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Combined the elemental and material calculate_xs routines
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Adam Nelson
parent
9afb0c8d68
commit
24798a0ecd
1 changed files with 63 additions and 115 deletions
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@ -228,11 +228,11 @@ def calculate_xs(this, types, temperature=294., sab_name=None,
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for line in range(len(types)):
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data[line, :] = xs[line](energy_grid)
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elif isinstance(this, openmc.Element):
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energy_grid, data = _calculate_xs_element(this, types, temperature,
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cross_sections, sab_name,
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enrichment)
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energy_grid, data = _calculate_xs_elem_mat(this, types, temperature,
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cross_sections, sab_name,
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enrichment)
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elif isinstance(this, openmc.Material):
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energy_grid, data = _calculate_xs_material(this, types, temperature,
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energy_grid, data = _calculate_xs_elem_mat(this, types, temperature,
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cross_sections)
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else:
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raise TypeError("Invalid type")
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@ -240,90 +240,6 @@ def calculate_xs(this, types, temperature=294., sab_name=None,
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return energy_grid, data
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def _calculate_xs_element(this, types, temperature=294., sab_name=None,
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cross_sections=None, enrichment=None):
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"""Calculates continuous-energy cross sections of a requested type
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Parameters
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----------
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this : openmc.Element
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Element object to source data from
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types : Iterable of values of PLOT_TYPES
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The type of cross sections to calculate
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temperature : float, optional
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Temperature in Kelvin to plot. If not specified, a default
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temperature of 294K will be plotted. Note that the nearest
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temperature in the library for each nuclide will be used as opposed
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to using any interpolation.
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sab_name : str, optional
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Name of S(a,b) library to apply to MT=2 data when applicable.
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cross_sections : str, optional
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Location of cross_sections.xml file. Default is None.
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enrichment : float, optional
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Enrichment for U235 in weight percent. For example, input 4.95 for
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4.95 weight percent enriched U. Default is None
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(natural composition).
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Returns
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-------
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energy_grid : numpy.ndarray
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Energies at which cross sections are calculated, in units of eV
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data : numpy.ndarray
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Macroscopic cross sections calculated at the energy grid described
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by energy_grid
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"""
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# Load the library
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library = openmc.data.DataLibrary.from_xml(cross_sections)
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# Expand elements in to nuclides with atomic densities
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nuclides = this.expand(1., 'ao', enrichment=enrichment,
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cross_sections=cross_sections)
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# For ease of processing split out nuc and nuc_density
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nuc_fractions = [nuclide[1] for nuclide in nuclides]
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# Identify the nuclides which have S(a,b) data
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sabs = {}
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for nuclide in nuclides:
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sabs[nuclide[0].name] = None
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if sab_name:
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sab = openmc.data.ThermalScattering.from_hdf5(sab_name)
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for nuc in sab.nuclides:
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sabs[nuc] = library.get_by_material(sab_name)['path']
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# Now we can create the data sets to be plotted
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xs = []
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E = []
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for nuclide in nuclides:
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sab_tab = sabs[nuclide[0].name]
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temp_E, temp_xs = calculate_xs(nuclide[0], types, temperature, sab_tab,
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cross_sections)
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E.append(temp_E)
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# Since the energy grids are different, store the cross sections as
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# a tabulated function so they can be calculated on any grid needed.
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xs.append([openmc.data.Tabulated1D(temp_E, temp_xs[line])
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for line in range(len(types))])
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# Condense the data for every nuclide
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# First create a union energy grid
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energy_grid = E[0]
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for grid in E[1:]:
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energy_grid = np.union1d(energy_grid, grid)
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# Now we can combine all the nuclidic data
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data = np.zeros((len(types), len(energy_grid)))
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for line in range(len(types)):
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if types[line] == 'unity':
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data[line, :] = 1.
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else:
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for n in range(len(nuclides)):
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data[line, :] += nuc_fractions[n] * xs[n][line](energy_grid)
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return energy_grid, data
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def _calculate_xs_nuclide(this, types, temperature=294., sab_name=None,
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cross_sections=None):
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"""Calculates continuous-energy cross sections of a requested type
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@ -513,14 +429,14 @@ def _calculate_xs_nuclide(this, types, temperature=294., sab_name=None,
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return energy_grid, xs
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def _calculate_xs_material(this, types, temperature=294., cross_sections=None):
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"""Calculates continuous-energy macroscopic cross sections of a
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requested type
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def _calculate_xs_elem_mat(this, types, temperature=294., cross_sections=None,
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sab_name=None, enrichment=None):
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"""Calculates continuous-energy cross sections of a requested type
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Parameters
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----------
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this : openmc.Material
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Material object to source data from
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this : {openmc.Material, openmc.Element}
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Object to source data from
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types : Iterable of values of PLOT_TYPES
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The type of cross sections to calculate
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temperature : float, optional
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@ -530,53 +446,83 @@ def _calculate_xs_material(this, types, temperature=294., cross_sections=None):
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to using any interpolation.
