"""OpenMC transport operator
This module implements functions shared by both OpenMC transport-coupled and
transport-independent transport operators.
"""
from abc import abstractmethod
from collections import OrderedDict
import numpy as np
import openmc
from openmc.exceptions import DataError
from openmc.mpi import comm
from .abc import TransportOperator, OperatorResult
from .atom_number import AtomNumber
from .reaction_rates import ReactionRates
__all__ = ["OpenMCOperator", "OperatorResult"]
def _distribute(items):
"""Distribute items across MPI communicator
Parameters
----------
items : list
List of items of distribute
Returns
-------
list
Items assigned to process that called
"""
min_size, extra = divmod(len(items), comm.size)
j = 0
for i in range(comm.size):
chunk_size = min_size + int(i < extra)
if comm.rank == i:
return items[j:j + chunk_size]
j += chunk_size
[docs]class OpenMCOperator(TransportOperator):
"""Abstract class holding OpenMC-specific functions for running
depletion calculations.
Specific classes for running transport-coupled or transport-independent
depletion calculations are implemented as subclasses of OpenMCOperator.
Parameters
----------
materials : openmc.Materials
List of all materials in the model
cross_sections : str or pandas.DataFrame
Path to continuous energy cross section library, or object containing
one-group cross-sections.
chain_file : str, optional
Path to the depletion chain XML file. Defaults to
openmc.config['chain_file'].
prev_results : Results, optional
Results from a previous depletion calculation. If this argument is
specified, the depletion calculation will start from the latest state
in the previous results.
diff_burnable_mats : bool, optional
Whether to differentiate burnable materials with multiple instances.
Volumes are divided equally from the original material volume.
fission_q : dict, optional
Dictionary of nuclides and their fission Q values [eV].
dilute_initial : float, optional
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.
helper_kwargs : dict
Keyword arguments for helper classes
reduce_chain : bool, optional
If True, use :meth:`openmc.deplete.Chain.reduce()` to reduce the
depletion chain up to ``reduce_chain_level``.
reduce_chain_level : int, optional
Depth of the search when reducing the depletion chain. Only used
if ``reduce_chain`` evaluates to true. The default value of
``None`` implies no limit on the depth.
Attributes
----------
materials : openmc.Materials
All materials present in the model
cross_sections : str or MicroXS
Path to continuous energy cross section library, or object
containing one-group cross-sections.
dilute_initial : float
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.
output_dir : pathlib.Path
Path to output directory to save results.
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.
number : openmc.deplete.AtomNumber
Total number of atoms in simulation.
nuclides_with_data : set of str
A set listing all unique nuclides available from cross_sections.xml.
chain : openmc.deplete.Chain
The depletion chain information necessary to form matrices and tallies.
reaction_rates : openmc.deplete.ReactionRates
Reaction rates from the last operator step.
burnable_mats : list of str
All burnable material IDs
heavy_metal : float
Initial heavy metal inventory [g]
local_mats : list of str
All burnable material IDs being managed by a single process
prev_res : Results or None
Results from a previous depletion calculation. ``None`` if no
results are to be used.
