diff --git a/include/openmc/random_ray/flat_source_domain.h b/include/openmc/random_ray/flat_source_domain.h index 0d4086966dd..33d62ce1035 100644 --- a/include/openmc/random_ray/flat_source_domain.h +++ b/include/openmc/random_ray/flat_source_domain.h @@ -40,9 +40,10 @@ class FlatSourceDomain { void random_ray_tally(); virtual void accumulate_iteration_flux(); void output_to_vtk() const; - void convert_external_sources(); + void convert_external_sources(bool use_adjoint_sources); void count_external_source_regions(); - void set_adjoint_sources(); + void set_fw_adjoint_sources(); + void set_local_adjoint_sources(); void flux_swap(); virtual double evaluate_flux_at_point(Position r, int64_t sr, int g) const; double compute_fixed_source_normalization_factor() const; @@ -76,6 +77,7 @@ class FlatSourceDomain { // Static Data members static bool volume_normalized_flux_tallies_; static bool adjoint_; // If the user wants outputs based on the adjoint flux + static bool cadis_; static double diagonal_stabilization_rho_; // Adjusts strength of diagonal stabilization // for transport corrected MGXS data @@ -84,6 +86,8 @@ class FlatSourceDomain { static std::unordered_map>> mesh_domain_map_; + static std::vector cadis_targets_; + //---------------------------------------------------------------------------- // Static data members static RandomRayVolumeEstimator volume_estimator_; diff --git a/include/openmc/random_ray/random_ray_simulation.h b/include/openmc/random_ray/random_ray_simulation.h index 3db6510697c..c783f8ce5f8 100644 --- a/include/openmc/random_ray/random_ray_simulation.h +++ b/include/openmc/random_ray/random_ray_simulation.h @@ -19,9 +19,10 @@ class RandomRaySimulation { //---------------------------------------------------------------------------- // Methods + void compute_segment_correction_factors(); void apply_fixed_sources_and_mesh_domains(); - void prepare_fixed_sources_adjoint(); - void prepare_adjoint_simulation(); + void prepare_fw_fixed_sources_adjoint(); + void prepare_local_fixed_sources_adjoint(); void simulate(); void output_simulation_results() const; void instability_check( @@ -34,15 +35,9 @@ class RandomRaySimulation { // Accessors FlatSourceDomain* domain() const { return domain_.get(); } - //---------------------------------------------------------------------------- - // Public data members - - // Flag for adjoint simulation; - bool adjoint_needed_; - private: //---------------------------------------------------------------------------- - // Private data members + // Data members // Contains all flat source region data unique_ptr domain_; @@ -57,9 +52,6 @@ class RandomRaySimulation { // Number of energy groups int negroups_; - // Toggle for first simulation - bool is_first_simulation_; - }; // class RandomRaySimulation //============================================================================ @@ -69,7 +61,6 @@ class RandomRaySimulation { void openmc_run_random_ray(); void validate_random_ray_inputs(); void openmc_reset_random_ray(); -void print_adjoint_header(); } // namespace openmc diff --git a/include/openmc/source.h b/include/openmc/source.h index 36c821fc07c..c36d2464bd7 100644 --- a/include/openmc/source.h +++ b/include/openmc/source.h @@ -34,6 +34,7 @@ class Source; namespace model { extern vector> external_sources; +extern vector> adjoint_sources; // Probability distribution for selecting external sources extern DiscreteIndex external_sources_probability; diff --git a/include/openmc/weight_windows.h b/include/openmc/weight_windows.h index 7638155228e..c21200440fd 100644 --- a/include/openmc/weight_windows.h +++ b/include/openmc/weight_windows.h @@ -17,7 +17,7 @@ namespace openmc { -enum class WeightWindowUpdateMethod { MAGIC, FW_CADIS }; +enum class WeightWindowUpdateMethod { MAGIC, FW_CADIS, CADIS }; //============================================================================== // Constants @@ -235,6 +235,9 @@ class WeightWindowsGenerator { double threshold_ {1.0}; // targets_; }; //! Finalize variance reduction objects after all inputs have been read diff --git a/openmc/model/model.py b/openmc/model/model.py index 90b43f9f74f..0935cd73df6 100644 --- a/openmc/model/model.py +++ b/openmc/model/model.py @@ -265,6 +265,37 @@ def add_kinetics_parameters_tallies(self, num_groups: int | None = None): denom_tally = openmc.Tally(name='IFP denominator') denom_tally.scores = ['ifp-denominator'] self.tallies.append(denom_tally) + + # TODO: This should also be incorporated into lower-level calls in + # settings.py, but it requires information about the tallies currently + # on the active Model + def _assign_cadis_tally_IDs(self): + # Verify that all tallies assigned as targets on WeightWindowGenerators + # exist within model.tallies. If this is the case, convert the .targets + # attribute of each WeightWindowGenerator to a sequence of tally IDs. + if len(self.settings.weight_window_generators) == 0: + return + + for wwg in self.settings.weight_window_generators: + # Only proceeds if the "targets" attribute is an openmc.Tallies, + # which means it hasn't been checked against model.tallies. + if isinstance(wwg.targets, openmc.Tallies): + id_vec = [] + for tal in wwg.targets: + # check against model tallies + id_next = None + for reference_tal in self.tallies: + if tal == reference_tal: + id_next = reference_tal.id + break + + if id_next == None: + raise RuntimeError( + f'CADIS target tally {tal.id} not found on model.tallies!') + else: + id_vec.append(id_next) + + wwg.targets = id_vec @classmethod def from_xml( @@ -576,6 +607,7 @@ def export_to_xml(self, directory: PathLike = '.', remove_surfs: bool = False, if not d.is_dir(): d.mkdir(parents=True, exist_ok=True) + self._assign_cadis_tally_IDs() self.settings.export_to_xml(d) self.geometry.export_to_xml(d, remove_surfs=remove_surfs) @@ -634,6 +666,9 @@ def export_to_model_xml(self, path: PathLike = 'model.xml', remove_surfs: bool = "set the Geometry.merge_surfaces attribute instead.") self.geometry.merge_surfaces = True + # Link CADIS WeightWindowGenerator target tallies, if present + self._assign_cadis_tally_IDs() + # provide a memo to track which meshes have been written mesh_memo = set() settings_element = self.settings.to_xml_element(mesh_memo) diff --git a/openmc/settings.py b/openmc/settings.py index 3cf662e311e..74fd4ca5f1a 100644 --- a/openmc/settings.py +++ b/openmc/settings.py @@ -225,6 +225,9 @@ class Settings: stabilization, which may be desirable as stronger diagonal stabilization also tends to dampen the convergence rate of the solver, thus requiring more iterations to converge. + :adjoint_source: + Source object used to define localized adjoint source/detector response + function. .. versionadded:: 0.15.0 resonance_scattering : dict @@ -1356,6 +1359,8 @@ def random_ray(self, random_ray: dict): cv.check_type('diagonal stabilization rho', value, Real) cv.check_greater_than('diagonal stabilization rho', value, 0.0, True) + elif key == 'adjoint_source': + cv.check_type('adjoint source', value, SourceBase) else: raise ValueError(f'Unable to set random ray to "{key}" which is ' 'unsupported by OpenMC') @@ -1887,11 +1892,12 @@ def _create_random_ray_subelement(self, root, mesh_memo=None): element = ET.SubElement(root, "random_ray") for key, value in self._random_ray.items(): if key == 'ray_source' and isinstance(value, SourceBase): + subelement = ET.SubElement(element, 'ray_source') source_element = value.to_xml_element() if source_element.find('bias') is not None: raise RuntimeError( "Ray source distributions should