ansys.materials.manager._models._mapdl.anisotropic_elasticity

Module Contents

Classes

ElasticityMode	Determines which kind of coefficients are used in the model.
AnisotropicElasticity	Provides the anisotropic elasticity model.

Attributes

TYPE_CHECKING

ansys.materials.manager._models._mapdl.anisotropic_elasticity.TYPE_CHECKING = False

class ansys.materials.manager._models._mapdl.anisotropic_elasticity.ElasticityMode

Bases: enum.Enum

Determines which kind of coefficients are used in the model.

STIFFNESS = 1

COMPLIANCE = 2

class ansys.materials.manager._models._mapdl.anisotropic_elasticity.AnisotropicElasticity(n_dimensions: int, coefficient_type: ElasticityMode, coefficients: Optional[numpy.ndarray] = None, temperature: Union[None, float, numpy.ndarray] = None)

Bases: ansys.materials.manager._models._common._base._BaseModel

Provides the anisotropic elasticity model.

The anisotropic elasticity model defines different elastic coefficients for each coordinate axis. This model can be used with plane and solid elements. The elastic coefficient matrix (D) is specified as one or up to six NumPy arrays, allowing temperature dependence to be modeled.

The elastic coefficient matrix is defined as a 2 x n_dimensions array:

\[\begin{split}\begin{matrix} D_{11}\\ D_{21} & D_{22}\\ D_{31} & D_{32} & D_{33}\\ D_{41} & D_{42} & D_{43} & D_44} \end{matrix}\end{split}\]

This can either be specified in “stiffness” form, with units of force/area, or in “compliance” form with the inverse unit.

This model wraps the APDL “ELAS” and “ANEL” models in both their forms. If one temperature is provided, the “ELAS” model is used, with either the “AELS” or “AELF” TBOPT. Otherwise, the “ANEL” model is used.

Create an anisotropic elasticity model.

Parameters:

n_dimensions: int

Number of dimensions for the model. The value must be either 2 or 3.

coefficient_type: ElasticityMode

Type of elasticity mode that the model uses, which is either stiffness or compliance coefficients.

coefficients: np.ndarray

Model coefficients, either one 2*n_dims x 2*n_dims array of the model coefficients or, if the model is temperature dependent, up to 6 x 2*n_dims x 2*n_dims array of the model coefficients at temperature.

temperature: Union[float, np.ndarray]

Either a single temperature at which to apply the model or an array of up to six temperatures if the model is temperature dependent. If multiple temperatures are defined, ensure that they cover the range of anticipated temperatures at which the model is applied.

property name: str

Name of the model.

property coefficients: numpy.ndarray

Current coefficient array for the model.

property temperature: numpy.ndarray

Temperature defined for the model.

model_codes = ('ANEL', 'ELAS')

name = 'Anisotropic Elasticity'

applicable_packages

classmethod deserialize_model(model_code: str, model_data: List[str]) → AnisotropicElasticity

Convert output from the MAPDL command into an object representing the model.

The input should be a section of output referring to one model from one material.

Parameters:

model_code: str

String model code, either “ELAS” or “ANEL”.

model_data: List[str]

Lines from MAPDL output corresponding to this model for one material.

Returns:

AnisotropicElasticity

Wrapper for the underlying MAPDL material model.

Notes

Depending on the type of the underlying model, the parameters of the returned AnisotropicElasticity model vary, but this class is returned for either “ELAS” or “ANEL” material models.

static deserialize_anel_data(model_data: List[str]) → Tuple[int, numpy.ndarray, numpy.ndarray]

Deserialize the first section of data returned by calling TBLIST with an “ANEL” model.

The first row contains the temperatures at which the model is applied, and subsequent rows contain each coefficient value at each specified temperature.

Parameters:

model_data: List[str]

Lines from MAPDL output corresponding to the model coefficients and measured temperatures.

static deserialize_elas_data(model_data: List[str]) → Tuple[int, float, numpy.ndarray]

Deserialize the first section of data returned by calling TBLIST with an “ELAS” model.

The first row contains the temperature at which the model is applied, and subsequent rows contain each coefficient value.

Parameters:

model_data: List[str]

Lines from MAPDL output corresponding to the model coefficients and measured temperature.

static read_matrix(model_data: List[str]) → List[Tuple]

Read a matrix from a list of strings.

Iterate through a provided list of strings and extract, if present, a valid matrix element label and any subsequent floating point values.

Parameters:

model_data: List[str]

Matrix coefficient section from the output of a TBLIST command. Any rows that do not begin with a label are ignored. otherwise, each row is deserialized into a tuple with the string label and any associated float values.

write_model(pyansys_session: Any, material: ansys.materials.manager.material.Material) → None

Write the model to MAPDL.

This method performs some pre-flight verification and writes the correct model for the provided values of coefficients and temperatures.

If no temperature value is specified for the model, the current reference temperature for the material is used.

Parameters:

pyansys_session: _MapdlCore

Configured instance of PyMAPDL.

material: Material

Material object to associate with this model.

validate_model() → Tuple[bool, List[str]]

Validate some aspects of the model before attempting to write to MAPDL.

This method performs these actions:

• Validates that the number of provided temperatures match the size of the first dimension

  of the coefficient array.

• Validates that the coefficient array is either two or three dimensional.

• Validates that no more than six temperature samples are provided.

Returns:

Tuple

First element is Boolean. True if validation is successful. If False, the second element contains a list of strings with more information.