Parameters#

CRC_file_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Path to channel reconstruction (Oxford Instruments binary) file.

Input of: sample_texture, sample_orientations

CSV_arguments#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Input of: read_tensile_test

CSV_file_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Path to CSV (possibly an Oxford Instruments single orientation) file.

Input of: read_tensile_test

CTF_file_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Path to CTF (HKL single orientation) file.

Input of: sample_texture, sample_orientations

DIC#

type: dict
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['filename', 'crop', 'scale', 'homog_points', 'min_grain_size']))

Digital image correlation data descriptor.

Input of: load_microstructure

EBSD#

type: dict
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['filename', 'boundary_tol', 'min_grain_size', 'homog_points']))

Electron backscatter diffraction data descriptor.

Input of: load_microstructure, load_microstructure

EBSD_phase#

type: str
Condition: Value.is_instance(<class 'str'>)

Electron backscatter diffraction phase.

Input of: sample_texture, sample_texture, sample_orientations, sample_orientations

EBSD_reference_frame_transformation#

type: str, ('euler_to_spatial' | 'spatial_to_euler' | 'convertEuler2SpatialReferenceFrame' | 'convertSpatial2EulerReferenceFrame')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['euler_to_spatial', 'spatial_to_euler', 'convertEuler2SpatialReferenceFrame', 'convertSpatial2EulerReferenceFrame']))

Electron backscatter diffraction referemce frame transformation.

Input of: sample_texture, sample_texture, sample_orientations, sample_orientations

EBSD_rotation#

type: dict
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['euler_angles_deg', 'keep_XY', 'keep_euler']))

Description of the rotation in the electron backscatter diffraction model. A dict with keys "euler_angles_deg" (list, optional) "keep_XY" (bool), or "keep_euler" (bool).

Input of: sample_texture, sample_texture, sample_orientations, sample_orientations

IPF_reference_direction#

type: str, ('x' | 'y' | 'z')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['x', 'y', 'z']))

Input of: visualise_orientations

ODF_components#

type: list (of: dict)
Condition: Value.is_instance(<class 'list'>)

Information used to control the orientation distribution function.

Input of: sample_texture

ODF_mat_file_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Path to ODF material file.

Input of: sample_texture

VE_grid_size#

type: list, length: 2 or 3 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

Number of simulation pixels (voxels) in each of the x, y(, z) directions.

Input of: generate_volume_element, generate_volume_element

VE_response#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Volume element response.

Input of: fit_single_crystal_parameters, dump_all_yield_stresses, fit_yield_function, collate_CP_data

Output of: simulate_VE_loading, simulate_VE_loading

VE_response_data#

type: dict
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['geom_path', 'incremental_data', 'volume_data', 'phase_data', 'field_data', 'grain_data']))

This parameter is a dictionary of values that are the optional arguments to damask_parse.read_HDF5_file (which should be consulted for details). Keys should be one of "geom_path", "volume_data", "phase_data", "field_data", "grain_data", or "incremental_data" (now deprecated).

Input of: simulate_VE_loading, simulate_VE_loading

VE_size#

type: list, length: 2 or 3 (of: float)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

Size of the simulation box in each of the x, y(, z) directions.

Example: For a simulation box that is twice as long (i.e. elongated) in the y-direction as in the x- and z-directions, use: [1.0, 2.0, 1.0].

Input of: generate_microstructure_seeds, generate_volume_element

bf_threshold#

type: float
Condition: Value.is_instance(<class 'float'>)

Correlation threshold used in rigid bruteforce check for a subset to be considered a good match(default: 0.6).

Input of: run_DIC

buffer_sizes#

type: list, length: 6 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=6))

Size of buffer on each face [-x, +x, -y, +y, -z, +z].

Input of: modify_VE

colourbar_limits#

type: list, length: 2 (of: float)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=2))

Uses API deprecated by MTEX. Might not work at all.

Input of: visualise_orientations

compile#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Whether to compile.

Input of: visualise_multi_orientations

correlation_criteria#

type: str, ('ZNSSD' | 'NSSD' | 'SSD')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['ZNSSD', 'NSSD', 'SSD']))

Metric for matching subsets: ZNSSD, NSSD or SSD (default: ZNSSD).

Input of: run_DIC

crop_dists#

type: dict (value: int)
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['left', 'right', 'top', 'bottom']))

Number of px to exclude from each edge of image (left, right, top, bottom).