not be biased.") - element.append(source_element) + subelement.append(source_element) elif key == 'source_region_meshes': subelement = ET.SubElement(element, 'source_region_meshes') @@ -1909,8 +1915,12 @@ def _create_random_ray_subelement(self, root, mesh_memo=None): path = f"./mesh[@id='{mesh.id}']" if root.find(path) is None: root.append(mesh.to_xml_element()) - if mesh_memo is not None: + if mesh_memo is not None: mesh_memo.add(mesh.id) + elif key == 'adjoint_source' and isinstance(value, SourceBase): + subelement = ET.SubElement(element, 'adjoint_source') + adj_source_element = value.to_xml_element() + subelement.append(adj_source_element) elif isinstance(value, bool): subelement = ET.SubElement(element, key) subelement.text = str(value).lower() @@ -2337,8 +2347,9 @@ def _random_ray_from_xml_element(self, root, meshes=None): for child in elem: if child.tag in ('distance_inactive', 'distance_active', 'diagonal_stabilization_rho'): self.random_ray[child.tag] = float(child.text) - elif child.tag == 'source': - source = SourceBase.from_xml_element(child) + elif child.tag == 'ray_source': + source_element = child.find('source') + source = SourceBase.from_xml_element(source_element) if child.find('bias') is not None: raise RuntimeError( "Ray source distributions should not be biased.") @@ -2355,6 +2366,11 @@ def _random_ray_from_xml_element(self, root, meshes=None): self.random_ray['adjoint'] = ( child.text in ('true', '1') ) + elif child.tag == 'adjoint_source': + for subelem in child.findall('source'): + src = SourceBase.from_xml_element(subelem) + # add newly constructed source object to the list + self.random_ray['adjoint_source'].append(src) elif child.tag == 'sample_method': self.random_ray['sample_method'] = child.text elif child.tag == 'source_region_meshes': diff --git a/openmc/tallies.py b/openmc/tallies.py index 74d4722af47..13ad1e57452 100644 --- a/openmc/tallies.py +++ b/openmc/tallies.py @@ -16,6 +16,23 @@ import openmc import openmc.checkvalue as cv +from openmc.filter import ( + Filter, + DistribcellFilter, + EnergyFunctionFilter, + DelayedGroupFilter, + FilterMeta, + MeshFilter, + MeshBornFilter, +) +from openmc.arithmetic import ( + CrossFilter, + AggregateFilter, + CrossScore, + AggregateScore, + CrossNuclide, + AggregateNuclide, +) from ._sparse_compat import lil_array from ._xml import clean_indentation, get_elem_list, get_text from .mixin import IDManagerMixin @@ -31,9 +48,9 @@ # The following indicate acceptable types when setting Tally.scores, # Tally.nuclides, and Tally.filters -_SCORE_CLASSES = (str, openmc.CrossScore, openmc.AggregateScore) -_NUCLIDE_CLASSES = (str, openmc.CrossNuclide, openmc.AggregateNuclide) -_FILTER_CLASSES = (openmc.Filter, openmc.CrossFilter, openmc.AggregateFilter) +_SCORE_CLASSES = (str, CrossScore, AggregateScore) +_NUCLIDE_CLASSES = (str, CrossNuclide, AggregateNuclide) +_FILTER_CLASSES = (Filter, CrossFilter, AggregateFilter) # Valid types of estimators ESTIMATOR_TYPES = {'tracklength', 'collision', 'analog'} @@ -394,7 +411,7 @@ def _read_results(self): self._num_realizations = int(group['n_realizations'][()]) for filt in self.filters: - if isinstance(filt, openmc.DistribcellFilter): + if isinstance(filt, DistribcellFilter): filter_group = f[f'tallies/filters/filter {filt.id}'] filt._num_bins = int(filter_group['n_bins'][()]) @@ -1062,8 +1079,8 @@ def _can_merge_filters(self, other): return False # Return False if only one tally has a delayed group filter - tally1_dg = self.contains_filter(openmc.DelayedGroupFilter) - tally2_dg = other.contains_filter(openmc.DelayedGroupFilter) + tally1_dg = self.contains_filter(DelayedGroupFilter) + tally2_dg = other.contains_filter(DelayedGroupFilter) if tally1_dg != tally2_dg: return False @@ -1575,7 +1592,7 @@ def find_filter(self, filter_type): # Also check to see if the desired filter is wrapped up in an # aggregate - elif isinstance(test_filter, openmc.AggregateFilter): + elif isinstance(test_filter, AggregateFilter): if isinstance(test_filter.aggregate_filter, filter_type): return test_filter @@ -1677,7 +1694,7 @@ def get_filter_indices(self, filters=[], filter_bins=[]): """ - cv.check_type('filters', filters, Iterable, openmc.FilterMeta) + cv.check_type('filters', filters, Iterable, FilterMeta) cv.check_type('filter_bins', filter_bins, Iterable, tuple) # If user did not specify any specific Filters, use them all @@ -1760,7 +1777,7 @@ def get_score_indices(self, scores): """ for score in scores: - if not isinstance(score, (str, openmc.CrossScore)): + if not isinstance(score, (str, CrossScore)): msg = f'Unable to get score indices for score "{score}" in ' \ f'ID="{self.id}" since it is not a string or CrossScore ' \ 'Tally' @@ -1957,9 +1974,9 @@ def get_pandas_dataframe(self, filters=True, nuclides=True, scores=True, column_name = 'score' for score in self.scores: - if isinstance(score, (str, openmc.CrossScore)): + if isinstance(score, (str, CrossScore)): scores.append(str(score)) - elif isinstance(score, openmc.AggregateScore): + elif isinstance(score, AggregateScore): scores.append(score.name) column_name = f'{score.aggregate_op}(score)' @@ -2059,7 +2076,7 @@ def get_reshaped_data(self, value='mean', expand_dims=False): for i, f in enumerate(self.filters): if expand_dims: # Mesh filter indices are backwards so we need to flip them - if type(f) in {openmc.MeshFilter, openmc.MeshBornFilter}: + if type(f) in {MeshFilter, MeshBornFilter}: fshape = f.shape[::-1] new_shape += fshape idx0, idx1 = i, i + len(fshape) - 1 @@ -2246,7 +2263,7 @@ def hybrid_product(self, other, binary_op, filter_product=None, else: all_filters = [self_copy.filters, other_copy.filters] for self_filter, other_filter in product(*all_filters): - new_filter = openmc.CrossFilter(self_filter, other_filter, + new_filter = CrossFilter(self_filter, other_filter, binary_op) new_tally.filters.append(new_filter) @@ -2257,7 +2274,7 @@ def hybrid_product(self, other, binary_op, filter_product=None, else: all_nuclides = [self_copy.nuclides, other_copy.nuclides] for self_nuclide, other_nuclide in product(*all_nuclides): - new_nuclide = openmc.CrossNuclide(self_nuclide, other_nuclide, + new_nuclide = CrossNuclide(self_nuclide, other_nuclide, binary_op) new_tally.nuclides.append(new_nuclide) @@ -2268,9 +2285,9 @@ def cross_score(score1, score2, binary_op): if score1 == score2: return score1 else: - return openmc.CrossScore(score1, score2, binary_op) + return CrossScore(score1, score2, binary_op) else: - return openmc.CrossScore(score1, score2, binary_op) + return CrossScore(score1, score2, binary_op) # Add scores to the new tally if score_product == 'entrywise': @@ -2479,16 +2496,16 @@ def _swap_filters(self, filter1, filter2): # Construct lists of tuples for the bins in each of the two filters filters = [type(filter1), type(filter2)] - if isinstance(filter1, openmc.DistribcellFilter): + if isinstance(filter1, DistribcellFilter): filter1_bins = [b for b in range(filter1.num_bins)] - elif isinstance(filter1, openmc.EnergyFunctionFilter): + elif isinstance(filter1, EnergyFunctionFilter): filter1_bins = [None] else: filter1_bins = filter1.bins - if isinstance(filter2, openmc.DistribcellFilter): + if isinstance(filter2, DistribcellFilter): filter2_bins = [b for b in range(filter2.num_bins)] - elif isinstance(filter2, openmc.EnergyFunctionFilter): + elif isinstance(filter2, EnergyFunctionFilter): filter2_bins = [None] else: filter2_bins = filter2.bins @@ -2621,11 +2638,11 @@ def _swap_scores(self, score1, score2): raise ValueError(msg) # Check that the scores