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Merge pull request #1514 from dryuri92/patch-1
Fix the bug on MGXS mode with Interpolation method
This commit is contained in:
Paul Romano
GitHub
commit
2160e6b156
6 changed files with 484 additions and 12 deletions
24
src/mgxs.cpp
24
src/mgxs.cpp
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@ -82,13 +82,14 @@ Mgxs::metadata_from_hdf5(hid_t xs_id, const std::vector<double>& temperature,
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// Determine the available temperatures
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hid_t kT_group = open_group(xs_id, "kTs");
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int num_temps = get_num_datasets(kT_group);
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size_t num_temps = get_num_datasets(kT_group);
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char** dset_names = new char*[num_temps];
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for (int i = 0; i < num_temps; i++) {
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dset_names[i] = new char[151];
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}
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get_datasets(kT_group, dset_names);
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xt::xarray<double> available_temps(num_temps);
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std::vector<size_t> shape = {num_temps};
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xt::xarray<double> available_temps(shape);
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for (int i = 0; i < num_temps; i++) {
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read_double(kT_group, dset_names[i], &available_temps[i], true);
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@ -131,7 +132,12 @@ Mgxs::metadata_from_hdf5(hid_t xs_id, const std::vector<double>& temperature,
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case TemperatureMethod::INTERPOLATION:
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for (int i = 0; i < temperature.size(); i++) {
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for (int j = 0; j < num_temps - 1; j++) {
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for (int j = 0; j < num_temps; j++) {
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if (j == (num_temps - 1)) {
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fatal_error("MGXS Library does not contain cross sections for " +
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in_name + " at temperatures that bound " +
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std::to_string(std::round(temperature[i])));
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}
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if ((available_temps[j] <= temperature[i]) &&
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(temperature[i] < available_temps[j + 1])) {
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if (std::find(temps_to_read.begin(),
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@ -144,13 +150,10 @@ Mgxs::metadata_from_hdf5(hid_t xs_id, const std::vector<double>& temperature,
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std::round(available_temps[j + 1])) == temps_to_read.end()) {
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temps_to_read.push_back(std::round((int) available_temps[j + 1]));
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}
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continue;
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break;
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}
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}
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fatal_error("MGXS Library does not contain cross sections for " +
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in_name + " at temperatures that bound " +
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std::to_string(std::round(temperature[i])));
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}
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}
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std::sort(temps_to_read.begin(), temps_to_read.end());
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@ -381,15 +384,16 @@ Mgxs::Mgxs(const std::string& in_name, const std::vector<double>& mat_kTs,
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// to do the 2nd temperature
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int num_interp_points = 2;
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if (settings::temperature_method == TemperatureMethod::NEAREST) num_interp_points = 1;
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std::vector<double> interp(micros.size());
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std::vector<int> temp_indices(micros.size());
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for (int interp_point = 0; interp_point < num_interp_points; interp_point++) {
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std::vector<double> interp(micros.size());
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std::vector<double> temp_indices(micros.size());
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for (int m = 0; m < micros.size(); m++) {
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interp[m] = (1. - micro_t_interp[m]) * atom_densities[m];
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temp_indices[m] = micro_t[m] + interp_point;
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micro_t_interp[m] = 1. - micro_t_interp[m];
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}
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combine(micros, interp, micro_t, t);
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combine(micros, interp, temp_indices, t);
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} // end loop to sum all micros across the temperatures
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} // end temperature (t) loop
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}
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@ -65,7 +65,10 @@ ScattData::base_combine(size_t max_order,
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xt::xtensor<double, 3> this_matrix({groups, groups, max_order}, 0.);
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xt::xtensor<double, 2> mult_numer({groups, groups}, 0.);
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xt::xtensor<double, 2> mult_denom({groups, groups}, 0.);
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// TODO: Need to review this:
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if (this->scattxs.size() > 0) {
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this_matrix = this->get_matrix(max_order);
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}
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// Build the dense scattering and multiplicity matrices
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// Get the multiplicity_matrix
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// To combine from nuclidic data we need to use the final relationship
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@ -110,7 +113,18 @@ ScattData::base_combine(size_t max_order,
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// Combine mult_numer and mult_denom into the combined multiplicity matrix
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xt::xtensor<double, 2> this_mult({groups, groups}, 1.);
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this_mult = xt::nan_to_num(mult_numer / mult_denom);
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// TODO: Need to check this too
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for (int gin = 0; gin < groups; gin++) {
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for (int gout = 0; gout < groups; gout++) {
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if (std::abs(mult_denom(gin, gout)) > 0.0) {
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this_mult(gin, gout) = mult_numer(gin, gout) / mult_denom(gin, gout);
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} else {
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if (mult_numer(gin, gout) == 0.0) {
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this_mult(gin, gout) = 1.0;
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}
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}
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}
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}
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// We have the data, now we need to convert to a jagged array and then use
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// the initialize function to store it on the object.