Input of: create_DIC_ROI

crystal_symmetry#

type: str
Condition: Value.is_instance(<class 'str'>)

Single parameter to make an instance of MTEX crystalSymmetry.

Example: cubic - Cubic symmetry

Example: hexagonal - Hexagonal symmetry

Input of: sample_texture, visualise_orientations, visualise_orientations, visualise_multi_orientations, sample_texture

damask_log#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Output of: simulate_VE_loading

damask_numerics#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Input of: simulate_VE_loading, simulate_VE_loading

damask_phases#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Input of: simulate_VE_loading, simulate_VE_loading

damask_post_processing#

type: list (of: dict)
Condition: Value.is_instance(<class 'list'>)

List of post-processing operations to apply to the DAMASK output.

[list-value]#

type: dict, optional
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['name', 'args', 'opts']))

name#

type: str, ('add_absolute' | 'add_calculation' | 'add_stress_Cauchy' | 'add_determinant' | 'add_deviator' | 'add_eigenvalue' | 'add_eigenvector' | 'add_IPF_color' | 'add_maximum_shear' | 'add_equivalent_Mises' | 'add_norm' | 'add_stress_second_Piola_Kirchhoff' | 'add_pole' | 'add_rotation' | 'add_spherical' | 'add_strain' | 'add_stretch_tensor' | 'add_curl' | 'add_divergence' | 'add_gradient'), optional
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['add_absolute', 'add_calculation', 'add_stress_Cauchy', 'add_determinant', 'add_deviator', 'add_eigenvalue', 'add_eigenvector', 'add_IPF_color', 'add_maximum_shear', 'add_equivalent_Mises', 'add_norm', 'add_stress_second_Piola_Kirchhoff', 'add_pole', 'add_rotation', 'add_spherical', 'add_strain', 'add_stretch_tensor', 'add_curl', 'add_divergence', 'add_gradient']))

See damask.Result for what the operations do.

Input of: simulate_VE_loading, simulate_VE_loading

damask_post_processing_result#

Output of: simulate_VE_loading

damask_solver#

type: dict (value: str)
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['mechanical', 'thermal', 'damage']))

A dictionary that specifies which solver to use, for each considered physical phenomenon (mechanical, thermal, or damage).

Example: To use the spectral_polarization mechanical solver instead of the default spectral_basic solver, set to: {"mechanical": "spectral_polarization"}

Input of: simulate_VE_loading, simulate_VE_loading

damask_viz#

Condition: ConditionOr(ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['increments', 'phases', 'homogenizations', 'fields'])), Value.is_instance(<class 'list'>))

Dictionary or list of dictionaries describing particular visualizations. Keys should be increments, phases, homogenizations, or fields; all are optional.

Input of: simulate_VE_loading, simulate_VE_loading

damask_viz_result#

Output of: simulate_VE_loading

deformed_image_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Input of: run_DIC

depth#

type: int
Condition: Value.is_instance(<class 'int'>)

Input of: generate_volume_element

dic_seed#

type: list, length: 2 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=2))

Coordinates [x, y] of the seed point for Reliability-Guided (RG) scanning, default is centre of image.

dump_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Where to write dump data.

Input of: dump_all_yield_stresses

eng_strain_col_index#

type: int
Condition: Value.is_instance(<class 'int'>)

CSV column index.

Input of: read_tensile_test

eng_stress_col_index#

type: int
Condition: Value.is_instance(<class 'int'>)

CSV column index.

Input of: read_tensile_test

fft_mad#

type: bool
Condition: Value.is_instance(<class 'bool'>)

The option to smooth FFT windowing data by identifying and replacing outliers using a robust statistical method. For each subset, the function collects values from its neighboring subsets (within a 5x5 window, i.e., radius = 2), computes the median and Median Absolute Deviation (MAD), and determines whether the value at the current subset is an outlier. If it is, the value is replaced with the median of its neighbors. (default: False)

Input of: run_DIC

fft_mad_scale#

type: bool
Condition: Value.is_instance(<class 'bool'>)

An outlier is defined as a value whose deviation from the local median exceeds fft_mad_scale times the MAD. This value choses the scaling factor that determines the threshold for detecting outliers relative to the MAD.

Input of: run_DIC

find_grains_algorithm#

type: str, ('warp' | 'floodfill')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['warp', 'floodfill']))

Input of: load_microstructure

fit_yield_fixed_parameters#

Input of: fit_yield_function

fit_yield_initial_parameters#

Input of: fit_yield_function

fit_yield_opt_parameters#

Input of: fit_yield_function

fitted_yield_functions#

Output of: fit_yield_function

generate_exodus#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Whether to generate an Exodus file of the mesh to allow visualisation in ParaView.