are valid - if not isinstance(score1, (str, openmc.CrossScore)): + if not isinstance(score1, (str, CrossScore)): msg = 'Unable to swap score1 "{}" in Tally ID="{}" since it is ' \ 'not a string or CrossScore'.format(score1, self.id) raise ValueError(msg) - elif not isinstance(score2, (str, openmc.CrossScore)): + elif not isinstance(score2, (str, CrossScore)): msg = 'Unable to swap score2 "{}" in Tally ID="{}" since it is ' \ 'not a string or CrossScore'.format(score2, self.id) raise ValueError(msg) @@ -3269,7 +3286,7 @@ def get_slice(self, scores=[], filters=[], filter_bins=[], nuclides=[], new_filter.bins = [f.bins[i] for i in bin_indices] # Set number of bins manually for mesh/distribcell filters - if filter_type is openmc.DistribcellFilter: + if filter_type is DistribcellFilter: new_filter._num_bins = f._num_bins # Replace existing filter with new one @@ -3335,16 +3352,16 @@ def summation(self, scores=[], filter_type=None, std_dev = self.get_reshaped_data(value='std_dev') # Sum across any filter bins specified by the user - if isinstance(filter_type, openmc.FilterMeta): + if isinstance(filter_type, FilterMeta): find_filter = self.find_filter(filter_type) # If user did not specify filter bins, sum across all bins if len(filter_bins) == 0: bin_indices = np.arange(find_filter.num_bins) - if isinstance(find_filter, openmc.DistribcellFilter): + if isinstance(find_filter, DistribcellFilter): filter_bins = np.arange(find_filter.num_bins) - elif isinstance(find_filter, openmc.EnergyFunctionFilter): + elif isinstance(find_filter, EnergyFunctionFilter): filter_bins = [None] else: filter_bins = find_filter.bins @@ -3373,7 +3390,7 @@ def summation(self, scores=[], filter_type=None, # Add AggregateFilter to the tally sum if not remove_filter: - filter_sum = openmc.AggregateFilter(self_filter, + filter_sum = AggregateFilter(self_filter, [tuple(filter_bins)], 'sum') tally_sum.filters.append(filter_sum) @@ -3396,7 +3413,7 @@ def summation(self, scores=[], filter_type=None, std_dev = np.sqrt(std_dev) # Add AggregateNuclide to the tally sum - nuclide_sum = openmc.AggregateNuclide(nuclides, 'sum') + nuclide_sum = AggregateNuclide(nuclides, 'sum') tally_sum.nuclides.append(nuclide_sum) # Add a copy of this tally's nuclides to the tally sum @@ -3414,7 +3431,7 @@ def summation(self, scores=[], filter_type=None, std_dev = np.sqrt(std_dev) # Add AggregateScore to the tally sum - score_sum = openmc.AggregateScore(scores, 'sum') + score_sum = AggregateScore(scores, 'sum') tally_sum.scores.append(score_sum) # Add a copy of this tally's scores to the tally sum @@ -3487,16 +3504,16 @@ def average(self, scores=[], filter_type=None, std_dev = self.get_reshaped_data(value='std_dev') # Average across any filter bins specified by the user - if isinstance(filter_type, openmc.FilterMeta): + if isinstance(filter_type, FilterMeta): find_filter = self.find_filter(filter_type) # If user did not specify filter bins, average across all bins if len(filter_bins) == 0: bin_indices = np.arange(find_filter.num_bins) - if isinstance(find_filter, openmc.DistribcellFilter): + if isinstance(find_filter, DistribcellFilter): filter_bins = np.arange(find_filter.num_bins) - elif isinstance(find_filter, openmc.EnergyFunctionFilter): + elif isinstance(find_filter, EnergyFunctionFilter): filter_bins = [None] else: filter_bins = find_filter.bins @@ -3526,7 +3543,7 @@ def average(self, scores=[], filter_type=None, # Add AggregateFilter to the tally avg if not remove_filter: - filter_sum = openmc.AggregateFilter(self_filter, + filter_sum = AggregateFilter(self_filter, [tuple(filter_bins)], 'avg') tally_avg.filters.append(filter_sum) @@ -3550,7 +3567,7 @@ def average(self, scores=[], filter_type=None, std_dev = np.sqrt(std_dev) # Add AggregateNuclide to the tally avg - nuclide_avg = openmc.AggregateNuclide(nuclides, 'avg') + nuclide_avg = AggregateNuclide(nuclides, 'avg') tally_avg.nuclides.append(nuclide_avg) # Add a copy of this tally's nuclides to the tally avg @@ -3569,7 +3586,7 @@ def average(self, scores=[], filter_type=None, std_dev = np.sqrt(std_dev) # Add AggregateScore to the tally avg - score_sum = openmc.AggregateScore(scores, 'avg') + score_sum = AggregateScore(scores, 'avg') tally_avg.scores.append(score_sum) # Add a copy of this tally's scores to the tally avg @@ -3759,7 +3776,7 @@ def _create_mesh_subelements(self, root_element, memo=None): already_written = memo if memo else set() for tally in self: for f in tally.filters: - if isinstance(f, openmc.MeshFilter): + if isinstance(f, MeshFilter): if f.mesh.id in already_written: continue if len(f.mesh.name) > 0: @@ -3854,7 +3871,7 @@ def from_xml_element(cls, elem, meshes=None): # Read filter elements filters = {} for e in elem.findall('filter'): - filter = openmc.Filter.from_xml_element(e, meshes=meshes) + filter = Filter.from_xml_element(e, meshes=meshes) filters[filter.id] = filter # Read derivative elements diff --git a/openmc/weight_windows.py b/openmc/weight_windows.py index 5d52a579a11..221fa718217 100644 --- a/openmc/weight_windows.py +++ b/openmc/weight_windows.py @@ -12,6 +12,7 @@ import openmc from openmc.filter import _PARTICLES from openmc.mesh import MeshBase, RectilinearMesh, CylindricalMesh, SphericalMesh, UnstructuredMesh +from openmc.tallies import Tallies import openmc.checkvalue as cv from openmc.checkvalue import PathLike from ._xml import get_elem_list, get_text, clean_indentation @@ -496,8 +497,10 @@ class WeightWindowGenerator: maximum and minimum energy for the data available at runtime. particle_type : {'neutron', 'photon'} Particle type the weight windows apply to - method : {'magic', 'fw_cadis'} + method : {'magic', 'fw_cadis', 'cadis'} The weight window generation methodology applied during an update. + targets : :class:`openmc.Tallies` + Target tallies for local variance reduction via CADIS. max_realizations : int The upper limit for number of tally realizations when generating weight windows. @@ -515,8 +518,10 @@ class WeightWindowGenerator: energies in [eV] for a single bin particle_type : {'neutron', 'photon'} Particle type the weight windows apply to - method : {'magic', 'fw_cadis'} + method : {'magic', 'fw_cadis', 'cadis'} The weight window generation methodology applied during an update. + targets : :class:`openmc.Tallies` + Target tallies for local variance reduction via CADIS. max_realizations : int The upper limit for number of tally realizations when generating weight windows. @@ -528,7 +533,7 @@ class WeightWindowGenerator: Whether or not to apply weight windows on the fly. """ - _MAGIC_PARAMS = {'value': str, 'threshold': float, 'ratio': float} + _WWG_PARAMS = {'value': str, 'threshold': float, 'ratio': float} def __init__( self, @@ -536,6 +541,7 @@ def __init__( energy_bounds: Sequence[float] | None = None, particle_type: str = 'neutron', method: str = 'magic', + targets: openmc.Tallies | list[int] | None = None, max_realizations: int = 1, update_interval: int = 1, on_the_fly: bool = True @@ -548,6 +554,7 @@ def __init__( self.energy_bounds = energy_bounds self.particle_type = particle_type self.method = method + self.targets = targets self.max_realizations = max_realizations self.update_interval = update_interval self.on_the_fly = on_the_fly @@ -601,13 +608,33 @@ def method(self) -> str: @method.setter def method(self, m: str): cv.check_type('generation method', m, str) - cv.check_value('generation method', m, ('magic', 'fw_cadis')) + cv.check_value('generation method', m, ('magic', 'fw_cadis', 'cadis')) self._method = m if self._update_parameters is not