"""function module.
This module contains the Operator class, which is then passed to an integrator
to run a full depletion simulation.
"""
from abc import ABC, abstractmethod
from collections import namedtuple, defaultdict
from collections.abc import Iterable, Callable
from copy import deepcopy
from inspect import signature
from numbers import Real, Integral
import os
from pathlib import Path
import sys
import time
from warnings import warn
from numpy import nonzero, empty, asarray
from uncertainties import ufloat
from openmc.data import DataLibrary
from openmc.lib import MaterialFilter, Tally
from openmc.checkvalue import check_type, check_greater_than
from . import comm
from .results import Results
from .chain import Chain
from .results_list import ResultsList
from .pool import deplete
__all__ = [
"OperatorResult", "TransportOperator", "ReactionRateHelper",
"NormalizationHelper", "FissionYieldHelper", "TalliedFissionYieldHelper",
"Integrator", "SIIntegrator", "DepSystemSolver", "add_params"]
_SECONDS_PER_MINUTE = 60
_SECONDS_PER_HOUR = 60*60
_SECONDS_PER_DAY = 24*60*60
OperatorResult = namedtuple('OperatorResult', ['k', 'rates'])
OperatorResult.__doc__ = """\
Result of applying transport operator
Parameters
----------
k : uncertainties.ufloat
Resulting eigenvalue and standard deviation
rates : openmc.deplete.ReactionRates
Resulting reaction rates
"""
try:
OperatorResult.k.__doc__ = None
OperatorResult.rates.__doc__ = None
except AttributeError:
# Can't set __doc__ on properties on Python 3.4
pass
[docs]class TransportOperator(ABC):
"""Abstract class defining a transport operator
Each depletion integrator is written to work with a generic transport
operator that takes a vector of material compositions and returns an
eigenvalue and reaction rates. This abstract class sets the requirements
for such a transport operator. Users should instantiate
:class:`openmc.deplete.Operator` rather than this class.
Parameters
----------
chain_file : str, optional
Path to the depletion chain XML file. Defaults to the file
listed under ``depletion_chain`` in
:envvar:`OPENMC_CROSS_SECTIONS` environment variable.
fission_q : dict, optional
Dictionary of nuclides and their fission Q values [eV]. If not given,
values will be pulled from the ``chain_file``.
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.
Defaults to 1.0e3.
prev_results : ResultsList, optional
Results from a previous depletion calculation.
Attributes
----------
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.
prev_res : ResultsList or None
Results from a previous depletion calculation. ``None`` if no
results are to be used.
"""
def __init__(self, chain_file=None, fission_q=None, dilute_initial=1.0e3,
prev_results=None):
self.dilute_initial = dilute_initial
self.output_dir = '.'
# Read depletion chain
if chain_file is None:
chain_file = os.environ.get("OPENMC_DEPLETE_CHAIN", None)
if chain_file is None:
data = DataLibrary.from_xml()
# search for depletion_chain path from end of list
for lib in reversed(data.libraries):
if lib['type'] == 'depletion_chain':
break
else:
raise IOError(
"No chain specified, either manually or "
"under depletion_chain in environment variable "
"OPENMC_CROSS_SECTIONS.")
chain_file = lib['path']
else:
warn("Use of OPENMC_DEPLETE_CHAIN is deprecated in favor "
"of adding depletion_chain to OPENMC_CROSS_SECTIONS",
FutureWarning)
self.chain = Chain.from_xml(chain_file, fission_q)
if prev_results is None:
self.prev_res = None
else:
check_type("previous results", prev_results, ResultsList)
self.prev_res = prev_results
@property
def dilute_initial(self):
"""Initial atom density for nuclides with zero initial concentration"""
return self._dilute_initial
@dilute_initial.setter
def dilute_initial(self, value):
check_type("dilute_initial", value, Real)
check_greater_than("dilute_initial", value, 0.0, equality=True)
self._dilute_initial = value
[docs] @abstractmethod
def __call__(self, vec, source_rate):
"""Runs a simulation.
