n",
" 93/1 1.04118 6.31384 1.11784 +/- 0.00446\n",
" 94/1 1.16581 6.31406 1.11841 +/- 0.00444\n",
" 95/1 1.08111 6.34289 1.11797 +/- 0.00441\n",
" 96/1 1.15478 6.30786 1.11840 +/- 0.00438\n",
" 97/1 1.09825 6.33143 1.11817 +/- 0.00434\n",
" 98/1 1.14136 6.30687 1.11843 +/- 0.00429\n",
" 99/1 1.12183 6.27010 1.11847 +/- 0.00425\n",
" 100/1 1.15657 6.31522 1.11890 +/- 0.00422\n",
" Creating state point statepoint.100.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 = 1.9520e+01 seconds\n",
" Time in transport only = 1.9506e+01 seconds\n",
" Time in inactive batches = 1.3732e+00 seconds\n",
" Time in active batches = 1.8147e+01 seconds\n",
" Time synchronizing fission bank = 1.6885e-03 seconds\n",
" Sampling source sites = 1.4447e-03 seconds\n",
" SEND/RECV source sites = 1.6767e-04 seconds\n",
" Time accumulating tallies = 5.7377e-03 seconds\n",
" Time writing statepoints = 2.1384e-03 seconds\n",
" Total time for finalization = 1.2658e-04 seconds\n",
" Total time elapsed = 1.9751e+01 seconds\n",
" Calculation Rate (inactive) = 7282.52 particles/second\n",
" Calculation Rate (active) = 4959.49 particles/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.12524 +/- 0.00363\n",
" k-effective (Track-length) = 1.11890 +/- 0.00422\n",
" k-effective (Absorption) = 1.12060 +/- 0.00351\n",
" Combined k-effective = 1.12210 +/- 0.00303\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n",
" Creating state point openmc_simulation_n1.h5...\n",
"[openmc.deplete] t=2160000.0 s, dt=2168640.0 s, source=174.0\n",
" Maximum neutron transport energy: 20000000 eV for O17\n",
" Initializing source particles...\n",
"\n",
" ====================> K EIGENVALUE SIMULATION <====================\n",
"\n",
" Bat./Gen. k Entropy Average k \n",
" ========= ======== ======== ====================\n",
" 1/1 1.12845 6.27596\n",
" 2/1 1.13900 6.28373\n",
" 3/1 1.20431 6.28207\n",
" 4/1 1.15496 6.33633\n",
" 5/1 1.11239 6.29062\n",
" 6/1 1.05243 6.29351\n",
" 7/1 1.06145 6.29588\n",
" 8/1 1.04968 6.30444\n",
" 9/1 1.12845 6.31550\n",
" 10/1 1.06837 6.31656\n",
" 11/1 1.11737 6.33225\n",
" 12/1 1.06896 6.30629 1.09316 +/- 0.02421\n",
" 13/1 1.05031 6.31259 1.07888 +/- 0.01998\n",
" 14/1 1.19799 6.30816 1.10866 +/- 0.03296\n",
" 15/1 1.11614 6.28461 1.11015 +/- 0.02557\n",
" 16/1 1.09314 6.27717 1.10732 +/- 0.02107\n",
" 17/1 1.11075 6.28821 1.10781 +/- 0.01782\n",
" 18/1 1.00896 6.31930 1.09545 +/- 0.01977\n",
" 19/1 1.17215 6.29835 1.10397 +/- 0.01940\n",
" 20/1 1.05388 6.30536 1.09896 +/- 0.01806\n",
" 21/1 1.10656 6.30293 1.09966 +/- 0.01635\n",
" 22/1 1.10363 6.32264 1.09999 +/- 0.01493\n",
" 23/1 1.07949 6.30716 1.09841 +/- 0.01383\n",
" 24/1 1.11004 6.27405 1.09924 +/- 0.01283\n",
" 25/1 1.11478 6.31939 1.10028 +/- 0.01199\n",
" 26/1 1.13011 6.31323 1.10214 +/- 0.01137\n",
" 27/1 1.06645 6.27511 1.10004 +/- 0.01088\n",
" 28/1 1.03214 6.26720 1.09627 +/- 0.01093\n",
" 29/1 1.16963 6.27974 1.10013 +/- 0.01104\n",
" 30/1 1.12738 6.30772 1.10149 +/- 0.01056\n",
" 31/1 1.10020 6.33863 1.10143 +/- 0.01004\n",
" 32/1 1.14373 6.31113 1.10335 +/- 0.00977\n",
" 33/1 1.08924 6.32446 1.10274 +/- 0.00935\n",
" 34/1 1.12176 6.30498 1.10353 +/- 0.00899\n",
" 35/1 1.12078 6.27414 1.10422 +/- 0.00865\n",
" 36/1 1.10406 6.31817 1.10422 +/- 0.00831\n",