None: try: self._check_update_parameters() except (TypeError, KeyError): warnings.warn(f'Update parameters are invalid for the "{m}" method.') + + @property + def targets(self) -> openmc.Tallies: + return self._targets + + @targets.setter + def targets(self, t): + if t is None: + self._targets = t + else: + cv.check_type('CADIS target tallies', t, [openmc.Tallies, list]) + cv.check_greater_than('CADIS target tallies', len(t), 0) + if isinstance(t, list): + for tally_id in t: + if not isinstance(tally_id, int): + raise TypeError( + "Tally IDs passed to WeightWindowGenerator " \ + "must be of type int") + + self._targets = t @property def max_realizations(self) -> int: @@ -634,14 +661,14 @@ def update_parameters(self) -> dict: return self._update_parameters def _check_update_parameters(self, params: dict): - if self.method == 'magic' or self.method == 'fw_cadis': - check_params = self._MAGIC_PARAMS + if self.method == 'magic' or self.method == 'fw_cadis' or self.method == 'cadis': + check_params = self._WWG_PARAMS for key, val in params.items(): if key not in check_params: raise ValueError(f'Invalid param "{key}" for {self.method} ' 'weight window generation') - cv.check_type(f'weight window generation param: "{key}"', val, self._MAGIC_PARAMS[key]) + cv.check_type(f'weight window generation param: "{key}"', val, self._WWG_PARAMS[key]) @update_parameters.setter def update_parameters(self, params: dict): @@ -677,8 +704,8 @@ def _sanitize_update_parameters(cls, method: str, update_parameters: dict): update_parameters : dict The update parameters as-read from the XML node (keys: str, values: str) """ - if method == 'magic' or method == 'fw_cadis': - check_params = cls._MAGIC_PARAMS + if method == 'magic' or method == 'fw_cadis' or method == 'cadis': + check_params = cls._WWG_PARAMS for param, param_type in check_params.items(): if param in update_parameters: @@ -704,6 +731,20 @@ def to_xml_element(self): otf_elem.text = str(self.on_the_fly).lower() method_elem = ET.SubElement(element, 'method') method_elem.text = self.method + if self.targets is not None: + if self.method != 'cadis': + raise ValueError( + "CADIS update method is required in order to use " \ + "target tallies for WeightWindowGenerator.") + elif isinstance(self.targets, openmc.Tallies): + raise RuntimeError( + "CADIS target tallies must be checked to ensure they are" \ + "present on model.tallies. Use model.export_to_xml() or " \ + "model.export_to_model_xml() to link CADIS target tallies.") + else: + targets_elem = ET.SubElement(element, 'targets') + targets_elem.text = ' '.join(str(tally_id) for tally_id in self.targets) + if self.update_parameters is not None: self._update_parameters_subelement(element) @@ -731,7 +772,7 @@ def from_xml_element(cls, elem: ET.Element, meshes: dict) -> Self: mesh_id = int(get_text(elem, 'mesh')) mesh = meshes[mesh_id] - energy_bounds = get_elem_list(elem, "energy_bounds, float") + energy_bounds = get_elem_list(elem, "energy_bounds", float) particle_type = get_text(elem, 'particle_type') wwg = cls(mesh, energy_bounds, particle_type) @@ -740,6 +781,14 @@ def from_xml_element(cls, elem: ET.Element, meshes: dict) -> Self: wwg.update_interval = int(get_text(elem, 'update_interval')) wwg.on_the_fly = bool(get_text(elem, 'on_the_fly')) wwg.method = get_text(elem, 'method') + targets_elem = elem.find('targets') + if targets_elem is not None: + if wwg.method != 'cadis': + raise ValueError( + "CADIS update method is required in order to use " \ + "target tallies for WeightWindowGenerator.") + else: + wwg.targets = get_elem_list(elem, "targets") if elem.find('update_parameters') is not None: update_parameters = {} diff --git a/src/random_ray/flat_source_domain.cpp b/src/random_ray/flat_source_domain.cpp index c2effaa5d4a..ab109199791 100644 --- a/src/random_ray/flat_source_domain.cpp +++ b/src/random_ray/flat_source_domain.cpp @@ -30,9 +30,11 @@ RandomRayVolumeEstimator FlatSourceDomain::volume_estimator_ { RandomRayVolumeEstimator::HYBRID}; bool FlatSourceDomain::volume_normalized_flux_tallies_ {false}; bool FlatSourceDomain::adjoint_ {false}; +bool FlatSourceDomain::cadis_ {false}; double FlatSourceDomain::diagonal_stabilization_rho_ {1.0}; std::unordered_map>> FlatSourceDomain::mesh_domain_map_; +std::vector FlatSourceDomain::cadis_targets_; FlatSourceDomain::FlatSourceDomain() : negroups_(data::mg.num_energy_groups_) { @@ -1053,13 +1055,17 @@ void FlatSourceDomain::count_external_source_regions() } } -void FlatSourceDomain::convert_external_sources() +void FlatSourceDomain::convert_external_sources(bool use_adjoint_sources) { + // Determine whether forward or (local) adjoint sources are desired + const auto& sources = use_adjoint_sources ? + model::adjoint_sources : model::external_sources; + // Loop over external sources - for (int es = 0; es < model::external_sources.size(); es++) { + for (int es = 0; es < sources.size(); es++) { // Extract source information - Source* s = model::external_sources[es].get(); + Source* s = sources[es].get(); IndependentSource* is = dynamic_cast(s); Discrete* energy = dynamic_cast(is->energy()); const std::unordered_set& domain_ids = is->domain_ids(); @@ -1198,7 +1204,7 @@ void FlatSourceDomain::flatten_xs() } } -void FlatSourceDomain::set_adjoint_sources() +void FlatSourceDomain::set_fw_adjoint_sources() { // Set the adjoint external source to 1/forward_flux. If the forward flux is // negative, zero, or extremely close to zero, set the adjoint source to zero, @@ -1227,6 +1233,10 @@ void FlatSourceDomain::set_adjoint_sources() source_regions_.external_source(sr, g) = 0.0; } else { source_regions_.external_source(sr, g) = 1.0 / flux; + if (!std::isfinite(source_regions_.external_source(sr, g))) { + // If the flux is NaN or Inf, set the adjoint source to zero + source_regions_.external_source(sr, g) = 0.0; + } } if (flux > 0.0) { source_regions_.external_source_present(sr) = 1; @@ -1249,29 +1259,133 @@ void FlatSourceDomain::set_adjoint_sources() // set its adjoint source to zero. This adds negligible bias to the adjoint // flux solution, as the true total adjoint source contribution from small // regions is likely to be negligible. + if (!cadis_) { #pragma omp parallel for - for (int64_t sr = 0; sr < n_source_regions(); sr++) { - if (source_regions_.is_small(sr)) { - for (int g = 0; g < negroups_; g++) { - source_regions_.external_source(sr, g) = 0.0; + for (int64_t sr = 0; sr < n_source_regions(); sr++) { + if (source_regions_.is_small(sr)) { + for (int g = 0; g < negroups_; g++) { + source_regions_.external_source(sr, g) = 0.0; + } + source_regions_.external_source_present(sr) = 0; } - source_regions_.external_source_present(sr) = 0; } - } - // Divide the fixed source term by sigma t (to save time when applying each - // iteration) + + // Divide the fixed source term by sigma t (to save time when applying each + // iteration) #pragma omp parallel for - for (int64_t sr = 0; sr < n_source_regions(); sr++) { - int material = source_regions_.material(sr); - if (material == MATERIAL_VOID) { - continue; - } - for (int g = 0; g < negroups_; g++) { - double sigma_t = - sigma_t_[material * negroups_ + g] * source_regions_.density_mult(sr); - source_regions_.external_source(sr, g) /= sigma_t; + for (int64_t sr = 0; sr < n_source_regions(); sr++) { + int material = source_regions_.material(sr); + if (material == MATERIAL_VOID) { + continue; + } + for (int g = 0; g < negroups_; g++) { + double sigma_t = + sigma_t_[material * negroups_ + g] * source_regions_.density_mult(sr); + source_regions_.external_source(sr, g) /= sigma_t; + if (!std::isfinite(source_regions_.external_source(sr, g))) { + // If the flux is NaN or Inf, set the adjoint source to zero + source_regions_.external_source(sr, g) = 0.0; + } + } } } + + if (cadis_) { +// Only external sources that have a non-mesh type tally task should remain +// non-zero. Everything else gets zero'd out. +#pragma omp parallel for + for (int64_t sr = 0; sr < n_source_regions(); sr++) { + + // If there is already no external source, don't need to do anything + if (source_regions_.external_source_present(sr) == 0) { + continue; + } + + // If there is an adjoint source term here, then we need to check it. + + // We will track if ANY group has a valid CADIS source term + bool has_any_sources = false; + + // Now, loop over groups + for (int g = 0; g < negroups_; g++) { + + // If there are no tally tasks associated with this source element + // then it is not a CADIS source, so we continue to the next group + if (source_regions_.tally_task(sr, g).empty()) { + source_regions_.external_source(sr, g) = 0.0; + continue; + } + + // If there are tally tasks, we can through them and check if + // any of them are CADIS targets and have a non-mesh filter type. + + // We track if ANY of the tasks are CADIS target tallies + bool cadis_target_region = false; + + // Now we loop through + for (const auto& task : source_regions_.tally_task(sr, g)) { + Tally& tally {*model::tallies[task.tally_idx]}; + const auto t_id = tally.id(); + + // Skip non-target tallies + if (std::find(cadis_targets_.begin(), + cadis_targets_.end(), + t_id) == cadis_targets_.end()) { + continue; + } + + auto filter_types = tally.filter_types(); + + // For each tally, we loop through the filter types array. + // If any of them have a CADIS-compatible filter type, + // then this source element is a valid CADIS source + for (const auto& filter_type : filter_types) { + if (filter_type == FilterType::CELL || + filter_type == FilterType::CELL_INSTANCE || + filter_type == FilterType::DISTRIBCELL || + filter_type == FilterType::UNIVERSE || + filter_type == FilterType::MATERIAL) { + cadis_target_region = true; + break; + } + } + // If a target tally doesn't have any compatible filters, error + if (!cadis_target_region) { + fatal_error("CADIS target tally with ID " + + std::to_string(t_id) + " does not have any " + "CADIS-compatible filters."); + } + } + + // If ANY of the tasks is a CADIS target, + // Then we keep the source term and set that this + // source region has a valid CADIS source term. + // Otherwise, we zero out the source term. + if (cadis_target_region) { + has_any_sources = true; + // print external source term + fmt::print("External source term for source region {} group {}: {}\n", + sr, g, source_regions_.external_source(sr, g)); + } else { + source_regions_.external_source(sr, g) = 0.0; + } + } // End loop over groups + + // If there were any valid CADIS source terms for any + // of the groups, then the SR as a whole counts as a source + if (has_any_sources) { + source_regions_.external_source_present(sr) = 1; + } else { + source_regions_.external_source_present(sr) = 0; + } + } // End loop over source regions + } // End CADIS logic +} + +void FlatSourceDomain::set_local_adjoint_sources() +{ + // Set the external source to user-specified adjoint sources. + convert_external_sources(true); } void FlatSourceDomain::transpose_scattering_matrix() diff --git a/src/random_ray/random_ray_simulation.cpp b/src/random_ray/random_ray_simulation.cpp index 7bab3a9b1b6..f38e5e9065c 100644 --- a/src/random_ray/random_ray_simulation.cpp +++ b/src/random_ray/random_ray_simulation.cpp @@ -28,12 +28,25 @@ void openmc_run_random_ray() // Run forward simulation ////////////////////////////////////////////////////////// - if (mpi::master) { - if (FlatSourceDomain::adjoint_) { - FlatSourceDomain::adjoint_ = false; - openmc::print_adjoint_header(); - FlatSourceDomain::adjoint_ = true; - } + // Check if adjoint calculation is needed, and if local adjoint source(s) + // are present. If an adjoint calculation is needed and no sources are + // specified, we will run a forward calculation first to calculate adjoint + // sources for global variance reduction, then perform an adjoint + // calculation later. + bool adjoint_needed = FlatSourceDomain::adjoint_; + bool fw_adjoint = model::adjoint_sources.empty() && adjoint_needed; + + // If we're going to do an adjoint simulation with forward-weighted adjoint + // sources afterwards, report that this is the initial forward flux solve. + if (!adjoint_needed || fw_adjoint) { + // Configure the domain for forward simulation + FlatSourceDomain::adjoint_ = false; + + if (adjoint_needed && mpi::master) + header("FORWARD FLUX SOLVE", 3); + } else { + // Configure domain for adjoint simulation (later) + FlatSourceDomain::adjoint_ = true; } // Initialize OpenMC general data structures @@ -46,23 +59,86 @@ void openmc_run_random_ray() // Initialize Random Ray Simulation Object RandomRaySimulation sim; - // Initialize fixed sources, if present - sim.apply_fixed_sources_and_mesh_domains(); + if (!adjoint_needed || fw_adjoint) { + // Initialize fixed sources, if present + sim.apply_fixed_sources_and_mesh_domains(); - // Run initial random ray simulation - sim.simulate(); + // Begin main simulation timer + simulation::time_total.start(); + + // Execute random ray simulation + sim.simulate(); + + // End main simulation timer + simulation::time_total.stop(); + + // Normalize and save the final forward flux + double source_normalization_factor = + sim.domain()->compute_fixed_source_normalization_factor() / + (settings::n_batches - settings::n_inactive); + +#pragma omp parallel for + for (uint64_t se = 0; se < sim.domain()->n_source_elements(); se++) { + sim.domain()->source_regions_.scalar_flux_final(se) *= + source_normalization_factor; + } + + // Finalize OpenMC + openmc_simulation_finalize(); + + // Output all simulation results + sim.output_simulation_results(); + } ////////////////////////////////////////////////////////// // Run adjoint simulation (if enabled) ////////////////////////////////////////////////////////// - if (sim.adjoint_needed_) { - // Setup for adjoint simulation - sim.prepare_adjoint_simulation(); + if (!adjoint_needed) { + return; + } - // Run adjoint simulation - sim.simulate(); + reset_timers(); + + if (mpi::master) + header("ADJOINT FLUX SOLVE", 3); + + if (fw_adjoint) { + // Forward simulation has already been run; + // Configure the domain for adjoint simulation and + // re-initialize OpenMC general data structures + FlatSourceDomain::adjoint_ = true; + + openmc_simulation_init(); + + sim.prepare_fw_fixed_sources_adjoint(); + } else { + // Initialize adjoint fixed sources + sim.prepare_local_fixed_sources_adjoint(); } + + sim.domain()->k_eff_ = 1.0; + + // Transpose scattering matrix + sim.domain()->transpose_scattering_matrix(); + + // Swap nu_sigma_f and chi + sim.domain()->nu_sigma_f_.swap(sim.domain()->chi_); + + // Begin main simulation timer + simulation::time_total.start(); + + // Execute random ray simulation + sim.simulate(); + + // End main simulation timer + simulation::time_total.stop(); + + // Finalize OpenMC + openmc_simulation_finalize(); + + // Output all simulation results + sim.output_simulation_results(); } // Enforces restrictions on inputs in random ray mode. While there are @@ -83,12 +159,11 @@ void validate_random_ray_inputs() case SCORE_FISSION: case SCORE_NU_FISSION: case SCORE_EVENTS: - case SCORE_KAPPA_FISSION: break; default: fatal_error( - "Invalid score specified. Only flux, total, fission, nu-fission, " - "kappa-fission, and event scores are supported in random ray mode."); + "Invalid score specified. Only flux, total, fission, nu-fission, and " + "event scores are supported in random ray mode."); } } @@ -278,8 +353,8 @@ void validate_random_ray_inputs() warning( "Linear sources may result in negative fluxes in small source regions " "generated by mesh subdivision. Negative sources may result in low " - "quality FW-CADIS weight windows. We recommend you use flat source mode " - "when generating weight windows with an overlaid mesh tally."); + "quality (FW-)CADIS weight windows. We recommend you use flat source " + "mode when generating weight windows with an overlaid mesh tally."); } } @@ -294,17 +369,6 @@ void openmc_reset_random_ray() RandomRay::sample_method_ = RandomRaySampleMethod::PRNG; } -void print_adjoint_header() -{ - if (!FlatSourceDomain::adjoint_) - // If we're going to do an adjoint simulation afterwards, report that this - // is the initial forward flux solve. - header("FORWARD FLUX SOLVE", 3); - else - // Otherwise report that we are doing the adjoint simulation - header("ADJOINT FLUX SOLVE", 3); -} - //============================================================================== // RandomRaySimulation implementation //============================================================================== @@ -335,16 +399,6 @@ RandomRaySimulation::RandomRaySimulation() // Convert OpenMC native MGXS into a more efficient format // internal to the random ray solver domain_->flatten_xs(); - - // Check if adjoint calculation is needed. If it is, we will run the forward - // calculation first and then the adjoint calculation later. - adjoint_needed_ = FlatSourceDomain::adjoint_; - - // Adjoint is always false for the forward calculation - FlatSourceDomain::adjoint_ = false; - - // The first simulation is run after initialization - is_first_simulation_ = true; } void RandomRaySimulation::apply_fixed_sources_and_mesh_domains() @@ -352,54 +406,29 @@ void RandomRaySimulation::apply_fixed_sources_and_mesh_domains() domain_->apply_meshes(); if (settings::run_mode == RunMode::FIXED_SOURCE) { // Transfer external source user inputs onto random ray source regions - domain_->convert_external_sources(); + domain_->convert_external_sources(false); domain_->count_external_source_regions(); } } -void RandomRaySimulation::prepare_fixed_sources_adjoint() +void RandomRaySimulation::prepare_fw_fixed_sources_adjoint() { + // Prepare adjoint fixed sources using forward flux domain_->source_regions_.adjoint_reset(); if (settings::run_mode == RunMode::FIXED_SOURCE) { - domain_->set_adjoint_sources(); + domain_->set_fw_adjoint_sources(); } } -void RandomRaySimulation::prepare_adjoint_simulation() +void RandomRaySimulation::prepare_local_fixed_sources_adjoint() { - // Configure the domain for adjoint simulation - FlatSourceDomain::adjoint_ = true; - - // Reset k-eff - domain_->k_eff_ = 1.0; - - // Initialize adjoint fixed sources, if present - prepare_fixed_sources_adjoint(); - - // Transpose scattering matrix - domain_->transpose_scattering_matrix(); - - // Swap nu_sigma_f and chi - domain_->nu_sigma_f_.swap(domain_->chi_); + if (settings::run_mode == RunMode::FIXED_SOURCE) { + domain_->set_local_adjoint_sources(); + } } void RandomRaySimulation::simulate() { - if (!is_first_simulation_) { - if (mpi::master && adjoint_needed_) - openmc::print_adjoint_header(); - - // Reset the timers and reinitialize the general OpenMC datastructures if - // this is after the first simulation - reset_timers(); - - // Initialize OpenMC general data structures - openmc_simulation_init(); - } - - // Begin main simulation timer - simulation::time_total.start(); - // Random ray power iteration loop while (simulation::current_batch < settings::n_batches) { // Initialize the current batch @@ -488,31 +517,6 @@ void RandomRaySimulation::simulate() } // End random ray power iteration loop domain_->count_external_source_regions(); - - // End main simulation timer - simulation::time_total.stop(); - - // Normalize and save the final flux - double source_normalization_factor = - domain_->compute_fixed_source_normalization_factor() / - (settings::n_batches - settings::n_inactive); - -#pragma omp parallel for - for (uint64_t se = 0; se < domain_->n_source_elements(); se++) { - domain_->source_regions_.scalar_flux_final(se) *= - source_normalization_factor; - } - - // Finalize OpenMC - openmc_simulation_finalize(); - - // Output all simulation results - output_simulation_results(); - - // Toggle that the simulation object has been initialized after the first - // simulation - if (is_first_simulation_) - is_first_simulation_ = false; } void RandomRaySimulation::output_simulation_results() const diff --git a/src/settings.cpp b/src/settings.cpp index 5b472468fc4..d8fca66df81 100644 --- a/src/settings.cpp +++ b/src/settings.cpp @@ -276,8 +276,9 @@ void get_run_parameters(pugi::xml_node node_base) } else { fatal_error("Specify random ray inactive distance in settings XML"); } - if (check_for_node(random_ray_node, "source")) { - xml_node source_node = random_ray_node.child("source"); + if (check_for_node(random_ray_node, "ray_source")) { + xml_node ray_source_node = random_ray_node.child("ray_source"); + xml_node source_node = ray_source_node.child("source"); // Get point to list of elements and make sure there is at least // one RandomRay::ray_source_ = Source::create(source_node); @@ -363,6 +364,14 @@ void get_run_parameters(pugi::xml_node node_base) "between 0 and 1"); } } + if (check_for_node(random_ray_node, "adjoint_source")) { + for (pugi::xml_node adj_source_node : + random_ray_node.children("adjoint_source")) { + // Find any local adjoint sources + xml_node source_node = adj_source_node.child("source"); + model::adjoint_sources.push_back(Source::create(source_node)); + } + } } } @@ -1249,6 +1258,16 @@ void read_settings_xml(pugi::xml_node root) break; } } + // If any weight window generators have CADIS target tallies, user-defined + // adjoint sources cannot be used at the same time. + if (!model::adjoint_sources.empty()) { + for (const auto& wwg : variance_reduction::weight_windows_generators) { + if (!wwg->targets_.empty()) { + fatal_error("Cannot use both user-defined adjoint sources and CADIS " + "target tallies at the same time."); + } + } + } } // Set up weight window checkpoints diff --git a/src/source.cpp b/src/source.cpp index b30b964d39c..566ac32d29b 100644 --- a/src/source.cpp +++ b/src/source.cpp @@ -45,6 +45,8 @@ namespace model { vector> external_sources; +vector> adjoint_sources; + DiscreteIndex external_sources_probability; } // namespace model diff --git a/src/weight_windows.cpp b/src/weight_windows.cpp index 4838e459152..f60de4c56d5 100644 --- a/src/weight_windows.cpp +++ b/src/weight_windows.cpp @@ -698,7 +698,7 @@ void WeightWindows::update_weights(const Tally* tally, const std::string& value, } } } else { - // For FW-CADIS, weight windows are inversely proportional to the adjoint + // For (FW-)CADIS, weight windows are inversely proportional to the adjoint // fluxes. We normalize the weight windows across all energy groups. #pragma omp parallel for collapse(2) schedule(static) for (int e = 0; e < e_bins; e++) { @@ -876,6 +876,22 @@ WeightWindowsGenerator::WeightWindowsGenerator(pugi::xml_node node) fatal_error("FW-CADIS can only be run in random ray solver mode."); } FlatSourceDomain::adjoint_ = true; + } else if (method_string == "cadis") { + method_ = WeightWindowUpdateMethod::CADIS; + if (settings::solver_type != SolverType::RANDOM_RAY) { + fatal_error("CADIS can only be run in random ray solver mode."); + } + FlatSourceDomain::adjoint_ = true; + FlatSourceDomain::cadis_ = true; + if (check_for_node(node,"targets")) { + targets_ = get_node_array(node, "targets"); + FlatSourceDomain::cadis_targets_.insert( + std::end(FlatSourceDomain::cadis_targets_), std::begin(targets_), + std::end(targets_)); + } else { + fatal_error("CADIS method requires target tallies be specified to " + "WeightWindowGenerator."); + } } else { fatal_error(fmt::format( "Unknown weight window update method '{}' specified", method_string)); diff --git a/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat b/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat index 0adfc548848..94e2709768f 100644 --- a/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat +++ b/tests/regression_tests/random_ray_adjoint_fixed_source/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true true naive diff --git a/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat b/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat index 073348c41e7..755afd6c439 100644 --- a/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat +++ b/tests/regression_tests/random_ray_adjoint_k_eff/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true true diff --git a/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat b/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat index dfef53cd2f9..429067b2212 100644 --- a/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat +++ b/tests/regression_tests/random_ray_adjoint_k_eff/results_true.dat @@ -79,7 +79,7 @@ tally 1: 0.000000E+00 0.000000E+00 0.000000E+00 -9.248400E-01 +9.248399E-01 1.710699E-01 0.000000E+00 0.000000E+00 @@ -148,7 +148,7 @@ tally 1: 9.272977E-01 1.721077E-01 3.161443E-02 -2.000179E-04 +2.000180E-04 2.002789E-07 8.027290E-15 8.778794E-01 diff --git a/tests/regression_tests/random_ray_auto_convert/infinite_medium/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert/infinite_medium/inputs_true.dat index 464c89a5df9..86d5ec4abd5 100644 --- a/tests/regression_tests/random_ray_auto_convert/infinite_medium/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/infinite_medium/inputs_true.dat @@ -41,11 +41,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert/material_wise/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert/material_wise/inputs_true.dat index 464c89a5df9..86d5ec4abd5 100644 --- a/tests/regression_tests/random_ray_auto_convert/material_wise/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/material_wise/inputs_true.dat @@ -41,11 +41,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert/stochastic_slab/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert/stochastic_slab/inputs_true.dat index 464c89a5df9..86d5ec4abd5 100644 --- a/tests/regression_tests/random_ray_auto_convert/stochastic_slab/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert/stochastic_slab/inputs_true.dat @@ -41,11 +41,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat index 80a166c6786..15981f7fa5f 100644 --- a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/model/inputs_true.dat @@ -38,11 +38,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat index 464c89a5df9..86d5ec4abd5 100644 --- a/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/infinite_medium/user/inputs_true.dat @@ -41,11 +41,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat index 80a166c6786..15981f7fa5f 100644 --- a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/model/inputs_true.dat @@ -38,11 +38,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat index 464c89a5df9..2314266563c 100644 --- a/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat +++ b/tests/regression_tests/random_ray_auto_convert_source_energy/stochastic_slab/user/inputs_true.dat @@ -40,12 +40,14 @@ multi-group - - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_diagonal_stabilization/inputs_true.dat b/tests/regression_tests/random_ray_diagonal_stabilization/inputs_true.dat index 47325ebd7d5..11100e88e12 100644 --- a/tests/regression_tests/random_ray_diagonal_stabilization/inputs_true.dat +++ b/tests/regression_tests/random_ray_diagonal_stabilization/inputs_true.dat @@ -41,11 +41,13 @@ multi-group - - - -0.63 -0.63 -1.0 0.63 0.63 1.0 - - + + + + -0.63 -0.63 -1.0 0.63 0.63 1.0 + + + 30.0 150.0 diff --git a/tests/regression_tests/random_ray_entropy/settings.xml b/tests/regression_tests/random_ray_entropy/settings.xml index 81deaa7751d..0d830417b62 100644 --- a/tests/regression_tests/random_ray_entropy/settings.xml +++ b/tests/regression_tests/random_ray_entropy/settings.xml @@ -6,11 +6,13 @@ 5 multi-group - - - 0.0 0.0 0.0 100.0 100.0 100.0 - - + + + + 0.0 0.0 0.0 100.0 100.0 100.0 + + + 40.0 400.0 diff --git a/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat index 9f1987f3acc..d650bbaf95c 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/cell/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat index b4f57dbfa8a..98a51add1f3 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/material/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat index ab91f74e50d..20deba664bd 100644 --- a/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_domain/universe/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat index 220fa7db643..2268d82c391 100644 --- a/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_linear/linear/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear diff --git a/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat index f8c4430852f..fe95baa7bb5 100644 --- a/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_linear/linear_xy/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear_xy diff --git a/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat index c84e544fcc4..a5632ece960 100644 --- a/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_mesh/flat/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat index 05c4846e6b4..9d22603c63c 100644 --- a/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_mesh/linear/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat index 0c870e10067..de941f10fbb 100644 --- a/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_normalization/False/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + false diff --git a/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat index ab91f74e50d..20deba664bd 100644 --- a/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_normalization/True/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat index 0c05a71df32..943468a1095 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/flat/inputs_true.dat @@ -110,11 +110,13 @@ 40.0 40.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + false flat diff --git a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat index a67495bf169..650953c4b06 100644 --- a/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_fixed_source_subcritical/linear_xy/inputs_true.dat @@ -110,11 +110,13 @@ 40.0 40.