Parameters
----------
vec : list of numpy.ndarray
Total atoms to be used in function.
source_rate : float
Power in [W] or source rate in [neutron/sec]
Returns
-------
openmc.deplete.OperatorResult
Eigenvalue and reaction rates resulting from transport operator
"""
def __enter__(self):
# Save current directory and move to specific output directory
self._orig_dir = os.getcwd()
if not self.output_dir.exists():
self.output_dir.mkdir() # exist_ok parameter is 3.5+
# In Python 3.6+, chdir accepts a Path directly
os.chdir(str(self.output_dir))
return self.initial_condition()
def __exit__(self, exc_type, exc_value, traceback):
self.finalize()
os.chdir(self._orig_dir)
@property
def output_dir(self):
return self._output_dir
@output_dir.setter
def output_dir(self, output_dir):
self._output_dir = Path(output_dir)
[docs] @abstractmethod
def initial_condition(self):
"""Performs final setup and returns initial condition.
Returns
-------
list of numpy.ndarray
Total density for initial conditions.
"""
[docs] @abstractmethod
def get_results_info(self):
"""Returns volume list, cell lists, and nuc lists.
Returns
-------
volume : dict of str to float
Volumes corresponding to materials in burn_list
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 cell IDs to be burned. Used for sorting the
simulation.
full_burn_list : list of int
All burnable materials in the geometry.
"""
def finalize(self):
pass
[docs] @abstractmethod
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
"""
[docs]class ReactionRateHelper(ABC):
"""Abstract class for generating reaction rates for operators
Responsible for generating reaction rate tallies for burnable materials,
given nuclides and scores from the operator.
Reaction rates are passed back to the operator to be used by an
:class:`openmc.deplete.OperatorResult` instance.
Parameters
----------
n_nucs : int
Number of burnable nuclides tracked by :class:`openmc.deplete.Operator`
n_react : int
Number of reactions tracked by :class:`openmc.deplete.Operator`
Attributes
----------
nuclides : list of str
All nuclides with desired reaction rates.
"""
def __init__(self, n_nucs, n_react):
self._nuclides = None
self._results_cache = empty((n_nucs, n_react))
[docs] @abstractmethod
def generate_tallies(self, materials, scores):
"""Use the C API to build tallies needed for reaction rates"""
@property
def nuclides(self):
"""List of nuclides with requested reaction rates"""
return self._nuclides
@nuclides.setter
def nuclides(self, nuclides):
check_type("nuclides", nuclides, list, str)
self._nuclides = nuclides
[docs] @abstractmethod
def get_material_rates(self, mat_id, nuc_index, react_index):
"""Return 2D array of [nuclide, reaction] reaction rates
Parameters
----------
mat_id : int
Unique ID for the requested material
nuc_index : list of str
Ordering of desired nuclides
react_index : list of str
Ordering of reactions
"""
[docs] def divide_by_adens(self, number):
"""Normalize reaction rates by number of nuclides
Acts on the current material examined by :meth:`get_material_rates`
Parameters
----------
number : iterable of float
Number density [atoms/b-cm] of each nuclide tracked in the
calculation.
Returns
-------
results : numpy.ndarray
Array of reactions rates of shape ``(n_nuclides, n_rxns)``
normalized by the number of nuclides
"""
mask = nonzero(number)
results = self._results_cache
for col in range(results.shape[1]):
results[mask, col] /= number[mask]
return results
[docs]class NormalizationHelper(ABC):
"""Abstract class for obtaining normalization factor on tallies
This helper class determines how reaction rates calculated by an instance of
:class:`openmc.deplete.Operator` should be normalized for the purpose of
constructing a burnup matrix. Based on the method chosen, the power or
source rate provided by the user, and reaction rates from a
:class:`ReactionRateHelper`, this class will scale reaction rates to the
correct values.
