def create_openmc_2mg_libs(names):
"""Built a micro/macro two group openmc MGXS libraries"""
# Initialized library params
group_edges = [0.0, 0.625, 20.0e6]
groups = openmc.mgxs.EnergyGroups(group_edges=group_edges)
mg_cross_sections_file_micro = openmc.MGXSLibrary(groups)
mg_cross_sections_file_macro = openmc.MGXSLibrary(groups)
# Building a micro mg library
micro_cs = create_micro_xs_dict()
for name in names:
mg_cross_sections_file_micro.add_xsdata(build_openmc_xs_lib(name,
groups,
[t for t in
micro_cs],
micro_cs))
# Building a macro mg library
macro_xs = create_macro_dict(micro_cs)
mg_cross_sections_file_macro.add_xsdata(build_openmc_xs_lib('macro',
groups,
[t for t in
macro_xs],
macro_xs))
# Exporting library to hdf5 files
mg_cross_sections_file_micro.export_to_hdf5('micro_2g.h5')
mg_cross_sections_file_macro.export_to_hdf5('macro_2g.h5')
# Returning the macro_xs dict is needed for analytical solution
return macro_xs
def create_6g():
# Instantiate the energy group data and file object
groups = GROUP_STRUCT[6]
mg_cross_sections_file = openmc.MGXSLibrary(groups)
###########################################################################
# 7 URR
nu = [3.0, 2.5, 2.0, 2.0, 2.50, 3.0]
fiss = np.array([0.006, 0.060, 0.90, 0.90, 0.060, 0.006])
capture = [0.006, 0.040, 0.20, 0.2, 0.04, 0.006]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.024, 0.171, 0.033, 0.00, 0.00, 0.00],
[0.000, 0.600, 0.275, 0.00, 0.00, 0.00],
[0.000, 0.000, 2.000, 0.00, 0.00, 0.00],
[0.000, 0.000, 0.000, 2.00, 0.00, 0.00],
[0.000, 0.000, 0.000, 0.275, 0.60, 0.00],
[0.000, 0.000, 2.000, 0.033, 0.171, 0.024]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.240, 0.975, 3.10, 3.10, 0.975, 0.240]
chi = [0.48, 0.02, 0.0, 0.0, 0.02, 0.048]
URR = set_it('URR', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(URR)
mg_cross_sections_file.export_to_hdf5('6g.h5')
def create_library():
# Instantiate the energy group data and file object
groups = openmc.mgxs.EnergyGroups(group_edges=[0.0, 0.625, 20.0e6])
mg_cross_sections_file = openmc.MGXSLibrary(groups)
# Make the base, isotropic data
nu = [2.50, 2.50]
fiss = np.array([0.002817, 0.097])
capture = [0.008708, 0.02518]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.31980, 0.06694, 0.003],
[0.004555, -0.0003972, 0.00002]],
[[0.00000, 0.00000, 0.000],
[0.424100, 0.05439000, 0.0025]]])
total = [0.33588, 0.54628]
chi = [1., 0.]
mat_1 = openmc.XSdata('mat_1', groups)
mat_1.order = 2
mat_1.set_nu_fission(np.multiply(nu, fiss))
mat_1.set_absorption(absorption)
mat_1.set_scatter_matrix(scatter)
mat_1.set_total(total)
mat_1.set_chi(chi)
mg_cross_sections_file.add_xsdata(mat_1)
# Write the file
mg_cross_sections_file.export_to_hdf5('2g.h5')
def make_libgroup_micro(nameoflib):
libgroup = temp_libgroup(tempdata)
openmclib = {}
for tt in tempdata:
for n in libgroup[tt]:
scatter = np.zeros((len(ENERGIES) - 1, len(ENERGIES) - 1, 2), dtype=np.double)
if (n in openmclib):
openmclib[n].set_total(libgroup[tt][n].stot, temperature=tt)
openmclib[n].set_absorption(libgroup[tt][n].sabs, temperature=tt)
scatter += libgroup[tt][n].xsmatrix*1.0
openmclib[n].set_scatter_matrix(scatter, temperature=tt)
openmclib[n].set_fission(libgroup[tt][n].sf, temperature=tt)
openmclib[n].set_nu_fission(libgroup[tt][n].nusf, temperature=tt)
openmclib[n].set_chi(libgroup[tt][n].schi, temperature=tt)
else:
openmclib[n] = openmc.XSdata(n, groups, temperatures=tempdata)
if (libgroup[tt][n].xsmatrix.shape[-1] < 2):
openmclib[n].order = 0
else:
openmclib[n].order = 1
openmclib[n].order = 1
openmclib[n].set_total(libgroup[tt][n].stot, temperature=tt)
openmclib[n].set_absorption(libgroup[tt][n].sabs, temperature=tt)
scatter += libgroup[tt][n].xsmatrix*1.0
openmclib[n].set_scatter_matrix(scatter, temperature=tt)
openmclib[n].set_fission(libgroup[tt][n].sf, temperature=tt)
openmclib[n].set_nu_fission(libgroup[tt][n].nusf, temperature=tt)
openmclib[n].set_chi(libgroup[tt][n].schi, temperature=tt)
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.add_xsdatas([openmclib[o] for o in openmclib])
mg_cross_sections_file.export_to_hdf5(nameoflib)
def build_mgxs_library(convert):
# Instantiate the energy group data
groups = openmc.mgxs.EnergyGroups(group_edges=[1e-5, 0.625, 20.0e6])
# Instantiate the 2-group (C5G7) cross section data
uo2_xsdata = openmc.XSdata('UO2', groups)
uo2_xsdata.order = 2
uo2_xsdata.set_total([2., 2.])
