compute_stress#

Autogenerated DPF operator classes.

class ansys.dpf.core.operators.result.compute_stress.compute_stress(scoping=None, streams_container=None, data_sources=None, requested_location=None, strain=None, config=None, server=None)#

Computes the stress from an elastic strain field.Only some 3-D elements (only hexa, tetra, pyramid and wedge) and integration schemes are supported. Only isotropic materials are supported. Material nonlinearity is not supported. Only constant materials are supported. All coordinates are global coordinates. All units need to be consistent.

Parameters

  • scoping (Scoping, optional) – The element scoping on which the result is computed.

  • streams_container (StreamsContainer, optional) – Needed to get mesh and material ids. optional if a data_sources have been connected.

  • data_sources (DataSources, optional) – Needed to get mesh and material ids. optional if a streams_container have been connected.

  • requested_location (str, optional) – Average the elemental nodal result to the requested location.

  • strain (FieldsContainer or Field) – Field/or fields container containing only the elastic strain field (element nodal).

Examples

>>> from ansys.dpf import core as dpf

>>> # Instantiate operator
>>> op = dpf.operators.result.compute_stress()

>>> # Make input connections
>>> my_scoping = dpf.Scoping()
>>> op.inputs.scoping.connect(my_scoping)
>>> my_streams_container = dpf.StreamsContainer()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> my_requested_location = str()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> my_strain = dpf.FieldsContainer()
>>> op.inputs.strain.connect(my_strain)

>>> # Instantiate operator and connect inputs in one line
>>> op = dpf.operators.result.compute_stress(
...     scoping=my_scoping,
...     streams_container=my_streams_container,
...     data_sources=my_data_sources,
...     requested_location=my_requested_location,
...     strain=my_strain,
... )

>>> # Get output data
>>> result_fields_container = op.outputs.fields_container()
static default_config(server=None)#

Returns the default config of the operator.

This config can then be changed to the user needs and be used to instantiate the operator. The Configuration allows to customize how the operation will be processed by the operator.

Parameters

server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When None, attempts to use the the global server.

property inputs#

Enables to connect inputs to the operator

Returns

inputs

Return type

InputsComputeStress

property outputs#

Enables to get outputs of the operator by evaluationg it

Returns

outputs

Return type

OutputsComputeStress

property config#

Copy of the operator’s current configuration.

You can modify the copy of the configuration and then use operator.config = new_config or create an operator with the new configuration as a parameter.

Returns

Copy of the operator’s current configuration.

Return type

ansys.dpf.core.config.Config

connect(pin, inpt, pin_out=0)#

Connect an input on the operator using a pin number.

Parameters

  • pin (int) – Number of the input pin.

  • inpt (str, int, double, bool, list of int, list of doubles,) –

    Field, FieldsContainer, Scoping, ScopingsContainer, MeshedRegion,

    MeshesContainer, DataSources, Operator, os.PathLike

    Object to connect to.

  • pin_out (int, optional) – If the input is an operator, the output pin of the input operator. The default is 0.

Examples

Compute the minimum of displacement by chaining the "U" and "min_max_fc" operators.

>>> from ansys.dpf import core as dpf
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.multishells_rst)
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> max_fc_op = dpf.operators.min_max.min_max_fc()
>>> max_fc_op.inputs.connect(disp_op.outputs)
>>> max_field = max_fc_op.outputs.field_max()
>>> max_field.data
array([[0.59428386, 0.00201751, 0.0006032 ]])
eval(pin=None)#

Evaluate this operator.

Parameters

pin (int) – Number of the output pin. The default is None.

Returns

output – Returns the first output of the operator by default and the output of a given pin when specified. Or, it only evaluates the operator without output.

Return type

FieldsContainer, Field, MeshedRegion, Scoping

Examples

Use the eval method.

>>> from ansys.dpf import core as dpf
>>> import ansys.dpf.core.operators.math as math
>>> from ansys.dpf.core import examples
>>> data_src = dpf.DataSources(examples.multishells_rst)
>>> disp_op = dpf.operators.result.displacement()
>>> disp_op.inputs.data_sources(data_src)
>>> normfc = math.norm_fc(disp_op).eval()
get_output(pin=0, output_type=None)#

Retrieve the output of the operator on the pin number.

To activate the progress bar for server version higher or equal to 3.0, use my_op.progress_bar=True

Parameters

  • pin (int, optional) – Number of the output pin. The default is 0.

  • output_type (ansys.dpf.core.common.types, optional) – Requested type of the output. The default is None.

Returns

Output of the operator.

Return type

type

static operator_specification(op_name, server=None)#

Put the grpc spec message in self._spec

property progress_bar: bool#

With this property, the user can choose to print a progress bar when the operator’s output is requested, default is False

run()#

Evaluate this operator.

class ansys.dpf.core.operators.result.compute_stress.InputsComputeStress(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to connect user inputs to compute_stress operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> my_scoping = dpf.Scoping()
>>> op.inputs.scoping.connect(my_scoping)
>>> my_streams_container = dpf.StreamsContainer()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> my_data_sources = dpf.DataSources()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> my_requested_location = str()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> my_strain = dpf.FieldsContainer()
>>> op.inputs.strain.connect(my_strain)
property scoping#

Allows to connect scoping input to the operator.

The element scoping on which the result is computed.

Parameters

my_scoping (Scoping) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> op.inputs.scoping.connect(my_scoping)
>>> # or
>>> op.inputs.scoping(my_scoping)
property streams_container#

Allows to connect streams_container input to the operator.

Needed to get mesh and material ids. optional if a data_sources have been connected.

Parameters

my_streams_container (StreamsContainer) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> op.inputs.streams_container.connect(my_streams_container)
>>> # or
>>> op.inputs.streams_container(my_streams_container)
property data_sources#

Allows to connect data_sources input to the operator.

Needed to get mesh and material ids. optional if a streams_container have been connected.

Parameters

my_data_sources (DataSources) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> op.inputs.data_sources.connect(my_data_sources)
>>> # or
>>> op.inputs.data_sources(my_data_sources)
property requested_location#

Allows to connect requested_location input to the operator.

Average the elemental nodal result to the requested location.

Parameters

my_requested_location (str) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> op.inputs.requested_location.connect(my_requested_location)
>>> # or
>>> op.inputs.requested_location(my_requested_location)
property strain#

Allows to connect strain input to the operator.

Field/or fields container containing only the elastic strain field (element nodal).

Parameters

my_strain (FieldsContainer or Field) –

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> op.inputs.strain.connect(my_strain)
>>> # or
>>> op.inputs.strain(my_strain)
connect(inpt)#

Connect any input (an entity or an operator output) to any input pin of this operator.

Searches for the input type corresponding to the output.

Parameters

inpt (str, int, double, Field, FieldsContainer, Scoping,) –

DataSources, MeshedRegion, ScopingsContainer, CyclicSupport,

…, Output, Outputs, Operator, os.PathLike

Input of the operator.

class ansys.dpf.core.operators.result.compute_stress.OutputsComputeStress(op: ansys.dpf.core.dpf_operator.Operator)#

Intermediate class used to get outputs from compute_stress operator.

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> # Connect inputs : op.inputs. ...
>>> result_fields_container = op.outputs.fields_container()
property fields_container#

Allows to get fields_container output of the operator

Returns

my_fields_container

Return type

FieldsContainer

Examples

>>> from ansys.dpf import core as dpf
>>> op = dpf.operators.result.compute_stress()
>>> # Connect inputs : op.inputs. ...
>>> result_fields_container = op.outputs.fields_container()