bluemira.codes.openmc.output

Functions to present the results prettily (Including both printed/logged texts and images)

Classes

`OpenMCResultBase`	Base class for openmc results
`OpenMCCSGResult`	Class that looks opens up the openmc universe from the statepoint file,
`OpenMCDAGMCResult`	Open up the openmc universe from the statepoint file,
`NeutronicsOutputParams`	Neutronics output parameters

Functions

`_get_std_dev_iloc`(df)
`_get_std_dev_numpy`(df)
`get_percent_err`(row)	Calculate a percentage error to the required row,

Module Contents

bluemira.codes.openmc.output._get_std_dev_iloc(df)

bluemira.codes.openmc.output._get_std_dev_numpy(df)

bluemira.codes.openmc.output.get_percent_err(row)

Calculate a percentage error to the required row, assuming cells had been filled out.

Parameters:

row (pd.Series object) – It should have the “mean” and “std. dev.” row[‘mean’]: float row[‘std. dev.’]: float

Returns:

fractional_error (float)
Usage
—–
dataframe.apply(get_percent_err),
where dataframe must have one row named “std. dev.” and another named “mean”.

class bluemira.codes.openmc.output.OpenMCResultBase

Base class for openmc results

static _load_dataframe_from_statepoint(statepoint: openmc.StatePoint, tally_name: str) → pandas.DataFrame

Parameters:

statepoint (openmc.StatePoint)
tally_name (str)

Return type:

pandas.DataFrame

static _convert_dict_contents(dataset: dict[str, dict[int, list[str | float]]])

Parameters:: dataset (dict[str, dict[int, list[str | float]]])

static dt_neuton_power(src_triton_rate): Calculate dt neutron power

static energy_multiplication(dt_neutron_power, total_power): Calculate energy multiplication

static multiplication_power(energy_multiplication, dt_neutron_power): Calculate multiplication power

classmethod _load_filter_power_err(statepoint, src_rate: float, filter_name: str) → tuple[float, float]

Power is initially loaded as eV/source particle. To convert to Watt, we need the source particle rate.

Parameters:

filter_name (str) – the literal name that was used in tallying.py to refer to this tally.
src_rate (float) – source particle rate.

Returns:

power – The total power [W].
errors – The absolute error on the total power [W]. RMS of errors from each cell.

Return type:

tuple[float, float]

classmethod _load_tbr(statepoint, source_rate: float, source_triton_rate: float)

Load the TBR value and uncertainty.

Returns:

mean – average TBR, i.e. average (n,Xt) per source particle.
error – absolute error, but since the table is only 1 row long, we can turn the array into a float by .sum().

Parameters:

source_rate (float)
source_triton_rate (float)

class bluemira.codes.openmc.output.OpenMCCSGResult

Bases: OpenMCResultBase

Class that looks opens up the openmc universe from the statepoint file,: so that the dataframes containing the relevant results can be generated and reformatted by its methods.

tbr: float

tbr_err: float

e_mult: float

e_mult_err: float

heating: dict

blanket_power: float

blanket_power_err: float

divertor_power: float

divertor_power_err: float

vessel_power: float

vessel_power_err: float

total_power: float

total_power_err: float

mult_power: float

peak_bb_fe_damage: float

peak_bb_fe_damage_err: float

fluxes: dict

damage: dict

photon_heat_flux: dict: Photon heat flux

universe: openmc.Universe

cell_arrays: bluemira.codes.openmc.make_csg.CellStage

src_rate: float

statepoint: openmc.StatePoint

statepoint_file: str

cell_names: dict

cell_vols: dict

mat_names: dict

classmethod from_run(universe: openmc.Universe, cell_arrays: bluemira.codes.openmc.make_csg.CellStage, src_rate: float, src_triton_rate: float, statepoint_file: pathlib.Path)

Create results class from run statepoint

Parameters:

universe (openmc.Universe)
cell_arrays (bluemira.codes.openmc.make_csg.CellStage)
src_rate (float)
src_triton_rate (float)
statepoint_file (pathlib.Path)

static _load_volume_calculation_from_file(volume_file_path: pathlib.Path, cell_names: list[str])

Load the volume file to record as volume information.

Parameters:

volume_file_path (pathlib.Path) – filepath to volume
cell_names (list[str]) – indicative names to print.

classmethod _load_heating(statepoint, mat_names, src_rate): Load the heating (sorted by material) dataframe

classmethod _load_fluxes(statepoint, cell_names, cell_vols, src_rate): Load the neutron fluxes dataframe.

classmethod _load_damage(statepoint, cell_names, cell_vols, cell_arrays, src_rate): Load the damage-energy tally dataframe, post-process them until we get: - Fe damage rate for the FW - Fe damage rate behind the FW - Cu damage rate in the divertor - Fe damage rate in the VV

static _add_dpa_column(df, dpa_threshold_eV): Add the data for number of atoms and number of displacements, which are then used to calculate the DPA/FPY.

classmethod _load_photon_heat_flux(statepoint, cell_names, cell_vols, src_rate): Load the photon heaat flux dataframe

__str__(): String representation

static _tabulate(records: dict[str, str | float], tablefmt: str = 'fancy_grid', floatfmt: str = '.3g') → str

Parameters:

records (dict[str, str | float])
tablefmt (str)
floatfmt (str)

Return type:

str

class bluemira.codes.openmc.output.OpenMCDAGMCResult

Bases: OpenMCResultBase

Open up the openmc universe from the statepoint file, so that the dataframes containing the relevant results can be generated and reformatted by its methods.