Attributes
----------
nuclides : list of str
All nuclides with desired reaction rates. Ordered to be
consistent with :class:`openmc.deplete.Operator`
"""
def __init__(self):
self._nuclides = None
[docs] def reset(self):
"""Reset state for normalization"""
[docs] @abstractmethod
def prepare(self, chain_nucs, rate_index):
"""Perform work needed to obtain energy produced
This method is called prior to the transport simulations
in :meth:`openmc.deplete.Operator.initial_condition`. Only used for
energy-based normalization.
Parameters
----------
chain_nucs : list of str
All nuclides to be tracked in this problem
rate_index : dict of str to int
Mapping from nuclide name to index in the
`fission_rates` for :meth:`update`.
"""
[docs] def update(self, fission_rates):
"""Update the normalization based on fission rates (only used for
energy-based normalization)
Parameters
----------
fission_rates : numpy.ndarray
fission reaction rate for each isotope in the specified
material. Should be ordered corresponding to initial
``rate_index`` used in :meth:`prepare`
"""
@property
def nuclides(self):
"""List of nuclides with requested reaction rates"""
return self._nuclides
@nuclides.setter
def nuclides(self, nuclides):
check_type("nuclides", nuclides, list, str)
self._nuclides = nuclides
[docs] @abstractmethod
def factor(self, source_rate):
"""Return normalization factor
Parameters
----------
source_rate : float
Power in [W] or source rate in [neutron/sec]
Returns
-------
float
Normalization factor for tallies
"""
[docs]class FissionYieldHelper(ABC):
"""Abstract class for processing energy dependent fission yields
Parameters
----------
chain_nuclides : iterable of openmc.deplete.Nuclide
Nuclides tracked in the depletion chain. All nuclides are
not required to have fission yield data.
Attributes
----------
constant_yields : collections.defaultdict
Fission yields for all nuclides that only have one set of
fission yield data. Dictionary of form ``{str: {str: float}}``
representing yields for ``{parent: {product: yield}}``. Default
return object is an empty dictionary
"""
def __init__(self, chain_nuclides):
self._chain_nuclides = {}
self._constant_yields = defaultdict(dict)
# Get all nuclides with fission yield data
for nuc in chain_nuclides:
if nuc.yield_data is None:
continue
if len(nuc.yield_data) == 1:
self._constant_yields[nuc.name] = (
nuc.yield_data[nuc.yield_energies[0]])
elif len(nuc.yield_data) > 1:
self._chain_nuclides[nuc.name] = nuc
self._chain_set = set(self._chain_nuclides) | set(self._constant_yields)
@property
def constant_yields(self):
return deepcopy(self._constant_yields)
[docs] @abstractmethod
def weighted_yields(self, local_mat_index):
"""Return fission yields for a specific material
Parameters
----------
local_mat_index : int
Index for the material with requested fission yields.
Should correspond to the material represented in
``mat_indexes[local_mat_index]`` during
:meth:`generate_tallies`.
Returns
-------
library : collections.abc.Mapping
Dictionary-like object mapping ``{str: {str: float}``.
This reflects fission yields for ``{parent: {product: fyield}}``.
"""
[docs] @staticmethod
def unpack():
"""Unpack tally data prior to compute fission yields.
Called after a :meth:`openmc.deplete.Operator.__call__`
routine during the normalization of reaction rates.
Not necessary for all subclasses to implement, unless tallies
are used.
"""
[docs] @staticmethod
def generate_tallies(materials, mat_indexes):
"""Construct tallies necessary for computing fission yields
Called during the operator set up phase prior to depleting.
Not necessary for subclasses to implement
Parameters
----------
materials : iterable of C-API materials
Materials to be used in :class:`openmc.lib.MaterialFilter`
mat_indexes : iterable of int
Indices of tallied materials that will have their fission
yields computed by this helper. Necessary as the
:class:`openmc.deplete.Operator` that uses this helper
may only burn a subset of all materials when running
in parallel mode.