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1
tests/regression_tests/mg_temperature/__init__.py
Normal file
1
tests/regression_tests/mg_temperature/__init__.py
Normal file
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@ -0,0 +1 @@
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297
tests/regression_tests/mg_temperature/build_2g.py
Normal file
297
tests/regression_tests/mg_temperature/build_2g.py
Normal file
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@ -0,0 +1,297 @@
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import openmc
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import numpy as np
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names = ['H', 'O', 'Zr', 'U235', 'U238']
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def build_openmc_xs_lib(name, groups, temperatures, xsdict, micro=True):
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"""Build an Openm XSdata based on dictionary values"""
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xsdata = openmc.XSdata(name, groups, temperatures=temperatures)
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xsdata.order = 0
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for tt in temperatures:
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xsdata.set_absorption(xsdict[tt]['absorption'][name], temperature=tt)
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xsdata.set_scatter_matrix(xsdict[tt]['scatter'][name], temperature=tt)
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xsdata.set_total(xsdict[tt]['total'][name], temperature=tt)
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if (name in xsdict[tt]['nu-fission'].keys()):
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xsdata.set_nu_fission(xsdict[tt]['nu-fission'][name],
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temperature=tt)
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xsdata.set_chi(np.array([1., 0.]), temperature=tt)
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return xsdata
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def create_micro_xs_dict():
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"""Returns micro xs library"""
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xs_micro = {}
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reactions = ['absorption', 'total', 'scatter', 'nu-fission']
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# chi is unnecessary when energy bound is in thermal region
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# Temperature 300K
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# absorption
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xs_micro[300] = {r: {} for r in reactions}
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xs_micro[300]['absorption']['H'] = np.array([1.0285E-4, 0.0057])
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xs_micro[300]['absorption']['O'] = np.array([7.1654E-5, 3.0283E-6])
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xs_micro[300]['absorption']['Zr'] = np.array([4.5918E-5, 3.6303E-5])
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xs_micro[300]['absorption']['U235'] = np.array([0.0035, 0.1040])
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xs_micro[300]['absorption']['U238'] = np.array([0.0056, 0.0094])
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# nu-scatter matrix
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xs_micro[300]['scatter']['H'] = np.array([[[0.0910, 0.01469],
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[0.0, 0.3316]]])
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xs_micro[300]['scatter']['O'] = np.array([[[0.0814, 3.3235E-4],
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[0.0, 0.0960]]])
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xs_micro[300]['scatter']['Zr'] = np.array([[[0.0311, 2.6373E-5],
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[0.0, 0.0315]]])
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xs_micro[300]['scatter']['U235'] = np.array([[[0.0311, 2.6373E-5],
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[0.0, 0.0315]]])
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xs_micro[300]['scatter']['U238'] = np.array([[[0.0551, 2.2341E-5],
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[0.0, 0.0526]]])
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# nu-fission
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xs_micro[300]['nu-fission']['U235'] = np.array([0.0059, 0.2160])
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xs_micro[300]['nu-fission']['U238'] = np.array([0.0019, 1.4627E-7])
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# total
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xs_micro[300]['total']['H'] = xs_micro[300]['absorption']['H'] + \
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np.sum(xs_micro[300]['scatter']['H'][0], 1)
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xs_micro[300]['total']['O'] = xs_micro[300]['absorption']['O'] + \
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np.sum(xs_micro[300]['scatter']['O'][0], 1)