"""
def __init__(
self,
materials=None,
cross_sections=None,
chain_file=None,
prev_results=None,
diff_burnable_mats=False,
fission_q=None,
dilute_initial=0.0,
helper_kwargs=None,
reduce_chain=False,
reduce_chain_level=None):
# If chain file was not specified, try to get it from global config
if chain_file is None:
chain_file = openmc.config.get('chain_file')
if chain_file is None:
raise DataError(
"No depletion chain specified and could not find depletion "
"chain in openmc.config['chain_file']"
)
super().__init__(chain_file, fission_q, dilute_initial, prev_results)
self.round_number = False
self.materials = materials
self.cross_sections = cross_sections
# Reduce the chain to only those nuclides present
if reduce_chain:
init_nuclides = set()
for material in self.materials:
if not material.depletable:
continue
for name, _dens_percent, _dens_type in material.nuclides:
init_nuclides.add(name)
self.chain = self.chain.reduce(init_nuclides, reduce_chain_level)
if diff_burnable_mats:
self._differentiate_burnable_mats()
# Determine which nuclides have cross section data
# This nuclides variables contains every nuclides
# for which there is an entry in the micro_xs parameter
openmc.reset_auto_ids()
self.burnable_mats, volumes, all_nuclides = self._get_burnable_mats()
self.local_mats = _distribute(self.burnable_mats)
self._mat_index_map = {
lm: self.burnable_mats.index(lm) for lm in self.local_mats}
if self.prev_res is not None:
self._load_previous_results()
self.nuclides_with_data = self._get_nuclides_with_data(
self.cross_sections)
# Select nuclides with data that are also in the chain
self._burnable_nucs = [nuc.name for nuc in self.chain.nuclides
if nuc.name in self.nuclides_with_data]
# Extract number densities from the geometry / previous depletion run
self._extract_number(self.local_mats,
volumes,
all_nuclides,
self.prev_res)
# Create reaction rates array
self.reaction_rates = ReactionRates(
self.local_mats, self._burnable_nucs, self.chain.reactions)
self._get_helper_classes(helper_kwargs)
def _differentiate_burnable_mats(self):
"""Assign distribmats for each burnable material"""
pass
def _get_burnable_mats(self):
"""Determine depletable materials, volumes, and nuclides
Returns
-------
burnable_mats : list of str
List of burnable material IDs
volume : OrderedDict of str to float
Volume of each material in [cm^3]
nuclides : list of str
Nuclides in order of how they'll appear in the simulation.
"""
burnable_mats = set()
model_nuclides = set()
volume = OrderedDict()
self.heavy_metal = 0.0
# Iterate once through the geometry to get dictionaries
for mat in self.materials:
for nuclide in mat.get_nuclides():
model_nuclides.add(nuclide)
if mat.depletable:
burnable_mats.add(str(mat.id))
if mat.volume is None:
raise RuntimeError("Volume not specified for depletable "
"material with ID={}.".format(mat.id))
volume[str(mat.id)] = mat.volume
self.heavy_metal += mat.fissionable_mass
# Make sure there are burnable materials
if not burnable_mats:
raise RuntimeError(
"No depletable materials were found in the model.")
# Sort the sets
burnable_mats = sorted(burnable_mats, key=int)
model_nuclides = sorted(model_nuclides)
# Construct a global nuclide dictionary, burned first
nuclides = list(self.chain.nuclide_dict)
for nuc in model_nuclides:
if nuc not in nuclides:
nuclides.append(nuc)
return burnable_mats, volume, nuclides
def _load_previous_results(self):
"""Load results from a previous depletion simulation"""
pass
@abstractmethod
def _get_nuclides_with_data(self, cross_sections):
"""Find nuclides with cross section data
Parameters
----------
cross_sections : str or pandas.DataFrame
Path to continuous energy cross section library, or object
containing one-group cross-sections.
Returns
-------
nuclides : set of str
Set of nuclide names that have cross secton data
"""
def _extract_number(self, local_mats, volume, all_nuclides, prev_res=None):
"""Construct AtomNumber using geometry
Parameters
----------
local_mats : list of str
Material IDs to be managed by this process
volume : OrderedDict of str to float
Volumes for the above materials in [cm^3]
all_nuclides : list of str
Nuclides to be used in the simulation.