"""
[docs] def update_tally_nuclides(self, nuclides):
"""Return nuclides with non-zero densities and yield data
Parameters
----------
nuclides : iterable of str
Nuclides with non-zero densities from the
:class:`openmc.deplete.Operator`
Returns
-------
nuclides : list of str
Union of nuclides that the :class:`openmc.deplete.Operator`
says have non-zero densities at this stage and those that
have yield data. Sorted by nuclide name
"""
return sorted(self._chain_set & set(nuclides))
[docs] @classmethod
def from_operator(cls, operator, **kwargs):
"""Create a new instance by pulling data from the operator
All keyword arguments should be identical to their counterpart
in the main ``__init__`` method
Parameters
----------
operator : openmc.deplete.TransportOperator
Operator with a depletion chain
kwargs: optional
Additional keyword arguments to be used in constuction
"""
return cls(operator.chain.nuclides, **kwargs)
[docs]class TalliedFissionYieldHelper(FissionYieldHelper):
"""Abstract class for computing fission yields with tallies
Generates a basic fission rate tally in all burnable materials with
:meth:`generate_tallies`, and set nuclides to be tallied with
:meth:`update_tally_nuclides`. Subclasses will need to implement
:meth:`unpack` and :meth:`weighted_yields`.
Parameters
----------
chain_nuclides : iterable of openmc.deplete.Nuclide
Nuclides tracked in the depletion chain. Not necessary
that all have yield data.
Attributes
----------
constant_yields : dict of str to :class:`openmc.deplete.FissionYield`
Fission yields for all nuclides that only have one set of
fission yield data. Can be accessed as ``{parent: {product: yield}}``
results : None or numpy.ndarray
Tally results shaped in a manner useful to this helper.
"""
_upper_energy = 20.0e6 # upper energy for tallies
def __init__(self, chain_nuclides):
super().__init__(chain_nuclides)
self._local_indexes = None
self._fission_rate_tally = None
self._tally_nucs = []
self.results = None
[docs] def generate_tallies(self, materials, mat_indexes):
"""Construct the fission rate tally
Parameters
----------
materials : iterable of :class:`openmc.lib.Material`
Materials to be used in :class:`openmc.lib.MaterialFilter`
mat_indexes : iterable of int
Indices of tallied materials that will have their fission
yields computed by this helper. Necessary as the
:class:`openmc.deplete.Operator` that uses this helper
may only burn a subset of all materials when running
in parallel mode.
"""
self._local_indexes = asarray(mat_indexes)
# Tally group-wise fission reaction rates
self._fission_rate_tally = Tally()
self._fission_rate_tally.writable = False
self._fission_rate_tally.scores = ['fission']
self._fission_rate_tally.filters = [MaterialFilter(materials)]
[docs] def update_tally_nuclides(self, nuclides):
"""Tally nuclides with non-zero density and multiple yields
Must be run after :meth:`generate_tallies`.
Parameters
----------
nuclides : iterable of str
Potential nuclides to be tallied, such as those with
non-zero density at this stage.
Returns
-------
nuclides : list of str
Union of input nuclides and those that have multiple sets
of yield data. Sorted by nuclide name
Raises
------
AttributeError
If tallies not generated
"""
assert self._fission_rate_tally is not None, (
"Run generate_tallies first")
overlap = set(self._chain_nuclides).intersection(set(nuclides))
nuclides = sorted(overlap)
self._tally_nucs = [self._chain_nuclides[n] for n in nuclides]
self._fission_rate_tally.nuclides = nuclides
return nuclides
[docs] @abstractmethod
def unpack(self):
"""Unpack tallies after a transport run.
Abstract because each subclass will need to arrange its
tally data.
"""
def add_params(cls):
cls.__doc__ += cls._params
return cls
[docs]@add_params
class Integrator(ABC):
r"""Abstract class for solving the time-integration for depletion
"""
_params = r"""
Parameters
----------
operator : openmc.deplete.TransportOperator
Operator to perform transport simulations
timesteps : iterable of float or iterable of tuple
Array of timesteps. Note that values are not cumulative. The units are
specified by the `timestep_units` argument when `timesteps` is an
iterable of float. Alternatively, units can be specified for each step
by passing an iterable of (value, unit) tuples.
power : float or iterable of float, optional
Power of the reactor in [W]. A single value indicates that
the power is constant over all timesteps. An iterable
indicates potentially different power levels for each timestep.