uo2_xsdata.set_absorption([1., 1.])
scatter_matrix = np.array([[[0.75, 0.25],
[0.00, 1.00]],
[[0.75 / 3., 0.25 / 3.],
[0.00 / 3., 1.00 / 3.]],
[[0.75 / 4., 0.25 / 4.],
[0.00 / 4., 1.00 / 4.]]])
scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
uo2_xsdata.set_scatter_matrix(scatter_matrix)
uo2_xsdata.set_fission([0.5, 0.5])
uo2_xsdata.set_nu_fission([1., 1.])
uo2_xsdata.set_chi([1., 0.])
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.add_xsdatas([uo2_xsdata])
if convert is not None:
if isinstance(convert[0], list):
for conv in convert:
if conv[0] in ['legendre', 'tabular', 'histogram']:
mg_cross_sections_file = \
mg_cross_sections_file.convert_scatter_format(
conv[0], conv[1])
elif conv[0] in ['angle', 'isotropic']:
mg_cross_sections_file = \
mg_cross_sections_file.convert_representation(
conv[0], conv[1], conv[1])
elif convert[0] in ['legendre', 'tabular', 'histogram']:
mg_cross_sections_file = \
mg_cross_sections_file.convert_scatter_format(
convert[0], convert[1])
elif convert[0] in ['angle', 'isotropic']:
mg_cross_sections_file = \
mg_cross_sections_file.convert_representation(
convert[0], convert[1], convert[1])
mg_cross_sections_file.export_to_hdf5()
def make_libgroup_macro(nameoflib):
res,resl, dicel, el, rodel, dolna = make_model()
libgroup = temp_libgroup(tempdata)
nuclval = len(resl)
indexNa = el.index("Na")
for key, value in dicel.items():
value[indexNa] = densna(600.0) * 0.6022 / 23 * dolna[key[0]][key[1]]
for key, value in rodel.items():
value[indexNa] = densna(600.0) * 0.6022 / 23 * dolna[key[0]][key[1]]
nuclist, element_from, element_ind, element_val = get_unite_list(resl, el)
concentration = np.zeros(len(nuclist))
conc = {}
temp = {}
for key,value in res.items():
t0 = time.time()
concentration[:nuclval] = value
for f, i, v in zip(element_from, element_ind, element_val):
concentration[i] += dicel[key][f] * v
key_1 = ''+str(key)+''
conc[key_1] = concentration
temp[key_1] = 600.0 # for all zones a temperature the same : 600.0
concentration = 0.0*concentration[:]
print("Estimated time is {} min".format((time.time() - t0)))
rodnuclist, element_from, element_ind, element_val = get_unite_list([], el)
concentration = np.zeros(len(rodnuclist))
concrod = {}
temprod = {}
for key,value in rodel.items():
t0 = time.time()
for f, i, v in zip(element_from, element_ind, element_val):
concentration[i] += rodel[key][f] * v
key_1 = ''+str(key)+''
concrod[key_1] = concentration
temprod[key_1] = 600.0 # for all zones a temperature the same : 600.0
concentration = 0.0*concentration[:]
print("Estimated time is {} min".format((time.time() - t0)))
openmclib = prepare_mg(libgroup, conc, resl, tempdata,
groups, temp)
openmclib.update(prepare_mg(libgroup, concrod, rodnuclist, tempdata,
groups, temprod))
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.add_xsdatas([openmclib[o] for o in openmclib])
mg_cross_sections_file.export_to_hdf5(nameoflib)
def create_library():
# Instantiate the energy group data and file object
groups = openmc.mgxs.EnergyGroups(group_edges=[0.0, 0.625, 20.0e6])
mg_cross_sections_file = openmc.MGXSLibrary(groups, 6)
# Make the base, isotropic data
nu = np.array([2.50, 2.50])
fiss = np.array([0.002817, 0.097])
capture = np.array([0.008708, 0.02518])
absorption = capture + fiss
scatter = np.array([[[0.31980, 0.06694], [0.004555, -0.0003972]],
[[0.00000, 0.00000], [0.424100, 0.05439000]]])
total = np.array([0.33588, 0.54628])
chi = np.array([1., 0.])
