def replace_missing_fpy(actinide, fpy_data, decay_data):
"""Replace missing fission product yields
Parameters
----------
actinide : str
Name of actinide missing FPY data
fpy_data : dict
Dictionary of FPY data
decay_data : dict
Dictionary of decay data
Returns
-------
str
Actinide that can be used as replacement for FPY purposes
"""
# Check if metastable state has data (e.g., Am242m)
Z, A, m = zam(actinide)
if m == 0:
metastable = gnd_name(Z, A, 1)
if metastable in fpy_data:
return metastable
# Try increasing Z, holding N constant
isotone = actinide
while isotone in decay_data:
Z += 1
A += 1
isotone = gnd_name(Z, A, 0)
if isotone in fpy_data:
return isotone
# Try decreasing Z, holding N constant
isotone = actinide
while isotone in decay_data:
Z -= 1
A -= 1
isotone = gnd_name(Z, A, 0)
if isotone in fpy_data:
return isotone
# If all else fails, use U235 yields
return 'U235'
def set_branch_ratios(self,
branch_ratios,
reaction="(n,gamma)",
strict=True,
tolerance=1e-5):
"""Set the branching ratios for a given reactions
Parameters
----------
branch_ratios : dict of {str: {str: float}}
Capture branching ratios to be inserted.
First layer keys are names of parent nuclides, e.g.
``"Am241"``. The branching ratios for these
parents will be modified. Corresponding values are
dictionaries of ``{target: branching_ratio}``
reaction : str, optional
Reaction name like ``"(n,gamma)"`` [default], or
``"(n, alpha)"``.
strict : bool, optional
Error control. If this evalutes to ``True``, then errors will
be raised if inconsistencies are found. Otherwise, warnings
will be raised for most issues.
tolerance : float, optional
Tolerance on the sum of all branching ratios for a
single parent. Will be checked with::
1 - tol < sum_br < 1 + tol
Raises
------
IndexError
If no isotopes were found on the chain that have the requested
reaction
KeyError
If ``strict`` evaluates to ``False`` and a parent isotope in
``branch_ratios`` does not exist on the chain
AttributeError
If ``strict`` evaluates to ``False`` and a parent isotope in
``branch_ratios`` does not have the requested reaction
ValueError
If ``strict`` evalutes to ``False`` and the sum of one parents
branch ratios is outside 1 +/- ``tolerance``
See Also
--------
:meth:`get_branch_ratios`
"""
# Store some useful information through the validation stage
sums = {}
rxn_ix_map = {}
grounds = {}
tolerance = abs(tolerance)
missing_parents = set()
missing_products = {}
missing_reaction = set()
bad_sums = {}
# Secondary products, like alpha particles, should not be modified
secondary = _SECONDARY_PARTICLES.get(reaction, [])
# Check for validity before manipulation
for parent, sub in branch_ratios.items():
if parent not in self:
if strict:
raise KeyError(parent)
missing_parents.add(parent)
continue
# Make sure all products are present in the chain
prod_flag = False
for product in sub:
if product not in self:
if strict:
raise KeyError(product)
missing_products[parent] = product
prod_flag = True
break
if prod_flag:
continue
# Make sure this nuclide has the reaction
indexes = []
for ix, rx in enumerate(self[parent].reactions):
if rx.type == reaction and rx.target not in secondary:
indexes.append(ix)
if "_m" not in rx.target:
grounds[parent] = rx.target
if len(indexes) == 0:
if strict:
raise AttributeError(
"Nuclide {} does not have {} reactions".format(
parent, reaction))
missing_reaction.add(parent)
continue
this_sum = sum(sub.values())
# sum of branching ratios can be lower than 1 if no ground
# target is given, but never greater
if (this_sum >= 1 + tolerance
or (grounds[parent] in sub and this_sum <= 1 - tolerance)):
if strict:
msg = ("Sum of {} branching ratios for {} "
"({:7.3f}) outside tolerance of 1 +/- "
"{:5.3e}".format(reaction, parent, this_sum,
tolerance))
raise ValueError(msg)
bad_sums[parent] = this_sum
else:
rxn_ix_map[parent] = indexes
sums[parent] = this_sum
if len(rxn_ix_map) == 0:
raise IndexError("No {} reactions found in this {}".format(
reaction, self.__class__.__name__))
if len(missing_parents) > 0:
warn("The following nuclides were not found in {}: {}".format(
self.__class__.__name__, ", ".join(sorted(missing_parents))))
if len(missing_reaction) > 0:
warn("The following nuclides did not have {} reactions: "
"{}".format(reaction, ", ".join(sorted(missing_reaction))))
if len(missing_products) > 0:
tail = ("{} -> {}".format(k, v)
for k, v in sorted(missing_products.items()))
warn("The following products were not found in the {} and "
"parents were unmodified: \n{}".format(
self.__class__.__name__, ", ".join(tail)))
if len(bad_sums) > 0:
tail = ("{}: {:5.3f}".format(k, s)
for k, s in sorted(bad_sums.items()))
warn("The following parent nuclides were given {} branch ratios "
"with a sum outside tolerance of 1 +/- {:5.3e}:\n{}".format(
reaction, tolerance, "\n".join(tail)))
# Insert new ReactionTuples with updated branch ratios
for parent_name, rxn_index in rxn_ix_map.items():
parent = self[parent_name]
new_ratios = branch_ratios[parent_name]
rxn_index = rxn_ix_map[parent_name]
# Assume Q value is independent of target state
rxn_Q = parent.reactions[rxn_index[0]].Q
# Remove existing reactions
for ix in reversed(rxn_index):
parent.reactions.pop(ix)
all_meta = True
for tgt, br in new_ratios.items():
all_meta = all_meta and ("_m" in tgt)
parent.reactions.append(ReactionTuple(reaction, tgt, rxn_Q,
br))
if all_meta and sums[parent_name] != 1.0:
ground_br = 1.0 - sums[parent_name]
ground_tgt = grounds.get(parent_name)
if ground_tgt is None:
pz, pa, pm = zam(parent_name)
ground_tgt = gnd_name(pz, pa + 1, 0)
new_ratios[ground_tgt] = ground_br
parent.reactions.append(
ReactionTuple(reaction, ground_tgt, rxn_Q, ground_br))
from argparse import ArgumentParser
from math import pi
import matplotlib.pyplot as plt
from openmc.data import ATOMIC_SYMBOL, zam
import openmc.data
import openmc.deplete
import serpentTools
parser = ArgumentParser()
parser.add_argument('nuclide')
args = parser.parse_args()
nuc = args.nuclide
z, a, m = zam(nuc)
# Read OpenMC results ---------------------------------------------------------
# Open results file
results = openmc.deplete.ResultsList.from_hdf5("openmc/depletion_results.h5")
# Obtain K_eff as a function of time
time, keff = results.get_eigenvalue()
# Obtain concentration as a function of time
time, atoms = results.get_atoms('1', nuc)
radius = 0.39218
volume = pi * radius**2
openmc_conc = atoms * 1e-24 / volume # [atoms] [cm^2/b] / [cm^2] = atom/b
# Read Serpent results --------------------------------------------------------