For a 2D problem, the power can be given in [W/cm] as long
as the "volume" assigned to a depletion material is actually
an area in [cm^2]. Either ``power``, ``power_density``, or
``source_rates`` must be specified.
power_density : float or iterable of float, optional
Power density of the reactor in [W/gHM]. It is multiplied by
initial heavy metal inventory to get total power if ``power``
is not speficied.
source_rates : float or iterable of float, optional
Source rate in [neutron/sec] for each interval in :attr:`timesteps`
.. versionadded:: 0.12.1
timestep_units : {'s', 'min', 'h', 'd', 'MWd/kg'}
Units for values specified in the `timesteps` argument. 's' means
seconds, 'min' means minutes, 'h' means hours, and 'MWd/kg' indicates
that the values are given in burnup (MW-d of energy deposited per
kilogram of initial heavy metal).
solver : str or callable, optional
If a string, must be the name of the solver responsible for
solving the Bateman equations. Current options are:
* ``cram16`` - 16th order IPF CRAM
* ``cram48`` - 48th order IPF CRAM [default]
If a function or other callable, must adhere to the requirements in
:attr:`solver`.
.. versionadded:: 0.12
Attributes
----------
operator : openmc.deplete.TransportOperator
Operator to perform transport simulations
chain : openmc.deplete.Chain
Depletion chain
timesteps : iterable of float
Size of each depletion interval in [s]
source_rates : iterable of float
Source rate in [W] or [neutron/sec] for each interval in
:attr:`timesteps`
solver : callable
Function that will solve the Bateman equations
:math:`\frac{\partial}{\partial t}\vec{n} = A_i\vec{n}_i` with a step
size :math:`t_i`. Can be configured using the ``solver`` argument.
User-supplied functions are expected to have the following signature:
``solver(A, n0, t) -> n1`` where
* ``A`` is a :class:`scipy.sparse.csr_matrix` making up the
depletion matrix
* ``n0`` is a 1-D :class:`numpy.ndarray` of initial compositions
for a given material in atoms/cm3
* ``t`` is a float of the time step size in seconds, and
* ``n1`` is a :class:`numpy.ndarray` of compositions at the
next time step. Expected to be of the same shape as ``n0``
.. versionadded:: 0.12
"""
def __init__(self, operator, timesteps, power=None, power_density=None,
source_rates=None, timestep_units='s', solver="cram48"):
# Check number of stages previously used
if operator.prev_res is not None:
res = operator.prev_res[-1]
if res.data.shape[0] != self._num_stages:
raise ValueError(
"{} incompatible with previous restart calculation. "
"Previous scheme used {} intermediate solutions, while "
"this uses {}".format(
self.__class__.__name__, res.data.shape[0],
self._num_stages))
self.operator = operator
self.chain = operator.chain
# Determine source rate and normalize units to W in using power
if power is not None:
source_rates = power
elif power_density is not None:
if not isinstance(power_density, Iterable):
source_rates = power_density * operator.heavy_metal
else:
source_rates = [p*operator.heavy_metal for p in power_density]
elif source_rates is None:
raise ValueError("Either power, power_density, or source_rates must be set")
if not isinstance(source_rates, Iterable):
# Ensure that rate is single value if that is the case
source_rates = [source_rates] * len(timesteps)
if len(source_rates) != len(timesteps):
raise ValueError(
"Number of time steps ({}) != number of powers ({})".format(
len(timesteps), len(source_rates)))
# Get list of times / units
if isinstance(timesteps[0], Iterable):
times, units = zip(*timesteps)
else:
times = timesteps
units = [timestep_units] * len(timesteps)
# Determine number of seconds for each timestep
seconds = []
for timestep, unit, rate in zip(times, units, source_rates):
# Make sure values passed make sense
check_type('timestep', timestep, Real)
check_greater_than('timestep', timestep, 0.0, False)
check_type('timestep units', unit, str)
check_type('source rate', rate, Real)
check_greater_than('source rate', rate, 0.0, True)
if unit in ('s', 'sec'):
seconds.append(timestep)
elif unit in ('min', 'minute'):
seconds.append(timestep*_SECONDS_PER_MINUTE)