decay_rate = np.array(
[0.013336, 0.032739, 0.12078, 0.30278, 0.84949, 2.853])
delayed_yield = np.array([
0.00055487, 0.00286407, 0.00273429, 0.0061305, 0.00251342, 0.00105286
])
inv_vel = 1.0 / np.array([1.4e9, 4.4e5])
mat_1 = openmc.XSdata('mat_1', groups, num_delayed_groups=6)
mat_1.order = 1
mat_1.set_fission(fiss)
mat_1.set_kappa_fission(fiss * 200e6)
mat_1.set_nu_fission(nu * fiss)
mat_1.set_beta(delayed_yield / 2.5)
mat_1.set_decay_rate(decay_rate)
mat_1.set_absorption(absorption)
mat_1.set_scatter_matrix(scatter)
mat_1.set_total(total)
mat_1.set_chi(chi)
mat_1.set_inverse_velocity(inv_vel)
mg_cross_sections_file.add_xsdata(mat_1)
# Write the file
mg_cross_sections_file.export_to_hdf5('2g.h5')
0.0000000, 0.2823340, 0.1299400, 0.0006234, 0.0000480, 0.0000074, 0.0000010
], [
0.0000000, 0.0000000, 0.3452560, 0.2245700, 0.0169990, 0.0026443, 0.0005034
], [
0.0000000, 0.0000000, 0.0000000, 0.0910284, 0.4155100, 0.0637320, 0.0121390
], [
0.0000000, 0.0000000, 0.0000000, 0.0000714, 0.1391380, 0.5118200, 0.0612290
], [
0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0022157, 0.6999130, 0.5373200
], [
0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.1324400, 2.4807000
]]])
scatter_matrix = np.rollaxis(scatter_matrix, 0, 3)
h2o_xsdata.set_scatter_matrix(scatter_matrix)
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.add_xsdatas([uo2_xsdata, h2o_xsdata])
mg_cross_sections_file.export_to_hdf5()
###############################################################################
# Create materials for the problem
# Instantiate some Macroscopic Data
uo2_data = openmc.Macroscopic('UO2')
h2o_data = openmc.Macroscopic('LWTR')
# Instantiate some Materials and register the appropriate Macroscopic objects
uo2 = openmc.Material(name='UO2 fuel')
uo2.set_density('macro', 1.0)
uo2.add_macroscopic(uo2_data)
def create_library():
# Instantiate the energy group data and file object
groups = openmc.mgxs.EnergyGroups(group_edges=[0.0, 0.625, 20.0e6])
mg_cross_sections_file = openmc.MGXSLibrary(groups)
# Make the base, isotropic data
nu = [2.50, 2.50]
fiss = np.array([0.002817, 0.097])
capture = [0.008708, 0.02518]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.31980, 0.06694], [0.004555, -0.0003972]],
[[0.00000, 0.00000], [0.424100, 0.05439000]]])
total = [0.33588, 0.54628]
chi = [1., 0.]
mat_1 = openmc.XSdata('mat_1', groups)
mat_1.order = 1
mat_1.set_nu_fission(np.multiply(nu, fiss))
mat_1.set_absorption(absorption)
mat_1.set_scatter_matrix(scatter)
mat_1.set_total(total)
mat_1.set_chi(chi)
mg_cross_sections_file.add_xsdata(mat_1)
# Make a version of mat-1 which has a tabular representation of the
# scattering vice Legendre with 33 points
mat_2 = mat_1.convert_scatter_format('tabular', 33)
mat_2.name = 'mat_2'
mg_cross_sections_file.add_xsdata(mat_2)
# Make a version of mat-1 which has a histogram representation of the
# scattering vice Legendre with 33 bins
mat_3 = mat_1.convert_scatter_format('histogram', 33)
mat_3.name = 'mat_3'
mg_cross_sections_file.add_xsdata(mat_3)
# Make a version which uses a fission matrix vice chi & nu-fission
mat_4 = openmc.XSdata('mat_4', groups)
mat_4.order = 1
mat_4.set_nu_fission(np.outer(np.multiply(nu, fiss), chi))
mat_4.set_absorption(absorption)
mat_4.set_scatter_matrix(scatter)
mat_4.set_total(total)
mg_cross_sections_file.add_xsdata(mat_4)
# Make an angle-dependent version of mat_1 with 2 polar and 2 azim. angles
mat_5 = mat_1.convert_representation('angle', 2, 2)
mat_5.name = 'mat_5'
mg_cross_sections_file.add_xsdata(mat_5)
# Make a copy of mat_1 for testing microscopic cross sections
mat_6 = openmc.XSdata('mat_6', groups)
mat_6.order = 1
mat_6.set_nu_fission(np.multiply(nu, fiss))
mat_6.set_absorption(absorption)
mat_6.set_scatter_matrix(scatter)
mat_6.set_total(total)
mat_6.set_chi(chi)
mg_cross_sections_file.add_xsdata(mat_6)
# Write the file
mg_cross_sections_file.export_to_hdf5('2g.h5')
def _build_inputs(self):
# Define materials
water = openmc.Material(1)
water.add_nuclide('H1', 2.0)
water.add_nuclide('O16', 1.0)
water.add_nuclide('B10', 0.0001)
if self.is_ce:
water.add_s_alpha_beta('c_H_in_H2O')
water.set_density('g/cc', 1.0)
fuel = openmc.Material(2)
fuel.add_nuclide('U235', 1.0)
fuel.add_nuclide('Mo99', 0.1)
fuel.set_density('g/cc', 4.5)
materials = openmc.Materials((water, fuel))
if not self.is_ce:
materials.cross_sections = 'mg_lib.h5'
materials.export_to_xml()
cyl = openmc.ZCylinder(surface_id=1, r=1.0, boundary_type='vacuum')
top_sphere = openmc.Sphere(surface_id=2,
z0=5.,
r=1.,
boundary_type='vacuum')
top_plane = openmc.ZPlane(surface_id=3, z0=5.)
bottom_sphere = openmc.Sphere(surface_id=4,
z0=-5.,
r=1.,
boundary_type='vacuum')
bottom_plane = openmc.ZPlane(surface_id=5, z0=-5.)