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xs_micro[300]['total']['Zr'] = xs_micro[300]['absorption']['Zr'] + \
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np.sum(xs_micro[300]['scatter']['Zr'][0], 1)
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xs_micro[300]['total']['U235'] = xs_micro[300]['absorption']['U235'] + \
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np.sum(xs_micro[300]['scatter']['U235'][0], 1)
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xs_micro[300]['total']['U238'] = xs_micro[300]['absorption']['U238'] + \
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np.sum(xs_micro[300]['scatter']['U238'][0], 1)
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# Temperature 600K
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xs_micro[600] = {r: {} for r in reactions}
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# absorption
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xs_micro[600]['absorption']['H'] = np.array([1.0356E-4, 0.0046])
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xs_micro[600]['absorption']['O'] = np.array([7.2678E-5, 2.4963E-6])
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xs_micro[600]['absorption']['Zr'] = np.array([4.7256E-5, 2.9757E-5])
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xs_micro[600]['absorption']['U235'] = np.array([0.0035, 0.0853])
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xs_micro[600]['absorption']['U238'] = np.array([0.0058, 0.0079])
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# nu-scatter matrix
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xs_micro[600]['scatter']['H'] = np.array([[[0.0910, 0.0138],
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[0.0, 0.3316]]])
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xs_micro[600]['scatter']['O'] = np.array([[[0.0814, 3.5367E-4],
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[0.0, 0.0959]]])
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xs_micro[600]['scatter']['Zr'] = np.array([[[0.0311, 3.2293E-5],
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[0.0, 0.0314]]])
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xs_micro[600]['scatter']['U235'] = np.array([[[0.0022, 1.9763E-6],
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[9.1634E-8, 0.0039]]])
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xs_micro[600]['scatter']['U238'] = np.array([[[0.0556, 2.8803E-5],
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[0.0, 0.0536]]])
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# nu-fission
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xs_micro[600]['nu-fission']['U235'] = np.array([0.0059, 0.1767])
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xs_micro[600]['nu-fission']['U238'] = np.array([0.0019, 1.2405E-7])
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# total
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xs_micro[600]['total']['H'] = xs_micro[600]['absorption']['H'] + \
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np.sum(xs_micro[600]['scatter']['H'][0], 1)
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xs_micro[600]['total']['O'] = xs_micro[600]['absorption']['O'] + \
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np.sum(xs_micro[600]['scatter']['O'][0], 1)
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xs_micro[600]['total']['Zr'] = xs_micro[600]['absorption']['Zr'] + \
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np.sum(xs_micro[600]['scatter']['Zr'][0], 1)
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xs_micro[600]['total']['U235'] = xs_micro[600]['absorption']['U235'] + \
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np.sum(xs_micro[600]['scatter']['U235'][0], 1)
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xs_micro[600]['total']['U238'] = xs_micro[600]['absorption']['U238'] + \
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np.sum(xs_micro[600]['scatter']['U238'][0], 1)
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# Temperature 900K
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xs_micro[900] = {r: {} for r in reactions}
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# absorption
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xs_micro[900]['absorption']['H'] = np.array([1.0529E-4, 0.0040])
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xs_micro[900]['absorption']['O'] = np.array([7.3055E-5, 2.1850E-6])
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xs_micro[900]['absorption']['Zr'] = np.array([4.7141E-5, 2.5941E-5])
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xs_micro[900]['absorption']['U235'] = np.array([0.0035, 0.0749])
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xs_micro[900]['absorption']['U238'] = np.array([0.0060, 0.0071])
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# total
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xs_micro[900]['total']['H'] = np.array([0.2982, 0.7332])
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xs_micro[900]['total']['O'] = np.array([0.0885, 0.1004])
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xs_micro[900]['total']['Zr'] = np.array([0.0370, 0.0317])