" 37/1 1.20322 6.29862 1.10788 +/- 0.00880\n",
" 38/1 1.15612 6.32833 1.10961 +/- 0.00865\n",
" 39/1 1.13479 6.30525 1.11047 +/- 0.00839\n",
" 40/1 1.12160 6.28436 1.11085 +/- 0.00812\n",
" 41/1 1.09884 6.29781 1.11046 +/- 0.00786\n",
" 42/1 1.13132 6.29179 1.11111 +/- 0.00764\n",
" 43/1 1.05295 6.30498 1.10935 +/- 0.00761\n",
" 44/1 1.09329 6.31529 1.10888 +/- 0.00740\n",
" 45/1 1.13964 6.29129 1.10975 +/- 0.00724\n",
" 46/1 1.14508 6.24924 1.11074 +/- 0.00710\n",
" 47/1 1.08007 6.30395 1.10991 +/- 0.00696\n",
" 48/1 1.10345 6.30860 1.10974 +/- 0.00677\n",
" 49/1 1.06543 6.30764 1.10860 +/- 0.00669\n",
" 50/1 1.15283 6.30265 1.10971 +/- 0.00662\n",
" 51/1 1.12912 6.31967 1.11018 +/- 0.00647\n",
" 52/1 1.18989 6.30559 1.11208 +/- 0.00659\n",
" 53/1 1.13141 6.30158 1.11253 +/- 0.00645\n",
" 54/1 1.08104 6.26153 1.11181 +/- 0.00635\n",
" 55/1 1.15529 6.30483 1.11278 +/- 0.00628\n",
" 56/1 1.04901 6.32716 1.11139 +/- 0.00630\n",
" 57/1 1.11639 6.27550 1.11150 +/- 0.00616\n",
" 58/1 1.05002 6.30002 1.11022 +/- 0.00617\n",
" 59/1 1.18437 6.31644 1.11173 +/- 0.00623\n",
" 60/1 1.12838 6.28795 1.11206 +/- 0.00611\n",
" 61/1 1.11308 6.29217 1.11208 +/- 0.00599\n",
" 62/1 1.13441 6.31719 1.11251 +/- 0.00589\n",
" 63/1 1.13130 6.28057 1.11287 +/- 0.00579\n",
" 64/1 1.13172 6.28089 1.11322 +/- 0.00569\n",
" 65/1 1.13995 6.33942 1.11370 +/- 0.00561\n",
" 66/1 1.04077 6.30323 1.11240 +/- 0.00566\n",
" 67/1 1.15550 6.29985 1.11316 +/- 0.00561\n",
" 68/1 1.15900 6.24700 1.11395 +/- 0.00557\n",
" 69/1 1.16121 6.30480 1.11475 +/- 0.00553\n",
" 70/1 1.05775 6.32939 1.11380 +/- 0.00552\n",
" 71/1 1.25486 6.28724 1.11611 +/- 0.00590\n",
" 72/1 1.16258 6.29694 1.11686 +/- 0.00585\n",
" 73/1 1.03890 6.32218 1.11562 +/- 0.00589\n",
" 74/1 1.08603 6.27491 1.11516 +/- 0.00582\n",
" 75/1 1.12798 6.28528 1.11536 +/- 0.00573\n",
" 76/1 1.08881 6.31045 1.11496 +/- 0.00566\n",
" 77/1 1.06480 6.27791 1.11421 +/- 0.00562\n",
" 78/1 1.05927 6.27955 1.11340 +/- 0.00560\n",
" 79/1 1.18770 6.33638 1.11448 +/- 0.00562\n",
" 80/1 1.09655 6.31997 1.11422 +/- 0.00554\n",
" 81/1 1.14141 6.27796 1.11460 +/- 0.00548\n",
" 82/1 1.12740 6.29239 1.11478 +/- 0.00540\n",
" 83/1 1.08431 6.28158 1.11436 +/- 0.00535\n",
" 84/1 1.15089 6.32010 1.11486 +/- 0.00530\n",
" 85/1 1.20794 6.35885 1.11610 +/- 0.00537\n",
" 86/1 1.12375 6.29209 1.11620 +/- 0.00530\n",
" 87/1 1.06976 6.29139 1.11560 +/- 0.00527\n",
" 88/1 1.19094 6.28109 1.11656 +/- 0.00529\n",
" 89/1 1.16171 6.30244 1.11713 +/- 0.00525\n",
" 90/1 1.15540 6.28737 1.11761 +/- 0.00521\n",
" 91/1 1.08091 6.23012 1.11716 +/- 0.00516\n",
" 92/1 1.13609 6.31348 1.11739 +/- 0.00510\n",
" 93/1 1.10576 6.25653 1.11725 +/- 0.00504\n",
" 94/1 1.13767 6.31427 1.11749 +/- 0.00499\n",
" 95/1 1.08038 6.28840 1.11706 +/- 0.00495\n",
" 96/1 1.13827 6.28213 1.11730 +/- 0.00490\n",
" 97/1 1.12600 6.28887 1.11740 +/- 0.00484\n",
" 98/1 1.11309 6.30899 1.11735 +/- 0.00479\n",
" 99/1 1.12853 6.29928 1.11748 +/- 0.00474\n",
" 100/1 1.12854 6.31633 1.11760 +/- 0.00468\n",
" Creating state point statepoint.100.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 = 1.9467e+01 seconds\n",
" Time in transport only = 1.9452e+01 seconds\n",
" Time in inactive batches = 1.3137e+00 seconds\n",