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cross_sections : str, optional
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Location of cross_sections.xml file. Default is None.
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sab_name : str, optional
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Name of S(a,b) library to apply to MT=2 data when applicable.
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enrichment : float, optional
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Enrichment for U235 in weight percent. For example, input 4.95 for
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4.95 weight percent enriched U. Default is None
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(natural composition).
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Returns
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-------
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energy_grid : numpy.ndarray
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Energies at which cross sections are calculated, in units of eV
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data : numpy.ndarray
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Macroscopic cross sections calculated at the energy grid described
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by energy_grid
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Cross sections calculated at the energy grid described by energy_grid
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"""
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if this.temperature is not None:
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T = this.temperature
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if isinstance(this, openmc.Material):
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if this.temperature is not None:
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T = this.temperature
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else:
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T = temperature
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else:
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T = temperature
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# Load the library
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library = openmc.data.DataLibrary.from_xml(cross_sections)
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# Expand elements in to nuclides with atomic densities
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nuclides = this.get_nuclide_atom_densities()
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if isinstance(this, openmc.Material):
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# Expand elements in to nuclides with atomic densities
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nuclides = this.get_nuclide_atom_densities()
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# For ease of processing split out nuc and nuc_density
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nuc_densities = [nuclide[1][1] for nuclide in nuclides.items()]
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# For ease of processing split out the nuclide and its fraction
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nuc_fractions = {nuclide[1][0].name: nuclide[1][1]
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for nuclide in nuclides.items()}
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# Create a dict of [nuclide name] = nuclide object to carry forward
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nuclides = {nuclide[1][0].name: nuclide[1][0]
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for nuclide in nuclides.items()}
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else:
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# Expand elements in to nuclides with atomic densities
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nuclides = this.expand(1., 'ao', enrichment=enrichment,
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cross_sections=cross_sections)
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# For ease of processing split out the nuclide and its fraction
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nuc_fractions = {nuclide[0].name: nuclide[1] for nuclide in nuclides}
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# Create a dict of [nuclide name] = nuclide object to carry forward
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nuclides = {nuclide[0].name: nuclide[0] for nuclide in nuclides}
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# Identify the nuclides which have S(a,b) data
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sabs = {}
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for nuclide in nuclides.items():
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sabs[nuclide[0].name] = None
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for sab_name in this._sab:
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sab = openmc.data.ThermalScattering.from_hdf5(
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library.get_by_material(sab_name)['path'])
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for nuc in sab.nuclides:
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sabs[nuc] = library.get_by_material(sab_name)['path']
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sabs[nuclide[0]] = None
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if isinstance(this, openmc.Material):
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for sab_name in this._sab:
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sab = openmc.data.ThermalScattering.from_hdf5(
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library.get_by_material(sab_name)['path'])
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for nuc in sab.nuclides:
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sabs[nuc] = library.get_by_material(sab_name)['path']
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else:
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if sab_name:
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sab = openmc.data.ThermalScattering.from_hdf5(sab_name)
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for nuc in sab.nuclides:
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sabs[nuc] = library.get_by_material(sab_name)['path']
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# Now we can create the data sets to be plotted
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xs = []
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xs = {}
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E = []
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# for nuclide in nuclides:
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for nuclide in nuclides.items():
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sab_tab = sabs[nuclide[0].name]
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temp_E, temp_xs = calculate_xs(nuclide[0], types, T, sab_tab,
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cross_sections)
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name = nuclide[0]
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nuc = nuclide[1]
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sab_tab = sabs[name]
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temp_E, temp_xs = calculate_xs(nuc, types, T, sab_tab, cross_sections)
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E.append(temp_E)
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# Since the energy grids are different, store the cross sections as
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# a tabulated function so they can be calculated on any grid needed.
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xs.append([openmc.data.Tabulated1D(temp_E, temp_xs[line])
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for line in range(len(types))])
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xs[name] = [openmc.data.Tabulated1D(temp_E, temp_xs[line])
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for line in range(len(types))]
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# Condense the data for every nuclide
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# First create a union energy grid
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@ -590,7 +536,9 @@ def _calculate_xs_material(this, types, temperature=294., cross_sections=None):
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if types[line] == 'unity':
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data[line, :] = 1.
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else:
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for n in range(len(nuclides)):
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data[line, :] += nuc_densities[n] * xs[n][line](energy_grid)
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for nuclide in nuclides.items():
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name = nuclide[0]
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data[line, :] += (nuc_fractions[name] *
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xs[name][line](energy_grid))
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return energy_grid, data
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