Input of: generate_plate_mesh_2D

geometry_name#

type: str
Condition: Value.is_instance(<class 'str'>)

The name of the geometry to mesh. Currently only quarter_plate_with_hole is accepted.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D

gmsh_mesh_str#

type: str
Condition: Value.is_instance(<class 'str'>)

The Gmsh-generated mesh, as a string.

Input of: moose_simulation

Output of: generate_plate_mesh_2D, generate_plate_mesh_3D

grid_size#

type: list, length: 2 or 3 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

Number of simulation pixels (voxels) in each of the x, y(, z) directions.

Input of: generate_volume_element, generate_volume_element, generate_phase_field_input, generate_phase_field_input, generate_phase_field_input

hole_diameter#

type: float
Condition: Value.is_instance(<class 'float'>)

The diameter of the hole in the plate.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, calculate_plate_SCF

hole_sect_nodes#

type: int
Condition: Value.is_instance(<class 'int'>)

The number of nodes to place around the circumference of the quarter-hole.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, refine_2D_plate_mesh, refine_3D_plate_mesh

Output of: refine_2D_plate_mesh, refine_3D_plate_mesh

homog_label#

type: str
Condition: Value.is_instance(<class 'str'>)

This parameter associates a string label with each grain that determines which homogenization scheme should be used. The homogenization schemes to be employed by the crystal plasticity simulation are then defined according to these labels.

Example: For a full-field simulation, where there is no mechanical homogenization we typically use the label 'SX'.

Input of: generate_volume_element, generate_volume_element, modify_VE, generate_volume_element

homogenization#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Dictionary whose keys are homogenization scheme labels and whose values are dictionaries that specify the homogenization parameters for that scheme.

Input of: simulate_VE_loading, simulate_VE_loading

image_axes#

type: list (of: str)
Condition: Value.is_instance(<class 'list'>)

Input of: generate_volume_element

initial_damping#

type: list (of: float | int)
Condition: Value.is_instance(<class 'list'>)

List of initial damping parameters.

Example: The default value is [2, 1, 0.5]

Input of: fit_single_crystal_parameters

input_deck#

Input of: moose_simulation

Constructors:

interpolation_routine#

type: str, ('BICUBIC')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['BICUBIC']))

Interpolation method used on image intensity. BICUBIC is currently the only supported option.

Input of: run_DIC

levenberg_marquardt_fitter#

type: list
Condition: Value.is_instance(<class 'list'>)

Output of: fit_single_crystal_parameters

load_case#

Input of: define_load_case, simulate_VE_loading, simulate_VE_loading

Constructors:

max_displacement#

type: int
Condition: Value.is_instance(<class 'int'>)

Estimate for the Maximum displacement in any direction (in pixels) (default: 128).

Input of: run_DIC

max_iterations#

type: int
Condition: Value.is_instance(<class 'int'>)

Maximum number of iterations allowed for subset optimization (default: 40).

Input of: run_DIC

method#

type: str, ('RG' | 'IMAGE_SCAN' | 'FFT')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['RG', 'IMAGE_SCAN', 'FFT']))

Subset scanning method: RG for Reliability-Guided (best overall approach), IMAGE_SCAN for a standard scan across the image with no seeding (best performance with for subpixel displacements with high quality images), FFT for a multi-window FFT based approach (Good for large displacements)

Input of: run_DIC

microstructure_image#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Input of: generate_volume_element

Output of: load_microstructure, load_microstructure

microstructure_seeds#

Input of: generate_volume_element, define_microstructure_seeds

Output of: generate_microstructure_seeds

Constructors:

new_grid_size#

type: list, length: 2 or 3 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

New number of simulation pixels (voxels) in each of the x, y(, z) directions.

Input of: modify_VE

num_grains#

type: int
Condition: Value.is_instance(<class 'int'>)

The integer number of grains to include.

Input of: generate_microstructure_seeds

num_orientations#

type: int
Condition: Value.is_instance(<class 'int'>)

Number of orientations.

Input of: sample_texture, sample_texture, sample_texture, sample_texture, generate_orientations, sample_orientations, sample_orientations, sample_texture

order#

type: list, length: 3 (of: str, ('x' | 'y' | 'z'))
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=3))

Order to add the zones in.