" Time in active batches = 1.8153e+01 seconds\n",
" Time synchronizing fission bank = 1.7952e-03 seconds\n",
" Sampling source sites = 1.5509e-03 seconds\n",
" SEND/RECV source sites = 1.7138e-04 seconds\n",
" Time accumulating tallies = 5.7253e-03 seconds\n",
" Time writing statepoints = 2.4526e-03 seconds\n",
" Total time for finalization = 8.7500e-05 seconds\n",
" Total time elapsed = 1.9701e+01 seconds\n",
" Calculation Rate (inactive) = 7611.91 particles/second\n",
" Calculation Rate (active) = 4957.84 particles/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.11441 +/- 0.00407\n",
" k-effective (Track-length) = 1.11760 +/- 0.00468\n",
" k-effective (Absorption) = 1.10773 +/- 0.00319\n",
" Combined k-effective = 1.11060 +/- 0.00280\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n",
" Creating state point openmc_simulation_n2.h5...\n",
"[openmc.deplete] t=4328640.0 s, dt=2168640.0 s, source=174.0\n",
" Maximum neutron transport energy: 20000000 eV for O17\n",
" Initializing source particles...\n",
"\n",
" ====================> K EIGENVALUE SIMULATION <====================\n",
"\n",
" Bat./Gen. k Entropy Average k \n",
" ========= ======== ======== ====================\n",
" 1/1 1.13285 6.31080\n",
" 2/1 1.10552 6.30636\n",
" 3/1 1.08574 6.33484\n",
" 4/1 1.15516 6.26548\n",
" 5/1 1.11559 6.31331\n",
" 6/1 1.15097 6.29826\n",
" 7/1 1.06720 6.24007\n",
" 8/1 1.14035 6.30952\n",
" 9/1 1.13657 6.28351\n",
" 10/1 1.14929 6.31773\n",
" 11/1 1.10566 6.31332\n",
" 12/1 1.19467 6.29239 1.15017 +/- 0.04451\n",
" 13/1 1.14752 6.31642 1.14929 +/- 0.02571\n",
" 14/1 1.05756 6.28737 1.12635 +/- 0.02926\n",
" 15/1 1.09275 6.31871 1.11963 +/- 0.02364\n",
" 16/1 1.07747 6.27061 1.11261 +/- 0.02054\n",
" 17/1 1.11868 6.28145 1.11347 +/- 0.01738\n",
" 18/1 1.13439 6.30351 1.11609 +/- 0.01528\n",
" 19/1 1.17747 6.32348 1.12291 +/- 0.01510\n",
" 20/1 1.01074 6.27594 1.11169 +/- 0.01756\n",
" 21/1 1.14547 6.27382 1.11476 +/- 0.01618\n",
" 22/1 1.15391 6.27381 1.11802 +/- 0.01512\n",
" 23/1 1.18890 6.29333 1.12348 +/- 0.01494\n",
" 24/1 1.06922 6.31530 1.11960 +/- 0.01437\n",
" 25/1 1.05555 6.29344 1.11533 +/- 0.01404\n",
" 26/1 1.09559 6.32653 1.11410 +/- 0.01319\n",
" 27/1 1.10568 6.25585 1.11360 +/- 0.01240\n",
" 28/1 1.11205 6.32409 1.11352 +/- 0.01169\n",
" 29/1 1.06477 6.33278 1.11095 +/- 0.01135\n",
" 30/1 1.21745 6.29878 1.11627 +/- 0.01201\n",
" 31/1 1.09299 6.28899 1.11517 +/- 0.01148\n",
" 32/1 1.07749 6.29890 1.11345 +/- 0.01108\n",
" 33/1 1.08443 6.32299 1.11219 +/- 0.01066\n",
" 34/1 1.07304 6.30690 1.11056 +/- 0.01034\n",
" 35/1 1.13298 6.31149 1.11146 +/- 0.00996\n",
" 36/1 1.13632 6.33117 1.11241 +/- 0.00961\n",
" 37/1 1.10000 6.23781 1.11195 +/- 0.00926\n",
" 38/1 1.06647 6.26534 1.11033 +/- 0.00907\n",
" 39/1 1.07174 6.30076 1.10900 +/- 0.00885\n",
" 40/1 1.01695 6.28783 1.10593 +/- 0.00909\n",
" 41/1 1.08398 6.29140 1.10522 +/- 0.00882\n",
" 42/1 1.05541 6.26909 1.10367 +/- 0.00868\n",
" 43/1 1.04598 6.29747 1.10192 +/- 0.00859\n",
" 44/1 1.10673 6.29832 1.10206 +/- 0.00834\n",
" 45/1 1.12219 6.30160 1.10263 +/- 0.00811\n",
" 46/1 1.12513 6.26543 1.10326 +/- 0.00791\n",
" 47/1 1.11804 6.28044 1.10366 +/- 0.00770\n",
" 48/1 1.12656 6.31176 1.10426 +/- 0.00752\n",
" 49/1 1.10706 6.32059 1.10433 +/- 0.00733\n",