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xs_micro[900]['total']['U235'] = np.array([0.0061, 0.0789])
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xs_micro[900]['total']['U238'] = np.array([0.0707, 0.0613])
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# nu-scatter matrix
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xs_micro[900]['scatter']['H'] = np.array([[[0.0913, 0.0147],
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[0.0, 0.4020]]])
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xs_micro[900]['scatter']['O'] = np.array([[[0.0812, 4.0413E-4],
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[0.0, 0.0965]]])
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xs_micro[900]['scatter']['Zr'] = np.array([[[0.0311, 3.6735E-5],
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[0.0, 0.0314]]])
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xs_micro[900]['scatter']['U235'] = np.array([[[0.0022, 2.9034E-6],
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[1.3117E-8, 0.0039]]])
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xs_micro[900]['scatter']['U238'] = np.array([[[0.0560, 3.7619E-5],
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[0.0, 0.0538]]])
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# nu-fission
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xs_micro[900]['nu-fission']['U235'] = np.array([0.0059, 0.1545])
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xs_micro[900]['nu-fission']['U238'] = np.array([0.0019, 1.1017E-7])
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# total
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xs_micro[900]['total']['H'] = xs_micro[900]['absorption']['H'] + \
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np.sum(xs_micro[900]['scatter']['H'][0], 1)
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xs_micro[900]['total']['O'] = xs_micro[900]['absorption']['O'] + \
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np.sum(xs_micro[900]['scatter']['O'][0], 1)
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xs_micro[900]['total']['Zr'] = xs_micro[900]['absorption']['Zr'] + \
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np.sum(xs_micro[900]['scatter']['Zr'][0], 1)
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xs_micro[900]['total']['U235'] = xs_micro[900]['absorption']['U235'] + \
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np.sum(xs_micro[900]['scatter']['U235'][0], 1)
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xs_micro[900]['total']['U238'] = xs_micro[900]['absorption']['U238'] + \
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np.sum(xs_micro[900]['scatter']['U238'][0], 1)
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# roll axis for scatter matrix
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for t in xs_micro:
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for n in xs_micro[t]['scatter']:
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xs_micro[t]['scatter'][n] = np.rollaxis(xs_micro[t]['scatter'][n],
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0, 3)
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return xs_micro
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def create_macro_dict(xs_micro):
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"""Create a dictionary with two group cross-section"""
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xs_macro = {}
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for t, d1 in xs_micro.items():
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xs_macro[t] = {}
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for r, d2 in d1.items():
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temp = []
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xs_macro[t][r] = {}
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for n, v in d2.items():
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temp.append(d2[n])
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# The name 'macro' is needed to store data at the same level
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# of a xs_macro dictionary as for xs_micro and use it in
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# function build_openmc_xs_lib
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xs_macro[t][r]['macro'] = sum(temp)
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return xs_macro
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def create_openmc_2mg_libs(names):
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"""Built a micro/macro two group openmc MGXS libraries"""
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# Initialized library params
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group_edges = [0.0, 0.625, 20.0e6]
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groups = openmc.mgxs.EnergyGroups(group_edges=group_edges)
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mg_cross_sections_file_micro = openmc.MGXSLibrary(groups)
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mg_cross_sections_file_macro = openmc.MGXSLibrary(groups)
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# Building a micro mg library