Input of: modify_VE

orientations#

Input of: generate_volume_element, visualise_orientations, visualise_orientations, visualise_multi_orientations, define_orientations, generate_volume_element, generate_volume_element, generate_rve, generate_phase_field_input

Output of: sample_texture, sample_texture, sample_texture, sample_texture, generate_orientations, sample_orientations, sample_orientations, sample_texture

Constructors:

origin#

type: list, length: 2 or 3 (of: float)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

Location of the origin of the grid.

Input of: generate_volume_element, generate_volume_element

output_below_threshold#

type: bool
Condition: Value.is_instance(<class 'bool'>)

If True, subset results with cost values that did not exceed the cost threshold will still be present in output (default: False).

Input of: run_DIC

output_delimiter#

type: str
Condition: Value.is_instance(<class 'str'>)

Delimiter used in text output files (default: ,).

Input of: run_DIC

path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Path to file to process.

Input of: visualise_VE

periodic#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Input of: generate_volume_element, generate_volume_element, generate_volume_element

phase_ids#

type: list, length: 6 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=6))

Phase of each buffer. Relative, so 1 is the first new phase and so on

Input of: modify_VE

phase_label#

type: str
Condition: Value.is_instance(<class 'str'>)

The string phase label to associated with e.g. the microstructure seed points.

Input of: generate_microstructure_seeds, generate_volume_element, generate_volume_element

phase_label_mapping#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Mapping from phase labels in the microstructure_image to phase labels for created in the VE.

Input of: generate_volume_element

phase_labels#

type: list, length: 6 (of: str)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=6))

Labels of the new phases.

Input of: modify_VE

phase_statistics#

type: list (of: dict)
Condition: Value.is_instance(<class 'list'>)

A list of dictionaries giving the statistics for the various phases. Each dictionary must have the keys type, name, crystal_structure, and volume_fraction. Dictionaries of type: primary must also have a size_distribution key. Dictionaries of type: precipitate must also have the keys size_distribution, radial_distribution_function, and number_fraction_on_boundary.

[list-value]#

type: dict, optional
Condition: ConditionAnd(Value.is_instance(<class 'dict'>), Key.in_(value=['type', 'name', 'crystal_structure', 'volume_fraction', 'size_distribution', 'radial_distribution_function', 'number_fraction_on_boundary', 'preset_statistics_model', 'ODF', 'axis_ODF']))

type#

type: str, ('matrix' | 'primary' | 'precipitate'), optional
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['matrix', 'primary', 'precipitate']))

Input of: generate_volume_element, generate_volume_element

plastic_range#

type: list, length: 2 (of: float)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=2))

Input of: read_tensile_test

plate_diff#

type: int
Condition: Value.is_instance(<class 'int'>)

The height of the extra block added to the top of the mesh.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, calculate_plate_SCF

plate_diff_nodes#

type: int
Condition: Value.is_instance(<class 'int'>)

The number of nodes to place along the vertical direction within the extra block added to the top of the mesh.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, refine_2D_plate_mesh, refine_3D_plate_mesh

Output of: refine_2D_plate_mesh, refine_3D_plate_mesh

plate_radial_nodes#

type: int
Condition: Value.is_instance(<class 'int'>)

The number of nodes to place along the radial direction.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, refine_2D_plate_mesh, refine_3D_plate_mesh

Output of: refine_2D_plate_mesh, refine_3D_plate_mesh

plate_width#

type: float
Condition: Value.is_instance(<class 'float'>)

The width of the full plate.

Input of: generate_plate_mesh_2D, generate_plate_mesh_3D, calculate_plate_SCF

pole_figure_directions#

type: list (of: list, length: 3)
Condition: Value.is_instance(<class 'list'>)

[list-value]#

type: list, length: 3 (of: int | float), optional
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=3))

Input of: visualise_orientations

precipitates#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Input of: generate_volume_element, generate_volume_element

precision#

type: float
Condition: Value.is_instance(<class 'float'>)

Precision threshold for iterative optimization convergence (default: 0.001).

Input of: run_DIC

reference_image_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Input of: create_DIC_ROI, run_DIC

resolution#

type: list (of: int | float)
Condition: Value.is_instance(<class 'list'>)

Input of: generate_volume_element, generate_volume_element

root_path#

type: str | path
Condition: Value.is_instance(<class 'str'>, <class 'pathlib._local.Path'>)

Location to resolve filenames with respect to.