# Define geometry
inside_cyl = openmc.Cell(1,
fill=fuel,
region=-cyl & -top_plane & +bottom_plane)
top_hemisphere = openmc.Cell(2,
fill=water,
region=-top_sphere & +top_plane)
bottom_hemisphere = openmc.Cell(3,
fill=water,
region=-bottom_sphere & -top_plane)
root = openmc.Universe(0,
cells=(inside_cyl, top_hemisphere,
bottom_hemisphere))
geometry = openmc.Geometry(root)
geometry.export_to_xml()
# Set up stochastic volume calculation
ll, ur = root.bounding_box
vol_calcs = [
openmc.VolumeCalculation(list(root.cells.values()), 100000),
openmc.VolumeCalculation([water, fuel], 100000, ll, ur),
openmc.VolumeCalculation([root], 100000, ll, ur),
openmc.VolumeCalculation(list(root.cells.values()), 100),
openmc.VolumeCalculation([water, fuel], 100, ll, ur),
openmc.VolumeCalculation(list(root.cells.values()), 100)
]
vol_calcs[3].set_trigger(self.exp_std_dev, 'std_dev')
vol_calcs[4].set_trigger(self.exp_rel_err, 'rel_err')
vol_calcs[5].set_trigger(self.exp_variance, 'variance')
# Define settings
settings = openmc.Settings()
settings.run_mode = 'volume'
if not self.is_ce:
settings.energy_mode = 'multi-group'
settings.volume_calculations = vol_calcs
settings.export_to_xml()
# Create the MGXS file if necessary
if not self.is_ce:
groups = openmc.mgxs.EnergyGroups(group_edges=[0., 20.e6])
mg_xs_file = openmc.MGXSLibrary(groups)
nu = [2.]
fiss = [1.]
capture = [1.]
absorption_fissile = np.add(fiss, capture)
absorption_other = capture
scatter = np.array([[[1.]]])
total_fissile = np.add(absorption_fissile,
np.sum(scatter[:, :, 0], axis=1))
total_other = np.add(absorption_other,
np.sum(scatter[:, :, 0], axis=1))
chi = [1.]
for iso in ['H1', 'O16', 'B10', 'Mo99', 'U235']:
mat = openmc.XSdata(iso, groups)
mat.order = 0
mat.atomic_weight_ratio = \
openmc.data.atomic_mass(iso) / openmc.data.NEUTRON_MASS
mat.set_scatter_matrix(scatter)
if iso == 'U235':
mat.set_nu_fission(np.multiply(nu, fiss))
mat.set_absorption(absorption_fissile)
mat.set_total(total_fissile)
mat.set_chi(chi)
else:
mat.set_absorption(absorption_other)
mat.set_total(total_other)
mg_xs_file.add_xsdata(mat)
mg_xs_file.export_to_hdf5('mg_lib.h5')
def create_1g():
# Instantiate the energy group data and file object
groups = GROUP_STRUCT[1]
mg_cross_sections_file = openmc.MGXSLibrary(groups)
###########################################################################
# PUa, Sec 4.1.1
nu = 3.24
fiss = [0.0816]
capture = [0.019584]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.225216]]])
total = [0.32640]
chi = [1.]
PUa = set_it('PUa', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(PUa)
###########################################################################
# PUb, Sec 4.1.1
nu = 2.84
PUb = set_it('PUb', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(PUb)
###########################################################################
# H2O, Sec 4.1.1
nu = 0.
fiss = None
capture = [0.032640]
absorption = capture
scatter = np.array([[[0.293760]]])
total = [0.32640]
chi = None
H2O = set_it('H2O', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(H2O)
###########################################################################
# Ua, Sec 4.1.2
nu = 2.70
fiss = [0.065280]
capture = [0.013056]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.248064]]])
total = [0.32640]
chi = [1.]
Ua = set_it('Ua', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ua)
###########################################################################
# Ub, Sec 4.1.2
nu = 2.797101
Ub = set_it('Ub', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ub)
###########################################################################
# Uc, Sec 4.1.2
nu = 2.707308
Uc = set_it('Uc', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Uc)
###########################################################################
# Ud, Sec 4.1.2
nu = 2.679198
Ud = set_it('Ud', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ud)
###########################################################################
# UD2O, Sec 4.1.3
nu = 1.70
fiss = [0.054628]
capture = [0.027314]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.464338]]])
total = [0.54628]
chi = [1.]
UD2O = set_it('UD2O', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(UD2O)
###########################################################################
# H2O, Sec 4.1.3
nu = 0.
fiss = None
capture = [0.054628]
absorption = capture
scatter = np.array([[[0.491652]]])
total = [0.54628]
chi = None
H2O_2 = set_it('H2O_2', groups, 0, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(H2O_2)
###########################################################################
# Ue, Sec 4.1.4
nu = 2.50
fiss = [0.06922744]
capture = [0.01013756]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.328042]]])
total = [0.407407]
chi = [1.]