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micro_cs = create_micro_xs_dict()
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for name in names:
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mg_cross_sections_file_micro.add_xsdata(build_openmc_xs_lib(name,
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groups,
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[t for t in
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micro_cs],
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micro_cs))
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# Building a macro mg library
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macro_xs = create_macro_dict(micro_cs)
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mg_cross_sections_file_macro.add_xsdata(build_openmc_xs_lib('macro',
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groups,
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[t for t in
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macro_xs],
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macro_xs))
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# Exporting library to hdf5 files
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mg_cross_sections_file_micro.export_to_hdf5('micro_2g.h5')
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mg_cross_sections_file_macro.export_to_hdf5('macro_2g.h5')
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# Returning the macro_xs dict is needed for analytical solution
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return macro_xs
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def analytical_solution_2g_therm(xsmin, xsmax=None, wgt=1.0):
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""" Calculate eigenvalue based on analytical solution for eq Lf = (1/k)Qf
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in two group for infinity dilution media in assumption of group
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boundary in thermal spectra < 1.e+3 Ev
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Parameters:
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----------
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xsmin : dict
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macro cross-sections dictionary with minimum range temperature
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xsmax : dict
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macro cross-sections dictionary with maximum range temperature
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by default: None not used for standalone temperature
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wgt : float
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weight for interpolation by default 1.0
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Returns:
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-------
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keff : np.float64
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analytical eigenvalue of critical eq matrix
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"""
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if xsmax is None:
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sa = xsmin['absorption']['macro']
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ss12 = xsmin['scatter']['macro'][0][1][0]
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nsf = xsmin['nu-fission']['macro']
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else:
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sa = xsmin['absorption']['macro'] * wgt + \
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xsmax['absorption']['macro'] * (1 - wgt)
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ss12 = xsmin['scatter']['macro'][0][1][0] * wgt + \
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xsmax['scatter']['macro'][0][1][0] * (1 - wgt)
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nsf = xsmin['nu-fission']['macro'] * wgt + \
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xsmax['nu-fission']['macro'] * (1 - wgt)
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L = np.array([sa[0] + ss12, 0.0, -ss12, sa[1]]).reshape(2, 2)
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Q = np.array([nsf[0], nsf[1], 0.0, 0.0]).reshape(2, 2)
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arr = np.linalg.inv(L).dot(Q)
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return np.amax(np.linalg.eigvals(arr))
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def build_inf_model(xsnames, xslibname, temperature, tempmethod='nearest'):
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""" Building an infinite medium for openmc multi-group testing
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Parameters:
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----------
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xsnames : list of str()
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list with xs names
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xslibname:
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name of hdf5 file with cross-section library