Input of: load_microstructure, load_microstructure

scale_morphology#

type: list, length: 3 (of: int | float)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.equal_to(value=3))

Input of: generate_volume_element, generate_volume_element

scale_update_size#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Input of: generate_volume_element, generate_volume_element

scaling_factor#

type: int | float
Condition: Value.is_instance(<class 'int'>, <class 'float'>)

Scaling factor.

Input of: load_microstructure, load_microstructure

shape_function#

type: str, ('AFFINE' | 'RIGID')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['AFFINE', 'RIGID']))

Deformation model: e.g., AFFINE, RIGID (default: AFFINE).

Input of: run_DIC

single_crystal_parameters#

Input of: simulate_VE_loading, simulate_VE_loading, fit_single_crystal_parameters

Output of: fit_single_crystal_parameters

Constructors:

size#

type: list, length: 2 or 3 (of: int)
Condition: ConditionAnd(Value.is_instance(<class 'list'>), ValueLength.in_(value=[2, 3]))

Number of simulation pixels (voxels) in each of the x, y(, z) directions.

Input of: generate_volume_element, generate_volume_element, generate_phase_field_input, generate_phase_field_input, generate_phase_field_input, generate_phase_field_input

specimen_symmetry#

type: str
Condition: Value.is_instance(<class 'str'>)

The symmetry of the specimen to sample, as understood by MTEX specimenSymmetry.

Example: cubic

Example: orthorhombic

Input of: sample_texture, sample_texture, sample_texture, sample_orientations, sample_orientations, sample_texture

stress_units#

type: str, ('Pa' | 'MPa' | 'GPa')
Condition: ConditionAnd(Value.is_instance(<class 'str'>), Value.in_(value=['Pa', 'MPa', 'GPa']))

Units to use for stress values.

Example: The normal value here is Pascals, "Pa"

Input of: read_tensile_test

subset_size#

type: int
Condition: Value.is_instance(<class 'int'>)

Size of the square subset window in pixels (default: 21).

Input of: run_DIC

subset_step#

type: int
Condition: Value.is_instance(<class 'int'>)

Step size between subset centers in pixels (default: 10).

Input of: run_DIC

tensile_test#

Input of: fit_single_crystal_parameters

Output of: read_tensile_test

threshold#

type: float
Condition: Value.is_instance(<class 'float'>)

Minimum correlation/cost coefficient value to be considered a matching subset (default: 0.9).

Input of: increment_chain, increment_chain_inner, increment_sub_chain, check_sub_chain, increment_chain_RST, run_DIC

Output of: collate_results

transform_type#

type: str
Condition: Value.is_instance(<class 'str'>)

Transformation type.

Input of: load_microstructure

true_strain_col_index#

type: int
Condition: Value.is_instance(<class 'int'>)

CSV column index.

Input of: read_tensile_test

true_stress_col_index#

type: int
Condition: Value.is_instance(<class 'int'>)

CSV column index.

Input of: read_tensile_test

use_contours#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Whether to use countours when visualising orientations.

Input of: visualise_orientations, visualise_orientations, visualise_multi_orientations

use_one_colourbar#

type: bool
Condition: Value.is_instance(<class 'bool'>)

Whether to use a single colour bar when visualising orientations.

Input of: visualise_orientations

volume_element#

type: dict
Condition: Value.is_instance(<class 'dict'>)

Voxelated volume element

Input of: visualise_VE, simulate_VE_loading, simulate_VE_loading, modify_VE, modify_VE, modify_VE, generate_phase_field_input, cluster_orientations

Output of: generate_volume_element, generate_volume_element, generate_volume_element, generate_volume_element, modify_VE, modify_VE, modify_VE, generate_rve, generate_volume_element, cluster_orientations

yield_function_name#

type: str
Condition: Value.is_instance(<class 'str'>)

The name of the yield function to fit to the data.

Example: VonMises - von Mises yield criteron

Example: Tresca - Tresca ductile failure criterion

Example: Hosford - Hosford yield criterion

Example: Barlat_Yld91 - Barlat anisotropic yield model

Example: Barlat_Yld2000_2D - Barlat planar stress yield model

Example: Barlat_Yld2004_18p - Barlat linear transformation yield functions

Example: Hill1979 - Generalised Hill yield criterion

Example: Hill1948 - Quadratic Hill yield criterion

Input of: fit_yield_function

yield_point#

type: float
Condition: Value.is_instance(<class 'float'>)

Input of: dump_all_yield_stresses

yield_point_criteria#

Input of: fit_yield_function