elif unit in ('h', 'hr', 'hour'):
seconds.append(timestep*_SECONDS_PER_HOUR)
elif unit in ('d', 'day'):
seconds.append(timestep*_SECONDS_PER_DAY)
elif unit.lower() == 'mwd/kg':
watt_days_per_kg = 1e6*timestep
kilograms = 1e-3*operator.heavy_metal
days = watt_days_per_kg * kilograms / rate
seconds.append(days*_SECONDS_PER_DAY)
else:
raise ValueError("Invalid timestep unit '{}'".format(unit))
self.timesteps = asarray(seconds)
self.source_rates = asarray(source_rates)
if isinstance(solver, str):
# Delay importing of cram module, which requires this file
if solver == "cram48":
from .cram import CRAM48
self._solver = CRAM48
elif solver == "cram16":
from .cram import CRAM16
self._solver = CRAM16
else:
raise ValueError(
"Solver {} not understood. Expected 'cram48' or "
"'cram16'".format(solver))
else:
self.solver = solver
@property
def solver(self):
return self._solver
@solver.setter
def solver(self, func):
if not isinstance(func, Callable):
raise TypeError(
"Solver must be callable, not {}".format(type(func)))
try:
sig = signature(func)
except ValueError:
# Guard against callables that aren't introspectable, e.g.
# fortran functions wrapped by F2PY
warn("Could not determine arguments to {}. Proceeding "
"anyways".format(func))
self._solver = func
return
# Inspect arguments
if len(sig.parameters) != 3:
raise ValueError("Function {} does not support three arguments: "
"{!s}".format(func, sig))
for ix, param in enumerate(sig.parameters.values()):
if param.kind in {param.KEYWORD_ONLY, param.VAR_KEYWORD}:
raise ValueError(
"Keyword arguments like {} at position {} are not "
"allowed".format(ix, param))
self._solver = func
def _timed_deplete(self, concs, rates, dt, matrix_func=None):
start = time.time()
results = deplete(
self._solver, self.chain, concs, rates, dt, matrix_func)
return time.time() - start, results
[docs] @abstractmethod
def __call__(self, conc, rates, dt, source_rate, i):
"""Perform the integration across one time step
Parameters
----------
conc : numpy.ndarray
Initial concentrations for all nuclides in [atom]
rates : openmc.deplete.ReactionRates
Reaction rates from operator
dt : float
Time in [s] for the entire depletion interval
source_rate : float
Power in [W] or source rate in [neutron/sec]
i : int
Current depletion step index
Returns
-------
proc_time : float
Time spent in CRAM routines for all materials in [s]
conc_list : list of numpy.ndarray
Concentrations at each of the intermediate points with
the final concentration as the last element
op_results : list of openmc.deplete.OperatorResult
Eigenvalue and reaction rates from intermediate transport
simulations
"""
@property
@abstractmethod
def _num_stages(self):
"""Number of intermediate transport solutions
Needed to ensure schemes are consistent with restarts
"""
[docs] def __iter__(self):
"""Return pair of time step in [s] and source rate in [W] or [neutron/sec]"""
return zip(self.timesteps, self.source_rates)
[docs] def __len__(self):
"""Return integer number of depletion intervals"""
return len(self.timesteps)
def _get_bos_data_from_operator(self, step_index, source_rate, bos_conc):
"""Get beginning of step concentrations, reaction rates from Operator
"""
x = deepcopy(bos_conc)
res = self.operator(x, source_rate)
self.operator.write_bos_data(step_index + self._i_res)
return x, res
def _get_bos_data_from_restart(self, step_index, source_rate, bos_conc):
"""Get beginning of step concentrations, reaction rates from restart"""
res = self.operator.prev_res[-1]
# Depletion methods expect list of arrays
bos_conc = list(res.data[0])
rates = res.rates[0]
k = ufloat(res.k[0, 0], res.k[0, 1])
# Scale reaction rates by ratio of source rates
rates *= source_rate / res.source_rate[0]
return bos_conc, OperatorResult(k, rates)
def _get_start_data(self):
if self.operator.prev_res is None:
return 0.0, 0
return (self.operator.prev_res[-1].time[-1],
len(self.operator.prev_res) - 1)
[docs] def integrate(self, final_step=True):
"""Perform the entire depletion process across all steps
Parameters
----------
final_step : bool, optional
Indicate whether or not a transport solve should be run at the end
of the last timestep.