Ue = set_it('Ue', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ue)
###########################################################################
# Fe, Sec 4.1.4
nu = 0.
fiss = None
capture = [0.00046512]
absorption = capture
scatter = np.array([[[0.23209488]]])
total = [0.23256]
chi = None
Fe = set_it('Fe', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Fe)
###########################################################################
# Na, Sec 4.1.4
nu = 0.
fiss = None
capture = [0.0]
absorption = capture
scatter = np.array([[[0.086368032]]])
total = [0.086368032]
chi = None
Na = set_it('Na', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Na)
###########################################################################
# PUa-1, Sec 4.1.4
nu = 2.5
fiss = [0.266667]
capture = [0.0]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.733333, 0.2]]])
total = [1.]
chi = [1.]
PUa_1 = set_it('PUa1', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(PUa_1)
###########################################################################
# PUb-2, Sec 4.2.1
scatter = np.array([[[0.733333, 0.333333]]])
PUb_1 = set_it('PUb1', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(PUb_1)
###########################################################################
# PUa-2, Sec 4.1.4
nu = 2.5
fiss = [0.266667]
capture = [0.0]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.733333, 0.2, 0.075]]])
total = [1.]
chi = [1.]
PUa_2 = set_it('PUa2', groups, 2, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(PUa_2)
###########################################################################
# PUb-2, Sec 4.2.1
scatter = np.array([[[0.733333, 0.333333, 0.125]]])
PUb_2 = set_it('PUb2', groups, 2, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(PUb_2)
###########################################################################
# Ua-1, Sec 4.1.4
nu = 2.70
fiss = [0.065280]
capture = [0.013056]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.248064, 0.042432]]])
total = [0.32640]
chi = [1.]
Ua_1 = set_it('Ua1', groups, 1, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ua_1)
###########################################################################
# Ub-1, Sec 4.2.1
scatter = np.array([[[0.248064, 0.212160]]])
Ub_1 = set_it('Ub1', groups, 1, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Ub_1)
###########################################################################
# UD2Oa-1, Sec 4.2.3
nu = 1.808381
fiss = [0.054628]
capture = [0.027314]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.464338, 0.056312624]]])
total = [0.54628]
chi = [1.]
UD2Oa = set_it('UD2Oa', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(UD2Oa)
###########################################################################
# UD2Ob-1, Sec 4.2.3
nu = 1.841086
scatter = np.array([[[0.464338, 0.112982569]]])
UD2Ob = set_it('UD2Ob', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(UD2Ob)
###########################################################################
# UD2Oc-1, Sec 4.2.3
nu = 1.6964
scatter = np.array([[[0.464338, -0.27850447]]])
UD2Oc = set_it('UD2Oc', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(UD2Oc)
mg_cross_sections_file.export_to_hdf5('1g.h5')
def create_2g():
# Instantiate the energy group data and file object
groups = GROUP_STRUCT[2]
mg_cross_sections_file = openmc.MGXSLibrary(groups)
###########################################################################
# 5.1.1 Pu
nu = [3.10, 2.93]
fiss = np.array([0.0936, 0.08544])
capture = [0.00480, 0.0144]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.0792, 0.0432], [0.00000, 0.23616]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.2208, 0.3360]
chi = [0.575, 0.425]
Pu = set_it('Pu', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(Pu)
###########################################################################
# 5.1.2 U
nu = [2.70, 2.5]
fiss = np.array([0.06192, 0.06912])
capture = [0.00384, 0.01344]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.078240, 0.0720], [0.00000, 0.26304]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.2160, 0.3456]
chi = [0.575, 0.425]
U = set_it('U', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(U)
###########################################################################
# 5.1.3 UAl
nu = [0.0, 2.830023]
fiss = np.array([0.0, 0.060706])
capture = [0.000217, 0.003143]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.247516, 0.020432], [0.000000, 1.213127]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.268165, 1.276976]
chi = [1.0, 0.0]
UAl = set_it('UAl', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(UAl)
###########################################################################
# 5.1.4 URRa-0
nu = [2.5, 2.5]
fiss = np.array([0.0010484, 0.050632])
capture = [0.0010046, 0.025788]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.62568, 0.029227], [0.00000, 2.443830]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.65696, 2.52025]
chi = [1., 0.]
URRa_0 = set_it('URRa0', groups, 0, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(URRa_0)
###########################################################################
# 5.1.4 URRb-0
fiss = np.array([0.000836, 0.029564])
capture = [0.001104, 0.024069]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.838920, 0.046350], [0.000767, 2.918300]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.88721, 2.9727]
chi = [1., 0.]
URRb_0 = set_it('URRb0', groups, 0, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(URRb_0)
###########################################################################
# 5.1.4 URRc-0
fiss = np.array([0.001648, 0.057296])
capture = [0.001472, 0.029244]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.838070, 0.045360], [0.001160, 2.8751]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.88655, 2.9628]
chi = [1., 0.]
URRc_0 = set_it('URRc0', groups, 0, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(URRc_0)
###########################################################################
# 5.1.4 H2Oa
nu = None
fiss = None
capture = [0.00074, 0.018564]
absorption = capture
scatter = np.array([[[0.839750, 0.04749], [0.000336, 2.96760]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.88798, 2.9865]
chi = None
H2Oa = set_it('H2Oa', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(H2Oa)
###########################################################################
# 5.1.4 URRd-0
nu = [1.004, 2.50]
fiss = np.array([0.61475, 0.045704])
capture = [0.0019662, 0.023496]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.000000, 0.0342008], [0.000000, 2.0688000]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.650917, 2.13800]
chi = [1., 0.]