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temperature : float
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value of a current temperature in K
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tempmethod : {'nearest', 'interpolation'}
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by default 'nearest'
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"""
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inf_medium = openmc.Material(name='test material', material_id=1)
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inf_medium.set_density("sum")
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for xs in xsnames:
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inf_medium.add_nuclide(xs, 1)
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INF = 11.1
|
||||
# Instantiate a Materials collection and export to XML
|
||||
materials_file = openmc.Materials([inf_medium])
|
||||
materials_file.cross_sections = xslibname
|
||||
materials_file.export_to_xml()
|
||||
|
||||
# Instantiate boundary Planes
|
||||
min_x = openmc.XPlane(boundary_type='reflective', x0=-INF)
|
||||
max_x = openmc.XPlane(boundary_type='reflective', x0=INF)
|
||||
min_y = openmc.YPlane(boundary_type='reflective', y0=-INF)
|
||||
max_y = openmc.YPlane(boundary_type='reflective', y0=INF)
|
||||
|
||||
# Instantiate a Cell
|
||||
cell = openmc.Cell(cell_id=1, name='cell')
|
||||
cell.temperature = temperature
|
||||
# Register bounding Surfaces with the Cell
|
||||
cell.region = +min_x & -max_x & +min_y & -max_y
|
||||
|
||||
# Fill the Cell with the Material
|
||||
cell.fill = inf_medium
|
||||
|
||||
# Create root universe
|
||||
root_universe = openmc.Universe(name='root universe', cells=[cell])
|
||||
|
||||
# Create Geometry and set root Universe
|
||||
openmc_geometry = openmc.Geometry(root_universe)
|
||||
|
||||
# Export to "geometry.xml"
|
||||
openmc_geometry.export_to_xml()
|
||||
|
||||
# OpenMC simulation parameters
|
||||
batches = 200
|
||||
inactive = 5
|
||||
particles = 5000
|
||||
|
||||
# Instantiate a Settings object
|
||||
settings_file = openmc.Settings()
|
||||
settings_file.batches = batches
|
||||
settings_file.inactive = inactive
|
||||
settings_file.particles = particles
|
||||
settings_file.energy_mode = 'multi-group'
|
||||
settings_file.output = {'summary': False}
|
||||
# Create an initial uniform spatial source distribution over fissionable zones
|
||||
bounds = [-INF, -INF, -INF, INF, INF, INF]
|
||||
uniform_dist = openmc.stats.Box(bounds[:3], bounds[3:], only_fissionable=True)
|
||||
settings_file.temperature = {'method': tempmethod}
|
||||
settings_file.source = openmc.Source(space=uniform_dist)
|
||||
settings_file.export_to_xml()
|
||||
40
tests/regression_tests/mg_temperature/results_true.dat
Normal file
40
tests/regression_tests/mg_temperature/results_true.dat
Normal file
|
|
@ -0,0 +1,40 @@
|
|||
micro, method: nearest, t: 300.0, k-combined:
|
||||
1.439920E+00 4.801994E-04
|
||||
kanalyt
|
||||
1.440410E+00
|
||||
micro, method: nearest, t: 600.0, k-combined:
|
||||
1.410482E+00 4.811844E-04
|
||||
kanalyt
|
||||
1.410164E+00
|
||||
micro, method: nearest, t: 900.0, k-combined:
|
||||
1.408198E+00 4.885882E-04
|
||||
kanalyt
|
||||
1.407830E+00
|
||||
micro, method: interpolation, t: 520.0, k-combined:
|
||||
1.418780E+00 5.222658E-04
|
||||
kanalyt
|
||||
1.418514E+00
|
||||
micro, method: interpolation, t: 600.0, k-combined:
|
||||
1.410482E+00 4.811844E-04
|
||||
kanalyt
|
||||
1.410164E+00
|
||||
macro, method: nearest, t: 300.0, k-combined:
|
||||
1.439920E+00 4.801994E-04
|
||||
kanalyt
|
||||
1.440410E+00
|
||||
macro, method: nearest, t: 600.0, k-combined:
|
||||
1.410482E+00 4.811844E-04
|
||||
kanalyt
|
||||
1.410164E+00
|
||||
macro, method: nearest, t: 900.0, k-combined:
|
||||
1.408198E+00 4.885882E-04
|
||||
kanalyt
|
||||
1.407830E+00
|
||||
macro, method: interpolation, t: 520.0, k-combined:
|
||||
1.418780E+00 5.222658E-04
|
||||
kanalyt
|
||||
1.418514E+00
|
||||
macro, method: interpolation, t: 600, k-combined:
|
||||
1.410482E+00 4.811844E-04
|
||||
kanalyt
|
||||
1.410164E+00
|
||||
116
tests/regression_tests/mg_temperature/test.py
Normal file
116
tests/regression_tests/mg_temperature/test.py
Normal file
|
|
@ -0,0 +1,116 @@
|
|||
import os
|
||||
from tests.regression_tests.mg_temperature.build_2g import *
|
||||
from tests.testing_harness import *
|
||||
import shutil
|
||||
|
||||
|
||||
class MgTemperatureTestHarness(TestHarness):
|
||||
|
||||
def execute_test(self):
|
||||
"""Run OpenMC with the appropriate arguments and check the outputs."""
|
||||
base_dir = os.getcwd()
|
||||
overall_results = []
|
||||
macro_xs = create_openmc_2mg_libs(names)
|
||||
types = ('micro', 'micro',
|
||||
'micro', 'micro',
|
||||
'micro',
|
||||
'macro', 'macro',
|
||||
'macro', 'macro',
|
||||
'macro')
|
||||
temperatures = (300., 600., 900.,
|
||||
520., 600.,
|
||||
300., 600., 900.,
|
||||
520., 600)
|
||||
methods = 2 * (3 * ('nearest',) + 2 * ('interpolation',))
|
||||
analyt_interp = 10 * [None]
|
||||
analyt_interp[3] = (600. - 520.) / 300.
|
||||
analyt_interp[8] = (600. - 520.) / 300.