.. versionadded:: 0.12.1
"""
with self.operator as conc:
t, self._i_res = self._get_start_data()
for i, (dt, source_rate) in enumerate(self):
# Solve transport equation (or obtain result from restart)
if i > 0 or self.operator.prev_res is None:
conc, res = self._get_bos_data_from_operator(i, source_rate, conc)
else:
conc, res = self._get_bos_data_from_restart(i, source_rate, conc)
# Solve Bateman equations over time interval
proc_time, conc_list, res_list = self(conc, res.rates, dt, source_rate, i)
# Insert BOS concentration, transport results
conc_list.insert(0, conc)
res_list.insert(0, res)
# Remove actual EOS concentration for next step
conc = conc_list.pop()
Results.save(self.operator, conc_list, res_list, [t, t + dt],
source_rate, self._i_res + i, proc_time)
t += dt
# Final simulation -- in the case that final_step is False, a zero
# source rate is passed to the transport operator (which knows to
# just return zero reaction rates without actually doing a transport
# solve)
res_list = [self.operator(conc, source_rate if final_step else 0.0)]
Results.save(self.operator, [conc], res_list, [t, t],
source_rate, self._i_res + len(self), proc_time)
self.operator.write_bos_data(len(self) + self._i_res)
[docs]@add_params
class SIIntegrator(Integrator):
r"""Abstract class for the Stochastic Implicit Euler integrators
Does not provide a ``__call__`` method, but scales and resets
the number of particles used in initial transport calculation
"""
_params = r"""
Parameters
----------
operator : openmc.deplete.TransportOperator
The operator object to simulate on.
timesteps : iterable of float or iterable of tuple
Array of timesteps. Note that values are not cumulative. The units are
specified by the `timestep_units` argument when `timesteps` is an
iterable of float. Alternatively, units can be specified for each step
by passing an iterable of (value, unit) tuples.
power : float or iterable of float, optional
Power of the reactor in [W]. A single value indicates that
the power is constant over all timesteps. An iterable
indicates potentially different power levels for each timestep.
For a 2D problem, the power can be given in [W/cm] as long
as the "volume" assigned to a depletion material is actually
an area in [cm^2]. Either ``power``, ``power_density``, or
``source_rates`` must be specified.
power_density : float or iterable of float, optional
Power density of the reactor in [W/gHM]. It is multiplied by
initial heavy metal inventory to get total power if ``power``
is not speficied.
source_rates : float or iterable of float, optional
Source rate in [neutron/sec] for each interval in :attr:`timesteps`
.. versionadded:: 0.12.1
timestep_units : {'s', 'min', 'h', 'd', 'MWd/kg'}
Units for values specified in the `timesteps` argument. 's' means
seconds, 'min' means minutes, 'h' means hours, and 'MWd/kg' indicates
that the values are given in burnup (MW-d of energy deposited per
kilogram of initial heavy metal).
n_steps : int, optional
Number of stochastic iterations per depletion interval.
Must be greater than zero. Default : 10
solver : str or callable, optional
If a string, must be the name of the solver responsible for
solving the Bateman equations. Current options are:
* ``cram16`` - 16th order IPF CRAM
* ``cram48`` - 48th order IPF CRAM [default]
If a function or other callable, must adhere to the requirements in
:attr:`solver`.