URRd_0 = set_it('URRd0', groups, 0, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(URRd_0)
###########################################################################
# 5.1.4 H2Ob
nu = None
fiss = None
capture = [8.480293E-6, 0.00016]
absorption = capture
scatter = np.array([[[0.1096742149, 0.001000595707],
[0.0000000000, 0.363390000000]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.1106832906, 0.36355]
chi = None
H2Ob = set_it('H2Ob', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(H2Ob)
###########################################################################
# 5.1.4 H2Oc
nu = None
fiss = None
capture = [4.97229E-4, 0.0188]
absorption = capture
scatter = np.array([[[1.226381244, 0.1046395340], [0.0000000000,
4.35470]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [1.331518007, 4.37350]
chi = None
H2Oc = set_it('H2Oc', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(H2Oc)
###########################################################################
# 5.1.5 UD2O
nu = [2.50, 2.50]
fiss = np.array([0.002817, 0.097])
capture = [0.0087078, 0.02518]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.31980, 0.0045552], [0.000000, 0.42410]]])
scatter = np.rollaxis(scatter, 0, 3)
total = [0.33588, 0.54628]
chi = [1., 0.]
UD2O = set_it('UD2O', groups, 0, fiss, nu, absorption, scatter, total, chi)
mg_cross_sections_file.add_xsdata(UD2O)
###########################################################################
# 5.2.1 URR-1
nu = [2.5, 2.5]
fiss = np.array([0.0010484, 0.050632])
capture = [0.0010046, 0.025788]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.62568, 0.27459], [0.029227, 0.0075737]],
[[0.00000, 0.00000], [2.443830, 0.8331800]]])
total = [0.65696, 2.52025]
chi = [1., 0.]
URR_1 = set_it('URR1', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(URR_1)
###########################################################################
# 5.2.2 UD2O-1
nu = [2.50, 2.50]
fiss = np.array([0.0028172, 0.097])
capture = [0.0087078, 0.02518]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.31980, 0.06694], [0.004555, -0.0003972]],
[[0.00000, 0.00000], [0.424100, 0.05439000]]])
total = [0.33588, 0.54628]
chi = [1., 0.]
UD2O_1 = set_it('UD2O1', groups, 1, fiss, nu, absorption, scatter, total,
chi)
mg_cross_sections_file.add_xsdata(UD2O_1)
# Write the file
mg_cross_sections_file.export_to_hdf5('2g.h5')
Et = x + y + z + 1.0
Ec = 0.3*Et
Es = 0.7*Et
# assign XSs
xs.set_total([Et,Et], temperature=294.)
xs.set_absorption([Ec,Ec], temperature=294.)
xs.set_nu_fission([0.0,0.0], temperature=294.)
sct_matrx = [[[0.5*Es, 0.5*Es],
[0.0, Es]]]
sct_matrx = np.array(sct_matrx)
sct_matrx = np.rollaxis(sct_matrx, 0, 3)
xs.set_scatter_matrix(sct_matrx, temperature=294.)
# Add xs to XSDATAS
XSDATAS.append(xs)
mg_xs_file = openmc.MGXSLibrary(groups)
for i in range(len(XSDATAS)):
mg_xs_file.add_xsdata(XSDATAS[i])
mg_xs_file.export_to_hdf5('mgxsd.h5')
# Make Materials
materials = {}
for i in range(nxbins):
for j in range(nybins):
for k in range(nzbins):
xsname = str(i)+"."+str(j)+"."+str(k)
materials[xsname] = openmc.Material(name=xsname)
materials[xsname].set_density('macro', 1.)
materials[xsname].add_macroscopic(xsname)
mat_file = openmc.Materials(materials.values())
def create_library():
# Instantiate the energy group data and file object
groups = openmc.mgxs.EnergyGroups(group_edges=[0.0, 0.625, 20.0e6])
n_dg = 2
mg_cross_sections_file = openmc.MGXSLibrary(groups)
mg_cross_sections_file.num_delayed_groups = n_dg
beta = np.array([0.003, 0.003])
one_m_beta = 1. - np.sum(beta)
nu = [2.50, 2.50]
fiss = np.array([0.002817, 0.097])
capture = [0.008708, 0.02518]
absorption = np.add(capture, fiss)
scatter = np.array([[[0.31980, 0.06694], [0.004555, -0.0003972]],
[[0.00000, 0.00000], [0.424100, 0.05439000]]])
total = [0.33588, 0.54628]
chi = [1., 0.]