" 50/1 1.11570 6.29753 1.10462 +/- 0.00715\n",
" 51/1 1.05827 6.29614 1.10349 +/- 0.00706\n",
" 52/1 1.14250 6.31912 1.10442 +/- 0.00695\n",
" 53/1 1.12678 6.29435 1.10494 +/- 0.00681\n",
" 54/1 1.12593 6.29570 1.10541 +/- 0.00667\n",
" 55/1 1.01983 6.31802 1.10351 +/- 0.00679\n",
" 56/1 1.16023 6.25535 1.10474 +/- 0.00676\n",
" 57/1 1.13294 6.32297 1.10534 +/- 0.00664\n",
" 58/1 1.15078 6.31390 1.10629 +/- 0.00657\n",
" 59/1 1.08886 6.33159 1.10593 +/- 0.00644\n",
" 60/1 1.10549 6.30424 1.10593 +/- 0.00631\n",
" 61/1 1.12098 6.28489 1.10622 +/- 0.00619\n",
" 62/1 1.14137 6.33513 1.10690 +/- 0.00611\n",
" 63/1 1.08653 6.31019 1.10651 +/- 0.00601\n",
" 64/1 1.11981 6.29997 1.10676 +/- 0.00590\n",
" 65/1 1.12847 6.27479 1.10715 +/- 0.00581\n",
" 66/1 1.11183 6.30330 1.10724 +/- 0.00570\n",
" 67/1 1.16858 6.31313 1.10831 +/- 0.00570\n",
" 68/1 1.10715 6.30826 1.10829 +/- 0.00560\n",
" 69/1 1.12031 6.30143 1.10850 +/- 0.00551\n",
" 70/1 1.18768 6.30786 1.10982 +/- 0.00558\n",
" 71/1 1.19824 6.30158 1.11127 +/- 0.00567\n",
" 72/1 1.06861 6.32451 1.11058 +/- 0.00562\n",
" 73/1 1.08383 6.32445 1.11015 +/- 0.00555\n",
" 74/1 1.10815 6.28951 1.11012 +/- 0.00546\n",
" 75/1 1.09637 6.31541 1.10991 +/- 0.00538\n",
" 76/1 1.11185 6.27594 1.10994 +/- 0.00530\n",
" 77/1 1.07071 6.30012 1.10935 +/- 0.00525\n",
" 78/1 1.09980 6.26082 1.10921 +/- 0.00518\n",
" 79/1 1.08843 6.29983 1.10891 +/- 0.00511\n",
" 80/1 1.04869 6.30655 1.10805 +/- 0.00511\n",
" 81/1 1.15056 6.29597 1.10865 +/- 0.00507\n",
" 82/1 1.13123 6.35333 1.10896 +/- 0.00501\n",
" 83/1 1.06594 6.30523 1.10838 +/- 0.00498\n",
" 84/1 1.07440 6.28528 1.10792 +/- 0.00493\n",
" 85/1 1.09834 6.30495 1.10779 +/- 0.00487\n",
" 86/1 1.08958 6.30761 1.10755 +/- 0.00481\n",
" 87/1 1.11715 6.24654 1.10767 +/- 0.00475\n",
" 88/1 1.17640 6.30907 1.10855 +/- 0.00477\n",
" 89/1 1.07181 6.26532 1.10809 +/- 0.00473\n",
" 90/1 1.06285 6.29943 1.10752 +/- 0.00470\n",
" 91/1 1.16446 6.29053 1.10823 +/- 0.00470\n",
" 92/1 1.02306 6.29530 1.10719 +/- 0.00476\n",
" 93/1 1.09838 6.28983 1.10708 +/- 0.00470\n",
" 94/1 1.03198 6.34684 1.10619 +/- 0.00473\n",
" 95/1 1.11466 6.32191 1.10629 +/- 0.00467\n",
" 96/1 1.11536 6.27898 1.10639 +/- 0.00462\n",
" 97/1 1.10048 6.28191 1.10633 +/- 0.00457\n",
" 98/1 1.14554 6.30311 1.10677 +/- 0.00454\n",
" 99/1 1.05999 6.29439 1.10625 +/- 0.00452\n",
" 100/1 1.06479 6.29052 1.10579 +/- 0.00449\n",
" Creating state point statepoint.100.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 = 1.9359e+01 seconds\n",
" Time in transport only = 1.9345e+01 seconds\n",
" Time in inactive batches = 1.3741e+00 seconds\n",
" Time in active batches = 1.7985e+01 seconds\n",
" Time synchronizing fission bank = 1.7691e-03 seconds\n",
" Sampling source sites = 1.5378e-03 seconds\n",
" SEND/RECV source sites = 1.8229e-04 seconds\n",
" Time accumulating tallies = 5.6940e-03 seconds\n",
" Time writing statepoints = 2.2907e-03 seconds\n",
" Total time for finalization = 9.6417e-05 seconds\n",
" Total time elapsed = 1.9588e+01 seconds\n",
" Calculation Rate (inactive) = 7277.65 particles/second\n",
" Calculation Rate (active) = 5004.19 particles/second\n",
"\n",
" ============================> RESULTS <============================\n",
"\n",