prev_res : Results, optional
Results from a previous depletion calculation
"""
self.number = AtomNumber(local_mats, all_nuclides, volume, len(self.chain))
if self.dilute_initial != 0.0:
for nuc in self._burnable_nucs:
self.number.set_atom_density(
np.s_[:], nuc, self.dilute_initial)
# Now extract and store the number densities
# From the geometry if no previous depletion results
if prev_res is None:
for mat in self.materials:
if str(mat.id) in local_mats:
self._set_number_from_mat(mat)
# Else from previous depletion results
else:
for mat in self.materials:
if str(mat.id) in local_mats:
self._set_number_from_results(mat, prev_res)
def _set_number_from_mat(self, mat):
"""Extracts material and number densities from openmc.Material
Parameters
----------
mat : openmc.Material
The material to read from
"""
mat_id = str(mat.id)
for nuclide, atom_per_bcm in mat.get_nuclide_atom_densities().items():
atom_per_cc = atom_per_bcm * 1.0e24
self.number.set_atom_density(mat_id, nuclide, atom_per_cc)
def _set_number_from_results(self, mat, prev_res):
"""Extracts material nuclides and number densities.
If the nuclide concentration's evolution is tracked, the densities come
from depletion results. Else, densities are extracted from the geometry
in the summary.
Parameters
----------
mat : openmc.Material
The material to read from
prev_res : Results
Results from a previous depletion calculation
"""
mat_id = str(mat.id)
# Get nuclide lists from geometry and depletion results
depl_nuc = prev_res[-1].index_nuc
geom_nuc_densities = mat.get_nuclide_atom_densities()
# Merge lists of nuclides, with the same order for every calculation
geom_nuc_densities.update(depl_nuc)
for nuclide, atom_per_bcm in geom_nuc_densities.items():
if nuclide in depl_nuc:
concentration = prev_res.get_atoms(mat_id, nuclide)[1][-1]
volume = prev_res[-1].volume[mat_id]
atom_per_cc = concentration / volume
else:
atom_per_cc = atom_per_bcm * 1.0e24
self.number.set_atom_density(mat_id, nuclide, atom_per_cc)
@abstractmethod
def _get_helper_classes(self, helper_kwargs):
"""Create the ``_rate_helper``, ``_normalization_helper``, and
``_yield_helper`` objects.
Parameters
----------
helper_kwargs : dict
Keyword arguments for helper classes
"""
[docs] def initial_condition(self, materials):
"""Performs final setup and returns initial condition.
Parameters
----------
materials : list of str
list of material IDs
Returns
-------
list of numpy.ndarray
Total density for initial conditions.
"""
self._rate_helper.generate_tallies(materials, self.chain.reactions)
self._normalization_helper.prepare(
self.chain.nuclides, self.reaction_rates.index_nuc)
# Tell fission yield helper what materials this process is
# responsible for
self._yield_helper.generate_tallies(
materials, tuple(sorted(self._mat_index_map.values())))
# Return number density vector
return list(self.number.get_mat_slice(np.s_[:]))
def _update_materials_and_nuclides(self, vec):
"""Update the number density, material compositions, and nuclide
lists in helper objects
Parameters
----------
vec : list of numpy.ndarray
Total atoms.
"""
# Update the number densities regardless of the source rate
self.number.set_density(vec)
self._update_materials()
# Prevent OpenMC from complaining about re-creating tallies
openmc.reset_auto_ids()
# Update tally nuclides data in preparation for transport solve
nuclides = self._get_reaction_nuclides()
self._rate_helper.nuclides = nuclides
self._normalization_helper.nuclides = nuclides
self._yield_helper.update_tally_nuclides(nuclides)
@abstractmethod
def _update_materials(self):
"""Updates material compositions in OpenMC on all processes."""
[docs] def write_bos_data(self, step):
"""Document beginning of step data for a given step
Called at the beginning of a depletion step and at
the final point in the simulation.
Parameters
----------
step : int
Current depletion step including restarts
"""
# Since we aren't running a transport simulation, we simply pass
pass
def _get_reaction_nuclides(self):
"""Determine nuclides that should be tallied for reaction rates.
This method returns a list of all nuclides that have cross section data
and are listed in the depletion chain. Technically, we should count
nuclides that may not appear in the depletion chain because we still
need to get the fission reaction rate for these nuclides in order to
normalize power, but that is left as a future exercise.