# Make the base data that uses chi & nu-fission vectors with a beta
mat_1 = openmc.XSdata('mat_1', groups)
mat_1.order = 1
mat_1.num_delayed_groups = 2
mat_1.set_beta(beta)
mat_1.set_nu_fission(np.multiply(nu, fiss))
mat_1.set_absorption(absorption)
mat_1.set_scatter_matrix(scatter)
mat_1.set_total(total)
mat_1.set_chi(chi)
mg_cross_sections_file.add_xsdata(mat_1)
# Make a version that uses prompt and delayed version of nufiss and chi
mat_2 = openmc.XSdata('mat_2', groups)
mat_2.order = 1
mat_2.num_delayed_groups = 2
mat_2.set_prompt_nu_fission(one_m_beta * np.multiply(nu, fiss))
delay_nu_fiss = np.zeros((n_dg, groups.num_groups))
for dg in range(n_dg):
for g in range(groups.num_groups):
delay_nu_fiss[dg, g] = beta[dg] * nu[g] * fiss[g]
mat_2.set_delayed_nu_fission(delay_nu_fiss)
mat_2.set_absorption(absorption)
mat_2.set_scatter_matrix(scatter)
mat_2.set_total(total)
mat_2.set_chi_prompt(chi)
mat_2.set_chi_delayed(np.stack([chi] * n_dg))
mg_cross_sections_file.add_xsdata(mat_2)
# Make a version that uses a nu-fission matrix with a beta
mat_3 = openmc.XSdata('mat_3', groups)
mat_3.order = 1
mat_3.num_delayed_groups = 2
mat_3.set_beta(beta)
mat_3.set_nu_fission(np.outer(np.multiply(nu, fiss), chi))
mat_3.set_absorption(absorption)
mat_3.set_scatter_matrix(scatter)
mat_3.set_total(total)
mg_cross_sections_file.add_xsdata(mat_3)
# Make a version that uses prompt and delayed version of the nufiss matrix
mat_4 = openmc.XSdata('mat_4', groups)
mat_4.order = 1
mat_4.num_delayed_groups = 2
mat_4.set_prompt_nu_fission(one_m_beta *
np.outer(np.multiply(nu, fiss), chi))
delay_nu_fiss = np.zeros((n_dg, groups.num_groups, groups.num_groups))
for dg in range(n_dg):
for g in range(groups.num_groups):
for go in range(groups.num_groups):
delay_nu_fiss[dg, g, go] = beta[dg] * nu[g] * fiss[g] * chi[go]
mat_4.set_delayed_nu_fission(delay_nu_fiss)
mat_4.set_absorption(absorption)
mat_4.set_scatter_matrix(scatter)
mat_4.set_total(total)
mg_cross_sections_file.add_xsdata(mat_4)
# Make the base data that uses chi & nu-fiss vectors with a group-wise beta
mat_5 = openmc.XSdata('mat_5', groups)
mat_5.order = 1
mat_5.num_delayed_groups = 2
mat_5.set_beta(np.stack([beta] * groups.num_groups))
mat_5.set_nu_fission(np.multiply(nu, fiss))
mat_5.set_absorption(absorption)
mat_5.set_scatter_matrix(scatter)
mat_5.set_total(total)
mat_5.set_chi(chi)
mg_cross_sections_file.add_xsdata(mat_5)
# Make a version that uses a nu-fission matrix with a group-wise beta
mat_6 = openmc.XSdata('mat_6', groups)
mat_6.order = 1
mat_6.num_delayed_groups = 2
mat_6.set_beta(np.stack([beta] * groups.num_groups))
mat_6.set_nu_fission(np.outer(np.multiply(nu, fiss), chi))
mat_6.set_absorption(absorption)
mat_6.set_scatter_matrix(scatter)
mat_6.set_total(total)
mg_cross_sections_file.add_xsdata(mat_6)
# Write the file
mg_cross_sections_file.export_to_hdf5('2g.h5')
def create_mg_library(self, xs_type='macro', xsdata_names=None,
xs_ids=None, tabular_legendre=None,
tabular_points=33):
"""Creates an openmc.MGXSLibrary object to contain the MGXS data for the
Multi-Group mode of OpenMC.
Parameters
----------
xs_type: {'macro', 'micro'}
Provide the macro or micro cross section in units of cm^-1 or
barns. Defaults to 'macro'. If the Library object is not tallied by
nuclide this will be set to 'macro' regardless.
xsdata_names : Iterable of str
List of names to apply to the "xsdata" entries in the
resultant mgxs data file. Defaults to 'set1', 'set2', ...
xs_ids : str or Iterable of str
Cross section set identifier (i.e., '71c') for all
data sets (if only str) or for each individual one
(if iterable of str). Defaults to '1m'.
tabular_legendre : None or bool
Flag to denote whether or not the Legendre expansion of the
scattering angular distribution is to be converted to a tabular
representation by OpenMC. A value of `True` means that it is to be
converted while a value of `False` means that it will not be.
Defaults to `None` which leaves the default behavior of OpenMC in
place (the distribution is converted to a tabular representation).
tabular_points : int
This parameter is not used unless the ``tabular_legendre``
parameter is set to `True`. In this case, this parameter sets the
number of equally-spaced points in the domain of [-1,1] to be used
in building the tabular distribution. Default is `33`.
Returns
-------
mgxs_file : openmc.MGXSLibrary
Multi-Group Cross Section File that is ready to be printed to the
file of choice by the user.
Raises
------
ValueError
When the Library object is initialized with insufficient types of
cross sections for the Library.