" k-effective (Collision) = 1.10608 +/- 0.00362\n",
" k-effective (Track-length) = 1.10579 +/- 0.00449\n",
" k-effective (Absorption) = 1.09831 +/- 0.00359\n",
" Combined k-effective = 1.10197 +/- 0.00303\n",
" Leakage Fraction = 0.00000 +/- 0.00000\n",
"\n",
" Creating state point openmc_simulation_n3.h5...\n",
"[openmc.deplete] t=6497280.0 s, dt=2592000.0 s, source=0.0\n",
" Creating state point openmc_simulation_n4.h5...\n",
"[openmc.deplete] t=9089280.0 (final operator evaluation)\n",
" Creating state point openmc_simulation_n5.h5...\n"
]
}
],
"source": [
"###############################################################################\n",
"# Define materials\n",
"###############################################################################\n",
"\n",
"# Instantiate some Materials and register the appropriate Nuclides\n",
"uo2 = openmc.Material(name='UO2 fuel at 2.4% wt enrichment')\n",
"uo2.set_density('g/cm3', 10.29769)\n",
"uo2.add_element('U', 1., enrichment=2.4)\n",
"uo2.add_element('O', 2.)\n",
"\n",
"helium = openmc.Material(name='Helium for gap')\n",
"helium.set_density('g/cm3', 0.001598)\n",
"helium.add_element('He', 2.4044e-4)\n",
"\n",
"zircaloy = openmc.Material(name='Zircaloy 4')\n",
"zircaloy.set_density('g/cm3', 6.55)\n",
"zircaloy.add_element('Sn', 0.014, 'wo')\n",
"zircaloy.add_element('Fe', 0.00165, 'wo')\n",
"zircaloy.add_element('Cr', 0.001, 'wo')\n",
"zircaloy.add_element('Zr', 0.98335, 'wo')\n",
"\n",
"borated_water = openmc.Material(name='Borated water')\n",
"borated_water.set_density('g/cm3', 0.740582)\n",
"borated_water.add_element('B', 4.0e-5)\n",
"borated_water.add_element('H', 5.0e-2)\n",
"borated_water.add_element('O', 2.4e-2)\n",
"borated_water.add_s_alpha_beta('c_H_in_H2O')\n",
"\n",
"###############################################################################\n",
"# Create geometry\n",
"###############################################################################\n",
"\n",
"# Define surfaces\n",
"pitch = 1.25984\n",
"fuel_or = openmc.ZCylinder(r=0.39218, name='Fuel OR')\n",
"clad_ir = openmc.ZCylinder(r=0.40005, name='Clad IR')\n",
"clad_or = openmc.ZCylinder(r=0.45720, name='Clad OR')\n",
"box = openmc.model.RectangularPrism(pitch, pitch, boundary_type='reflective')\n",
"\n",
"# Define cells\n",
"fuel = openmc.Cell(fill=uo2, region=-fuel_or)\n",
"gap = openmc.Cell(fill=helium, region=+fuel_or & -clad_ir)\n",
"clad = openmc.Cell(fill=zircaloy, region=+clad_ir & -clad_or)\n",
"water = openmc.Cell(fill=borated_water, region=+clad_or & -box)\n",
"\n",
"# Define overall geometry\n",
"geometry = openmc.Geometry([fuel, gap, clad, water])\n",
"\n",
"###############################################################################\n",
"# Set volumes of depletable materials\n",
"###############################################################################\n",
"\n",
"# Set material volume for depletion. For 2D simulations, this should be an area.\n",
"uo2.volume = pi * fuel_or.r**2\n",
"\n",
"###############################################################################\n",
"# Transport calculation settings\n",
"###############################################################################\n",
"\n",
"# Instantiate a Settings object, set all runtime parameters, and export to XML\n",