.. versionadded:: 0.12
Attributes
----------
operator : openmc.deplete.TransportOperator
Operator to perform transport simulations
chain : openmc.deplete.Chain
Depletion chain
timesteps : iterable of float
Size of each depletion interval in [s]
power : iterable of float
Power of the reactor in [W] for each interval in :attr:`timesteps`
n_steps : int
Number of stochastic iterations per depletion interval
solver : callable
Function that will solve the Bateman equations
:math:`\frac{\partial}{\partial t}\vec{n} = A_i\vec{n}_i` with a step
size :math:`t_i`. Can be configured using the ``solver`` argument.
User-supplied functions are expected to have the following signature:
``solver(A, n0, t) -> n1`` where
* ``A`` is a :class:`scipy.sparse.csr_matrix` making up the
depletion matrix
* ``n0`` is a 1-D :class:`numpy.ndarray` of initial compositions
for a given material in atoms/cm3
* ``t`` is a float of the time step size in seconds, and
* ``n1`` is a :class:`numpy.ndarray` of compositions at the
next time step. Expected to be of the same shape as ``n0``
.. versionadded:: 0.12
"""
def __init__(self, operator, timesteps, power=None, power_density=None,
source_rates=None, timestep_units='s', n_steps=10,
solver="cram48"):
check_type("n_steps", n_steps, Integral)
check_greater_than("n_steps", n_steps, 0)
super().__init__(
operator, timesteps, power, power_density, source_rates,
timestep_units=timestep_units, solver=solver)
self.n_steps = n_steps
def _get_bos_data_from_operator(self, step_index, step_power, bos_conc):
reset_particles = False
if step_index == 0 and hasattr(self.operator, "settings"):
reset_particles = True
self.operator.settings.particles *= self.n_steps
inherited = super()._get_bos_data_from_operator(
step_index, step_power, bos_conc)
if reset_particles:
self.operator.settings.particles //= self.n_steps
return inherited
[docs] def integrate(self):
"""Perform the entire depletion process across all steps"""
with self.operator as conc:
t, self._i_res = self._get_start_data()
for i, (dt, p) in enumerate(self):
if i == 0:
if self.operator.prev_res is None:
conc, res = self._get_bos_data_from_operator(i, p, conc)
else:
conc, res = self._get_bos_data_from_restart(i, p, conc)
else:
# Pull rates, k from previous iteration w/o
# re-running transport
res = res_list[-1] # defined in previous i iteration
proc_time, conc_list, res_list = self(conc, res.rates, dt, p, i)
# Insert BOS concentration, transport results
conc_list.insert(0, conc)
res_list.insert(0, res)
# Remove actual EOS concentration for next step
conc = conc_list.pop()
Results.save(self.operator, conc_list, res_list, [t, t + dt],
p, self._i_res + i, proc_time)
t += dt
# No final simulation for SIE, use last iteration results
Results.save(self.operator, [conc], [res_list[-1]], [t, t],
p, self._i_res + len(self), proc_time)
self.operator.write_bos_data(self._i_res + len(self))
[docs]class DepSystemSolver(ABC):
r"""Abstract class for solving depletion equations
Responsible for solving
.. math::
\frac{\partial \vec{N}}{\partial t} = \bar{A}\vec{N}(t),
for :math:`0< t\leq t +\Delta t`, given :math:`\vec{N}(0) = \vec{N}_0`
"""
[docs] @abstractmethod
def __call__(self, A, n0, dt):
"""Solve the linear system of equations for depletion
Parameters
----------
A : scipy.sparse.csr_matrix
Sparse transmutation matrix ``A[j, i]`` desribing rates at
which isotope ``i`` transmutes to isotope ``j``
n0 : numpy.ndarray
Initial compositions, typically given in number of atoms in some
material or an atom density
dt : float
Time [s] of the specific interval to be solved
Returns
-------
numpy.ndarray
Final compositions after ``dt``. Should be of identical shape
to ``n0``.
"""