See also
--------
Library.dump_to_file()
Library.create_mg_mode()
"""
# Check to ensure the Library contains the correct
# multi-group cross section types
self.check_library_for_openmc_mgxs()
cv.check_value('xs_type', xs_type, ['macro', 'micro'])
if xsdata_names is not None:
cv.check_iterable_type('xsdata_names', xsdata_names, basestring)
if xs_ids is not None:
if isinstance(xs_ids, basestring):
# If we only have a string lets convert it now to a list
# of strings.
xs_ids = [xs_ids for i in range(len(self.domains))]
else:
cv.check_iterable_type('xs_ids', xs_ids, basestring)
else:
xs_ids = ['1m' for i in range(len(self.domains))]
# If gathering material-specific data, set the xs_type to macro
if not self.by_nuclide:
xs_type = 'macro'
# Initialize file
mgxs_file = openmc.MGXSLibrary(self.energy_groups)
# Create the xsdata object and add it to the mgxs_file
for i, domain in enumerate(self.domains):
if self.by_nuclide:
nuclides = list(domain.get_all_nuclides().keys())
else:
nuclides = ['total']
for nuclide in nuclides:
# Build & add metadata to XSdata object
if xsdata_names is None:
xsdata_name = 'set' + str(i + 1)
else:
xsdata_name = xsdata_names[i]
if nuclide is not 'total':
xsdata_name += '_' + nuclide
xsdata = self.get_xsdata(domain, xsdata_name, nuclide=nuclide,
xs_type=xs_type, xs_id=xs_ids[i],
tabular_legendre=tabular_legendre,
tabular_points=tabular_points)
mgxs_file.add_xsdata(xsdata)
return mgxs_file
def create_mg_mode(self, xsdata_names=None, xs_ids=None,
tabular_legendre=None, tabular_points=33):
"""Creates an openmc.MGXSLibrary object to contain the MGXS data for the
Multi-Group mode of OpenMC as well as the associated openmc.Materials
and openmc.Geometry objects. The created Geometry is the same as that
used to generate the MGXS data, with the only differences being
modifications to point to newly-created Materials which point to the
multi-group data. This method only creates a macroscopic
MGXS Library even if nuclidic tallies are specified in the Library.
Parameters
----------
xsdata_names : Iterable of str
List of names to apply to the "xsdata" entries in the
resultant mgxs data file. Defaults to 'set1', 'set2', ...
xs_ids : str or Iterable of str
Cross section set identifier (i.e., '71c') for all
data sets (if only str) or for each individual one
(if iterable of str). Defaults to '1m'.
tabular_legendre : None or bool
Flag to denote whether or not the Legendre expansion of the
scattering angular distribution is to be converted to a tabular
representation by OpenMC. A value of `True` means that it is to be
converted while a value of `False` means that it will not be.
Defaults to `None` which leaves the default behavior of OpenMC in
place (the distribution is converted to a tabular representation).
tabular_points : int
This parameter is not used unless the ``tabular_legendre``
parameter is set to `True`. In this case, this parameter sets the
number of equally-spaced points in the domain of [-1,1] to be used
in building the tabular distribution. Default is `33`.
Returns
-------
mgxs_file : openmc.MGXSLibrary
Multi-Group Cross Section File that is ready to be printed to the
file of choice by the user.
materials : openmc.Materials
Materials file ready to be printed with all the macroscopic data
present within this Library.
geometry : openmc.Geometry
Materials file ready to be printed with all the macroscopic data
present within this Library.
Raises
------
ValueError
When the Library object is initialized with insufficient types of
cross sections for the Library.
See also
--------
Library.create_mg_library()
Library.dump_to_file()
"""
# Check to ensure the Library contains the correct
# multi-group cross section types
self.check_library_for_openmc_mgxs()
if xsdata_names is not None:
cv.check_iterable_type('xsdata_names', xsdata_names, basestring)
if xs_ids is not None:
if isinstance(xs_ids, basestring):
# If we only have a string lets convert it now to a list
# of strings.
xs_ids = [xs_ids for i in range(len(self.domains))]
else:
cv.check_iterable_type('xs_ids', xs_ids, basestring)
else:
xs_ids = ['1m' for i in range(len(self.domains))]
xs_type = 'macro'
# Initialize MGXS File
mgxs_file = openmc.MGXSLibrary(self.energy_groups)
# Create a copy of the Geometry to differentiate for these Macroscopics
geometry = copy.deepcopy(self.openmc_geometry)
materials = openmc.Materials()
# Get all Cells from the Geometry for differentiation
all_cells = geometry.get_all_material_cells()
# Create the xsdata object and add it to the mgxs_file
for i, domain in enumerate(self.domains):
# Build & add metadata to XSdata object
if xsdata_names is None:
xsdata_name = 'set' + str(i + 1)
else:
xsdata_name = xsdata_names[i]
# Create XSdata and Macroscopic for this domain
xsdata = self.get_xsdata(domain, xsdata_name, nuclide='total',
xs_type=xs_type, xs_id=xs_ids[i],
tabular_legendre=tabular_legendre,
tabular_points=tabular_points)
mgxs_file.add_xsdata(xsdata)
macroscopic = openmc.Macroscopic(name=xsdata_name, xs=xs_ids[i])
# Create Material and add to collection
material = openmc.Material(name=xsdata_name + '.' + xs_ids[i])
material.add_macroscopic(macroscopic)
materials.append(material)
# Differentiate Geometry with new Material
if self.domain_type == 'material':
# Fill all appropriate Cells with new Material
for cell in all_cells:
if cell.fill.id == domain.id:
cell.fill = material
elif self.domain_type == 'cell':
for cell in all_cells:
if cell.id == domain.id:
cell.fill = material
return mgxs_file, materials, geometry