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + false linear_xy diff --git a/tests/regression_tests/random_ray_halton_samples/inputs_true.dat b/tests/regression_tests/random_ray_halton_samples/inputs_true.dat index 36d5f6f2276..1b86d2daeea 100644 --- a/tests/regression_tests/random_ray_halton_samples/inputs_true.dat +++ b/tests/regression_tests/random_ray_halton_samples/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true halton diff --git a/tests/regression_tests/random_ray_halton_samples/results_true.dat b/tests/regression_tests/random_ray_halton_samples/results_true.dat index 256f8a744a3..5f39ebaeb19 100644 --- a/tests/regression_tests/random_ray_halton_samples/results_true.dat +++ b/tests/regression_tests/random_ray_halton_samples/results_true.dat @@ -24,7 +24,7 @@ tally 1: 1.707007E-02 5.933921E-05 4.154514E-02 -3.514889E-04 +3.514888E-04 1.513147E+00 4.652938E-01 1.810962E-02 @@ -34,7 +34,7 @@ tally 1: 4.347893E+00 3.798064E+00 6.851785E-03 -9.430195E-06 +9.430194E-06 1.695426E-02 5.773923E-05 2.809071E+00 @@ -152,7 +152,7 @@ tally 1: 4.036663E-02 3.323832E-04 1.516801E+00 -4.675245E-01 +4.675244E-01 1.752096E-02 6.241641E-05 4.264304E-02 diff --git a/tests/regression_tests/random_ray_k_eff/inputs_true.dat b/tests/regression_tests/random_ray_k_eff/inputs_true.dat index 545bd1d4578..72b783344fd 100644 --- a/tests/regression_tests/random_ray_k_eff/inputs_true.dat +++ b/tests/regression_tests/random_ray_k_eff/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true diff --git a/tests/regression_tests/random_ray_k_eff/results_true.dat b/tests/regression_tests/random_ray_k_eff/results_true.dat index ace18df8cce..4e0c31988d7 100644 --- a/tests/regression_tests/random_ray_k_eff/results_true.dat +++ b/tests/regression_tests/random_ray_k_eff/results_true.dat @@ -1,5 +1,5 @@ k-combined: -8.400321E-01 8.023357E-03 +8.400321E-01 8.023358E-03 tally 1: 1.075769E+00 2.317354E-01 @@ -28,7 +28,7 @@ tally 1: 1.509054E+00 4.629325E-01 1.749679E-02 -6.226587E-05 +6.226588E-05 4.258421E-02 3.688336E-04 4.322054E+00 @@ -131,7 +131,7 @@ tally 1: 2.304093E-01 4.053505E-01 3.291277E-02 -9.865420E-01 +9.865421E-01 1.949549E-01 6.047420E-01 7.327008E-02 diff --git a/tests/regression_tests/random_ray_k_eff_mesh/inputs_true.dat b/tests/regression_tests/random_ray_k_eff_mesh/inputs_true.dat index 98badea18d8..f6e9c8e3e71 100644 --- a/tests/regression_tests/random_ray_k_eff_mesh/inputs_true.dat +++ b/tests/regression_tests/random_ray_k_eff_mesh/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true diff --git a/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat b/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat index 2ae8fad85fb..2976d169b63 100644 --- a/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat +++ b/tests/regression_tests/random_ray_k_eff_mesh/results_true.dat @@ -1,5 +1,5 @@ k-combined: -8.379203E-01 8.057199E-03 +8.379203E-01 8.057198E-03 tally 1: 1.073897E+00 2.309328E-01 diff --git a/tests/regression_tests/random_ray_linear/linear/inputs_true.dat b/tests/regression_tests/random_ray_linear/linear/inputs_true.dat index a43a66e71c7..269d9892ebf 100644 --- a/tests/regression_tests/random_ray_linear/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_linear/linear/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true linear diff --git a/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat b/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat index 7f76f2fd1c1..217e9551614 100644 --- a/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat +++ b/tests/regression_tests/random_ray_linear/linear_xy/inputs_true.dat @@ -80,11 +80,13 @@ 100.0 20.0 - - - -1.26 -1.26 -1 1.26 1.26 1 - - + + + + -1.26 -1.26 -1 1.26 1.26 1 + + + true linear_xy diff --git a/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat b/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat index 052608b4254..e00538f64c6 100644 --- a/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat +++ b/tests/regression_tests/random_ray_linear/linear_xy/results_true.dat @@ -90,7 +90,7 @@ tally 1: 1.746692E+00 1.536860E-01 4.251098E+00 -9.103405E-01 +9.103406E-01 3.651202E+00 6.682179E-01 5.431675E-01 diff --git a/tests/regression_tests/random_ray_low_density/inputs_true.dat b/tests/regression_tests/random_ray_low_density/inputs_true.dat index ab91f74e50d..20deba664bd 100644 --- a/tests/regression_tests/random_ray_low_density/inputs_true.dat +++ b/tests/regression_tests/random_ray_low_density/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat b/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat index 088f803bfa8..b4bd263f5ac 100644 --- a/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat +++ b/tests/regression_tests/random_ray_point_source_locator/inputs_true.dat @@ -206,11 +206,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/random_ray_void/flat/inputs_true.dat b/tests/regression_tests/random_ray_void/flat/inputs_true.dat index aa28e7b68bf..66390c76661 100644 --- a/tests/regression_tests/random_ray_void/flat/inputs_true.dat +++ b/tests/regression_tests/random_ray_void/flat/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true flat diff --git a/tests/regression_tests/random_ray_void/linear/inputs_true.dat b/tests/regression_tests/random_ray_void/linear/inputs_true.dat index e4b2f22fa27..45228a03955 100644 --- a/tests/regression_tests/random_ray_void/linear/inputs_true.dat +++ b/tests/regression_tests/random_ray_void/linear/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear diff --git a/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat index 8e8a8ed9b81..4d1af46b121 100644 --- a/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/hybrid/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true hybrid diff --git a/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat index 1e25b97da66..a268d55d04a 100644 --- a/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/naive/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true naive diff --git a/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat index 78c16269763..777ccaea510 100644 --- a/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator/simulation_averaged/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true simulation_averaged diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat index 47a8a718249..dd11567f69d 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/hybrid/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear hybrid diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat index 80a9ada4d5b..6933fba435e 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/naive/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear naive diff --git a/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat b/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat index 4f032a62a82..3ccab1d21b7 100644 --- a/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat +++ b/tests/regression_tests/random_ray_volume_estimator_linear/simulation_averaged/inputs_true.dat @@ -207,11 +207,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true linear simulation_averaged diff --git a/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat index 5fa6505ddf4..6bdabfbee31 100644 --- a/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis/inputs_true.dat @@ -222,11 +222,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true naive diff --git a/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat index ceb89e6e34c..a0d84257a8d 100644 --- a/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis_mesh/flat/inputs_true.dat @@ -222,11 +222,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true diff --git a/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat b/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat index c7691e950c4..62f8478586b 100644 --- a/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat +++ b/tests/regression_tests/weightwindows_fw_cadis_mesh/linear/inputs_true.dat @@ -222,11 +222,13 @@ 500.0 100.0 - - - 0.0 0.0 0.0 30.0 30.0 30.0 - - + + + + 0.0 0.0 0.0 30.0 30.0 30.0 + + + true