"settings = openmc.Settings()\n",
"settings.batches = 100\n",
"settings.inactive = 10\n",
"settings.particles = 1000\n",
"\n",
"# Create an initial uniform spatial source distribution over fissionable zones\n",
"bounds = [-0.62992, -0.62992, -1, 0.62992, 0.62992, 1]\n",
"uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:])\n",
"settings.source = openmc.IndependentSource(\n",
" space=uniform_dist, constraints={'fissionable': True})\n",
"\n",
"entropy_mesh = openmc.RegularMesh()\n",
"entropy_mesh.lower_left = [-0.39218, -0.39218, -1.e50]\n",
"entropy_mesh.upper_right = [0.39218, 0.39218, 1.e50]\n",
"entropy_mesh.dimension = [10, 10, 1]\n",
"settings.entropy_mesh = entropy_mesh\n",
"\n",
"###############################################################################\n",
"# Initialize and run depletion calculation\n",
"###############################################################################\n",
"\n",
"model = openmc.Model(geometry=geometry, settings=settings)\n",
"\n",
"# Create depletion \"operator\"\n",
"chain_file = '/Users/gavin/Code/chain_endfb80_pwr.xml'\n",
"op = openmc.deplete.CoupledOperator(model, chain_file)\n",
"\n",
"\n",
"\n",
"# Perform simulation using the predictor algorithm.\n",
"# How many days are required to hit 3 MWd/kgU? The below is correct.\n",
"time_steps = [2.5, 22.5, 25.1, 25.1, 30.0] # days\n",
"power = [174.0, 174.0, 174.0, 174.0, 0.0] # W/cm\n",
"integrator = openmc.deplete.PredictorIntegrator(op, time_steps, power, timestep_units='d') \n",
"integrator.integrate()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "9302e1d7-76dc-4aa9-9073-c7ab99fe42f4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"grams U / cm\n",
"4.378680357527571\n"
]
}
],
"source": [
"print('grams U / cm')\n",
"u_linear_density = uo2.volume * uo2.density * .88\n",
"print(u_linear_density)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c3349532-ebdd-4ca1-81ff-64cc8865a8c7",
"metadata": {},
"outputs": [],
"source": [
"# BU = (P/1e6) * t / (m/1000)\n",
"# 0.1 MWd/kgU \n",
"# so t = 0.1 * 1e3 / 174 * 4.37 = 2.5 days"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "b3724963-9ff9-4634-99fd-6865b4bfe168",
"metadata": {},
"outputs": [],
"source": [
"###############################################################################\n",
"# Read depletion calculation results\n",
"###############################################################################\n",
"\n",
"# Open results file\n",
"results = openmc.deplete.Results(\"depletion_results.h5\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "a2a8ad1b-160e-4a1b-8d5b-4a35bc59c1d0",
"metadata": {},
"outputs": [],
"source": [
"# Now we give the composition one month of decay time.\n",
"# The volume to get 1 kgU is used.\n",
"u_rho = uo2.density * 0.88 # g/cm^3\n",
"v_one_kg = 1000.0 / u_rho"
]
},
{
"cell_type": "markdown",
"id": "2bc24026-f741-4eb8-ad42-634ddb3b3e68",
"metadata": {},
"source": [
"# Let's compare the activities reported"
]
},
{
"attachments": {
"6347e50a-a3d8-4ded-a65b-090512bb66cb.png": {
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"
}
},
"cell_type": "markdown",
"id": "482649b5-4c4f-4f68-964c-4c2dc6525c8b",
"metadata": {},
"source": [