Returns
-------
list of str
Nuclides with reaction rates
"""
nuc_set = set()
# Create the set of all nuclides in the decay chain in materials marked
# for burning in which the number density is greater than zero.
for nuc in self.number.nuclides:
if nuc in self.nuclides_with_data:
if np.sum(self.number[:, nuc]) > 0.0:
nuc_set.add(nuc)
# Communicate which nuclides have nonzeros to rank 0
if comm.rank == 0:
for i in range(1, comm.size):
nuc_newset = comm.recv(source=i, tag=i)
nuc_set |= nuc_newset
else:
comm.send(nuc_set, dest=0, tag=comm.rank)
if comm.rank == 0:
# Sort nuclides in the same order as self.number
nuc_list = [nuc for nuc in self.number.nuclides
if nuc in nuc_set]
else:
nuc_list = None
# Store list of nuclides on each process
nuc_list = comm.bcast(nuc_list)
return [nuc for nuc in nuc_list if nuc in self.chain]
def _calculate_reaction_rates(self, source_rate):
"""Unpack tallies from OpenMC and return an operator result
This method uses OpenMC's C API bindings to determine the k-effective
value and reaction rates from the simulation. The reaction rates are
normalized by a helper class depending on the method being used.
Parameters
----------
source_rate : float
Power in [W] or source rate in [neutron/sec]
Returns
-------
rates : openmc.deplete.ReactionRates
Reaction rates for nuclides
"""
rates = self.reaction_rates
rates.fill(0.0)
# Extract reaction nuclides
rxn_nuclides = self._rate_helper.nuclides
# Form fast map
nuc_ind = [rates.index_nuc[nuc] for nuc in rxn_nuclides]
react_ind = [rates.index_rx[react] for react in self.chain.reactions]
# Keep track of energy produced from all reactions in eV per source
# particle
self._normalization_helper.reset()
self._yield_helper.unpack()
# Store fission yield dictionaries
fission_yields = []
# Create arrays to store fission Q values, reaction rates, and nuclide
# numbers, zeroed out in material iteration
number = np.empty(rates.n_nuc)
fission_ind = rates.index_rx.get("fission")
# Reset the cached material reaction rates tallies
self._rate_helper.reset_tally_means()
# Extract results
for i, mat in enumerate(self.local_mats):
# Get tally index
mat_index = self._mat_index_map[mat]
# Zero out reaction rates and nuclide numbers
number.fill(0.0)
# Get new number densities
for nuc, i_nuc_results in zip(rxn_nuclides, nuc_ind):
number[i_nuc_results] = self.number[mat, nuc]
tally_rates = self._rate_helper.get_material_rates(
mat_index, nuc_ind, react_ind)
# Compute fission yields for this material
fission_yields.append(self._yield_helper.weighted_yields(i))
# Accumulate energy from fission
if fission_ind is not None:
self._normalization_helper.update(
tally_rates[:, fission_ind])
# Divide by total number and store
rates[i] = self._rate_helper.divide_by_adens(number)
# Scale reaction rates to obtain units of reactions/sec
rates *= self._normalization_helper.factor(source_rate)
# Store new fission yields on the chain
self.chain.fission_yields = fission_yields
return rates
[docs] def get_results_info(self):
"""Returns volume list, material lists, and nuc lists.
Returns
-------
volume : dict of str float
Volumes corresponding to materials in full_burn_dict
nuc_list : list of str
A list of all nuclide names. Used for sorting the simulation.
burn_list : list of int
A list of all material IDs to be burned. Used for sorting the simulation.
full_burn_list : list
List of all burnable material IDs
"""
nuc_list = self.number.burnable_nuclides
burn_list = self.local_mats
volume = {}
for i, mat in enumerate(burn_list):
volume[mat] = self.number.volume[i]
# Combine volume dictionaries across processes
volume_list = comm.allgather(volume)
volume = {k: v for d in volume_list for k, v in d.items()}
return volume, nuc_list, burn_list, self.burnable_mats