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Add type checking for keff; typo fixes in flux_operator.py

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This commit is contained in:
yardasol 2022-07-07 14:31:59 -05:00
parent 1d81b553de
commit 516c117533
1 changed files with 13 additions and 4 deletions
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17
openmc/deplete/flux_operator.py
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@ -90,6 +90,9 @@ class FluxDepletionOperator(TransportOperator):
Initial atom density [atoms/cm^3] to add for nuclides that are zero
in initial condition to ensure they exist in the decay chain.
Only done for nuclides with reaction rates.
round_number : bool
Whether or not to round output to OpenMC to 8 digits.
Useful in testing, as OpenMC is incredibly sensitive to exact values.
prev_res : Results or None
Results from a previous depletion calculation. ``None`` if no
results are to be used.
@ -120,6 +123,7 @@ class FluxDepletionOperator(TransportOperator):
reduce_chain_level=None,
fission_yield_opts=None):
super().__init__(chain_file, fission_q, dilute_initial, prev_results)
self.round_number = False
self.flux_spectra = flux_spectra
self._init_nuclides = nuclides
self._volume = volume
@ -134,6 +138,10 @@ class FluxDepletionOperator(TransportOperator):
check_type('micro_xs', micro_xs, pd.DataFrame)
self._micro_xs = micro_xs
if not isinstance(keff, type(None)):
check_type('keff', keff, tuple, float)
keff = ufloat(keff)
self._keff = keff
self._all_nuclides = self._get_all_nuclides_in_simulation()
@ -210,12 +218,13 @@ class FluxDepletionOperator(TransportOperator):
number.fill(0.0)
# Get new number densities
for nuc, i_nuc_results in zip(nuclides, nuc_ind):
for nuc, i_nuc_results in zip(rxn_nuclides, nuc_ind):
number[i_nuc_results] = self.number[0, nuc]
# Calculate macroscopic cross sections and store them in rates array
for nuc in nuclides:
density = number.get_atom_density('0', nuc)
for nuc in rxn_nuclides:
density = self.number.get_atom_density('0', nuc)
for rxn in self.chain.reactions:
rates.set(
'0',
@ -236,7 +245,7 @@ class FluxDepletionOperator(TransportOperator):
# vector. Since what we want is the depletion matrix, we need to
# divide the reaction rates by the number of atoms to get the right
# units.
mask = nonzero(number)
mask = np.nonzero(number)
results = rates[0]
for col in range(results.shape[1]):
results[mask, col] /= number[mask]