"![image.png](attachment:6347e50a-a3d8-4ded-a65b-090512bb66cb.png)"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "fd43eaa1-df4a-4ad3-9a48-ccb8032878c3",
"metadata": {},
"outputs": [],
"source": [
"times, activities = results.get_activity(uo2, units='Bq', by_nuclide=True, volume=v_one_kg)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "97c74faf-5fbe-4784-8711-a09ccb635fd6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Cs137 3.7e+11\n",
"Ba140 1.5e+13\n",
"Ru106 1.2e+12\n",
"Zr95 3.2e+13\n",
"Ce144 1.1e+13\n",
"Sr90 3.4e+11\n",
"Y90 3.4e+11\n"
]
}
],
"source": [
"nuclides = ['Cs137', 'Ba140', 'Ru106', 'Zr95', 'Ce144', 'Sr90', 'Y90']\n",
"for nuclide in nuclides:\n",
" print(nuclide, '%.1e'% activities[-1][nuclide])"
]
},
{
"attachments": {
"161867ef-4ea8-4b1d-9a97-2ae11904ee48.png": {
"image/png": 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"
}
},
"cell_type": "markdown",
"id": "f8a05491-325b-4cea-ac72-5c7b617d513e",
"metadata": {},
"source": [
"I then asked ChatGPT to parse out values from the image and plot against the values I obtained here in log scale. Overall, the agreement is solid on the key fission products. The disagreement on Ba140 is alarming, but shouldn't throw off the key conclusions here.\n",
"\n",
"![image.png](attachment:161867ef-4ea8-4b1d-9a97-2ae11904ee48.png)"
]
},
{
"cell_type": "markdown",
"id": "45d77c87-7697-489c-bbf4-0fcdc6fd51a9",
"metadata": {},
"source": [
"# Calculating the dose rate\n",
"\n",
"Here, I extract the source term from the depleted material and calculate to find the dose rate\n",
"at 1 cm."
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "c459cc59-e484-4cb0-9d73-dab89f0bf8df",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/gavin/Code/gavin-env/lib/python3.12/site-packages/openmc/mixin.py:70: IDWarning: Another Material instance already exists with id=5.\n",
" warn(msg, IDWarning)\n",
"/Users/gavin/Code/gavin-env/lib/python3.12/site-packages/openmc/mixin.py:70: IDWarning: Another Material instance already exists with id=6.\n",
" warn(msg, IDWarning)\n",
"/Users/gavin/Code/gavin-env/lib/python3.12/site-packages/openmc/mixin.py:70: IDWarning: Another Material instance already exists with id=7.\n",
" warn(msg, IDWarning)\n",
"/Users/gavin/Code/gavin-env/lib/python3.12/site-packages/openmc/mixin.py:70: IDWarning: Another Material instance already exists with id=8.\n",
" warn(msg, IDWarning)\n"
]
}
],
"source": [
"depleted_fuel = results.export_to_materials(-1)[0]"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "90aaebc6-e995-4d58-9c0e-17901ff39e9d",
"metadata": {},
"outputs": [],
"source": [
"depleted_fuel.volume = v_one_kg"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "aa81ab08-909b-4c70-b7cf-a9d07847a606",
"metadata": {},
"outputs": [],
"source": [
"openmc.config['chain_file'] = chain_file"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "b6215aed-834c-4e9b-a44e-66b0edef994d",
"metadata": {},
"outputs": [],
"source": [
"source_energy_spectrum = depleted_fuel.get_decay_photon_energy(volume=v_one_kg)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "38831c0b-c467-4ab3-bf11-15182aae60bf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total photon source rate (Bq/kgU): 1.65e+14\n"
]
}
],
"source": [