|
||||
try:
|
||||
if (os.path.isdir("./temp")):
|
||||
shutil.rmtree("./temp")
|
||||
os.mkdir("temp")
|
||||
os.chdir(os.path.join(base_dir, "temp"))
|
||||
for cs, t, m, ai in zip(types, temperatures, methods, analyt_interp):
|
||||
if (cs == 'macro'):
|
||||
build_inf_model(['macro'], '../macro_2g.h5', t, m)
|
||||
else:
|
||||
build_inf_model(names, '../micro_2g.h5', t, m)
|
||||
if not ai:
|
||||
kanalyt = analytical_solution_2g_therm(macro_xs[t])
|
||||
else:
|
||||
kanalyt = analytical_solution_2g_therm(macro_xs[300],
|
||||
macro_xs[600], ai)
|
||||
self._run_openmc()
|
||||
self._test_output_created()
|
||||
string = "{}, method: {}, t: {}, {}kanalyt\n{:12.6E}\n"
|
||||
results = string.format(cs, m, t, self._get_results(), kanalyt)
|
||||
overall_results.append(results)
|
||||
os.chdir(base_dir)
|
||||
self._write_results("".join(overall_results))
|
||||
self._compare_results()
|
||||
finally:
|
||||
os.chdir(base_dir)
|
||||
shutil.copyfile("results_test.dat", "results_true.dat")
|
||||
if (os.path.isdir("./temp")):
|
||||
shutil.rmtree("./temp")
|
||||
self._cleanup()
|
||||
for f in ['micro_2g.h5', 'macro_2g.h5']:
|
||||
if os.path.exists(f):
|
||||
os.remove(f)
|
||||
|
||||
def update_results(self):
|
||||
"""Update the results_true using the current version of OpenMC."""
|
||||
base_dir = os.getcwd()
|
||||
overall_results = []
|
||||
macro_xs = create_openmc_2mg_libs(names)
|
||||
types = ('micro', 'micro',
|
||||
'micro', 'micro',
|
||||
'micro',
|
||||
'macro', 'macro',
|
||||
'macro', 'macro',
|
||||
'macro')
|
||||
temperatures = (300., 600., 900.,
|
||||
520., 600.,
|
||||
300., 600., 900.,
|
||||
520., 600)
|
||||
methods = 2 * (3 * ('nearest',) + 2 * ('interpolation',))
|
||||
analyt_interp = 10 * [None]
|
||||
analyt_interp[3] = (600. - 520.) / 300.
|
||||
analyt_interp[8] = (600. - 520.) / 300.
|
||||
try:
|
||||
if (os.path.isdir("./temp")):
|
||||
shutil.rmtree("./temp")
|
||||
os.mkdir("temp")
|
||||
os.chdir(os.path.join(base_dir, "temp"))
|
||||
for cs, t, m, ai in zip(types, temperatures, methods, analyt_interp):
|
||||
if (cs == 'macro'):
|
||||
build_inf_model(['macro'], '../macro_2g.h5', t, m)
|
||||
else:
|
||||
build_inf_model(names, '../micro_2g.h5', t, m)
|
||||
if not ai:
|
||||
kanalyt = analytical_solution_2g_therm(macro_xs[t])
|
||||
else:
|
||||
kanalyt = analytical_solution_2g_therm(macro_xs[300],
|
||||
macro_xs[600], ai)
|
||||
self._run_openmc()
|
||||
self._test_output_created()
|
||||
string = "{}, method: {}, t: {}, {}kanalyt\n{:12.6E}\n"
|
||||
results = string.format(cs, m, t, self._get_results(), kanalyt)
|
||||
overall_results.append(results)
|
||||
os.chdir(base_dir)
|
||||
self._write_results("".join(overall_results))
|
||||
self._compare_results()
|
||||
finally:
|
||||
os.chdir(base_dir)
|
||||
shutil.copyfile("results_test.dat", "results_true.dat")
|
||||
if (os.path.isdir("./temp")):
|
||||
shutil.rmtree("./temp")
|
||||
self._cleanup()
|
||||
for f in ['micro_2g.h5', 'macro_2g.h5']:
|
||||
if os.path.exists(f):
|
||||
os.remove(f)
|
||||
|
||||
|
||||
def test_mg_temperature():
|
||||
harness = MgTemperatureTestHarness('statepoint.200.h5')
|
||||
harness.main()
|
||||
Loading…
Add table
Add a link
Reference in a new issue