"print('Total photon source rate (Bq/kgU): %.2e'%source_energy_spectrum.integral())"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "4f19de3c-438d-4caa-8798-efbe81de7532",
"metadata": {},
"outputs": [],
"source": [
"# ANSI/ANS-6.1.1-1977 photon flux-to-dose conversion factors.\n",
"# This converts the flux in 1/cm^2/s to rem/hr assuming average biological tissue.\n",
"# NOTE ENERGY IS IN MEV SO I CONVERT!!\n",
"flux2dose = np.array([[0.01 , 3.96e-6],\n",
" [0.03 , 5.82e-7],\n",
" [0.05 , 2.9e-7 ],\n",
" [0.07 , 2.58e-7],\n",
" [0.1 , 2.83e-7 ],\n",
" [0.15 , 3.79e-7],\n",
" [0.2 , 5.01e-7 ],\n",
" [0.25 , 6.31e-7],\n",
" [0.3 , 7.59e-7 ],\n",
" [0.35 , 8.78e-7],\n",
" [0.4 , 9.85e-7 ],\n",
" [0.45 , 1.08e-6],\n",
" [0.5 , 1.17e-6 ],\n",
" [0.55 , 1.27e-6],\n",
" [0.6 , 1.36e-6 ],\n",
" [0.65 , 1.44e-6],\n",
" [0.7 , 1.52e-6 ],\n",
" [0.8 , 1.68e-6 ],\n",
" [1.0 , 1.98e-6 ],\n",
" [1.4 , 2.51e-6 ],\n",
" [1.8 , 2.99e-6 ],\n",
" [2.2 , 3.42e-6 ],\n",
" [2.6 , 3.82e-6 ],\n",
" [2.8 , 4.01e-6 ],\n",
" [3.25 , 4.41e-6],\n",
" [3.75 , 4.83e-6],\n",
" [4.25 , 5.23e-6],\n",
" [4.75 , 5.6e-6 ],\n",
" [5.0 , 5.8e-6 ],\n",
" [5.25 , 6.01e-6],\n",
" [5.75 , 6.37e-6],\n",
" [6.25 , 6.74e-6],\n",
" [6.75 , 7.11e-6],\n",
" [7.5 , 7.66e-6 ],\n",
" [9.0 , 8.77e-6 ],\n",
" [11.0 , 1.03e-5],\n",
" [13.0 , 1.18e-5],\n",
" [15.0 , 1.33e-5]])\n",
"flux2dose[:, 0] *= 1e6"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "aa4f9aaf-4988-454b-bdbc-b2cc118249b2",
"metadata": {},
"outputs": [],
"source": [
"total_dose_rate = 0.0\n",
"distance = 1.0\n",
"for photon_energy, intensity in zip(source_energy_spectrum.x, source_energy_spectrum.p):\n",
" # Calculate the flux at 1 cm from this kilogram. Assume radiation emanates from a point source.\n",
" flux = intensity/(4.0 * np.pi * distance**2) # photon / cm^2 / s\n",
" total_dose_rate += flux * np.interp(photon_energy, flux2dose[:, 0], flux2dose[:, 1])"
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "a3aa4c98-69c5-403e-9466-c2b1e82f1955",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The dose rate (rem/hr) at 1 cm, with a 1 kgU at 3 MWd/kgU after 30 cooling days point source is:\n"
]
},
{
"data": {
"text/plain": [
"18868374.34044833"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# The dose rate at 1 cm is:\n",
"print('The dose rate (rem/hr) at 1 cm, with a 1 kgU at 3 MWd/kgU after 30 cooling days point source is:')\n",
"total_dose_rate"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "1bc4be9f-f86c-4d03-b4c7-b678aa575d3e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The time it would take to receive an LD50 of radiation (450 rem) is:\n"
]
},
{
"data": {
"text/plain": [
"2.3849431428511055e-05"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"print('The time (hours) it would take to receive an LD50 of radiation (450 rem) is:')\n",
"450.0 / total_dose_rate"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "ea12d03d-eeb3-4480-b172-0b4adecd8696",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.0858579531426398"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Time in seconds:\n",
"2.3849431428511055e-05 * 3600.0"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3dde7767-64c0-41f2-b172-518542800b33",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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