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Add examples for Fluids models (#1021)
* Add better support for plotting on faces * deep_copy mesh with an operator * use passed server * legacy behavior for legacy server * Improve MeshInfo api. Begin example * Update all get_property calls * fix missing test * remove topology and name tests to avoid TFS pipelines failing * Add simple example * Revert complete mesh_info tests * README for fluids examples * Second fluid example * fix fluid examples * Remove unneded map * Update docs.yml check for success conditional Parse the whole log for robustness, for cases such as this to still be marked as successful despite text being printed to the stdout after doc generation execution. * Implement rev comments * More examples * continue * averaging * Changes to mesh_info halfway-through * Remove type in mesh_info and gdc docstring * fix issue * Cosmetic changes --------- Co-authored-by: Paul Profizi <[email protected]>
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‎.github/workflows/docs.yml‎

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shell: bash
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working-directory: docs
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run: |
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case `tail -n 5 log.txt | grep -F "build succeeded" >/dev/null; echo $?` in
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case `grep -F "build succeeded" log.txt >/dev/null; echo $?` in
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0)
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echo "Build succeeded!"
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exit 0;;

‎examples/12-fluids/00-fluids_model.py‎

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"""
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.. _ref_fluids_model:
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Explore Fluids models
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------------------------------------------------------
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This example shows how to explore Ansys Fluent and Ansys CFX models employing
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the ``MeshInfo`` and ``ResultInfo``.
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"""
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###############################################################################
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# Exploring an Ansys Fluent model
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# -------------------------------
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# The first part of the example demonstrates how you can explore an Ansys Fluent
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# model. Import the result file and create a model
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import ansys.dpf.core as dpf
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from ansys.dpf.core import examples
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path = examples.download_fluent_axial_comp()["flprj"]
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ds = dpf.DataSources(path)
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model = dpf.Model(data_sources=ds)
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###############################################################################
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# Exploring the mesh
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# ~~~~~~~~~~~~~~~~~~
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# Explore the mesh through the ``MeshInfo``. The ``MeshInfo`` provides metadata
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# information about the mesh. For fluid models, it is useful to know the cell and
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# face zones, as well as the topological relationships between them. First get all
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# the available information in the ``MeshInfo``
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minfo = model.metadata.mesh_info
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print(minfo)
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###############################################################################
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# Then, get the bodies and their names in the model with the "body_names" ``StringField``,
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# which provides a relationship between body IDs and names. In this model there are two
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# bodies.
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print(minfo.get_property("body_names"))
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###############################################################################
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# Each body is comprised of a set of cell zones. You can investigate the hierarchical
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# relationship between bodies and cell zones through the "body_cell_topology"
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# ``PropertyField``, which provides a relationship between the body IDs and the cell zone
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# IDs. In this case, each body is only comprised of one cell zone.
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print(minfo.get_property("body_cell_topology"))
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###############################################################################
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# Similarly, each body is limited by a set of face zones (generally representing
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# boundary conditions). You can investigate the hierarchical relationship between
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# bodies and face zones through the "body_face_topology" ``PropertyField``, which
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# provides a relationship between the body IDs and the face zone IDs. In this case,
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# each body is limited by several face zones
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print(minfo.get_property("body_face_topology"))
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###############################################################################
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# The cell and face zone ids shown in the previous PropertyFields can be mapped
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# to their names through the "body_zone_names" and "face_zone_names" ``PropertyField``.
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# As in this model there is a 1-1 correspondence between bodies and cell zones,
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# they have the same names and IDs.
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print(minfo.get_property("cell_zone_names"))
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print(minfo.get_property("face_zone_names"))
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###############################################################################
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# All zone names (regardless of them being cell or face zones) are exported to
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# the "zone_names" ``StringField``
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print(minfo.get_property("zone_names"))
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###############################################################################
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# To facilitate the extraction of results, the body, cell and face zone ``Scoping``
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# are extracted. They can be used to scope results
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print(minfo.get_property("body_scoping"))
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print(minfo.get_property("cell_zone_scoping"))
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print(minfo.get_property("face_zone_scoping"))
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###############################################################################
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# Exploring the results
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# ~~~~~~~~~~~~~~~~~~~~~
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# Explore the available results in the model through the ResultInfo. This is a Fluent model
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# whose native results are exported to either the centroid of the elements (like
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# Enthalpy or RMS Temperature), the centroid of the faces (like the Mass Flow Rate)
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# or the centroid of both elements and faces (like Static Pressure).
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rinfo = model.metadata.result_info
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print(rinfo)
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###############################################################################
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# Each result holds more detailed information while explored individually. Enthalpy
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# is a scalar magnitude exported to the centroids of the elements (cells). Thus, it is
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# available for the two cell zones of the model (13 and 28). In addition, the model
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# only has one phase, and therefore the result can only be extracted for "phase-1".
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print(rinfo.available_results[0])
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###############################################################################
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# Static Pressure, however, is ElementalAndFaces, which means that it is exported
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# at both the centroids of the cells and the centroids of the faces. Therefore, it is
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# available for all the cell and face zones of the model.
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print(rinfo.available_results[2])
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###############################################################################
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# Exploring an Ansys CFX model
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# ----------------------------
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# The second part of the example demonstrates how you can explore an Ansys CFX model.
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# Import the result file and create a model
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path = examples.download_cfx_heating_coil()
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ds = dpf.DataSources()
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ds.set_result_file_path(path["cas"], "cas")
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ds.add_file_path(path["dat"], "dat")
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model = dpf.Model(data_sources=ds)
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###############################################################################
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# Exploring the mesh
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# ~~~~~~~~~~~~~~~~~~
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# If once again we explore the MeshInfo, we can see that the same information is
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# readily available
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minfo = model.metadata.mesh_info
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print(minfo)
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###############################################################################
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# In this CFX model there are also two bodies.
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print(minfo.get_property("body_names"))
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###############################################################################
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# For this model, each body is conformed by several cell zones. In this general
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# situation, the body ID corresponds to the highest cell zone ID of the one that
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# comprises it.
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print(minfo.get_property("body_cell_topology"))
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###############################################################################
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# You can also explore the face zone IDs in each body
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print(minfo.get_property("body_face_topology"))
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###############################################################################
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# The cell and face zone names are readily available
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print(minfo.get_property("cell_zone_names"))
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print(minfo.get_property("face_zone_names"))
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###############################################################################
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# Exploring the results
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# ~~~~~~~~~~~~~~~~~~~~~
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# By exploring the ResultInfo we can see that all CFX variables are exported to
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# the Nodes
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rinfo = model.metadata.result_info
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print(rinfo)
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###############################################################################
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# However, in this model there are two distinct phases. To understand the phases
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# at the model, you can explore the qualifiers of the ResultInfo. Thus, results
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# could potentially be scoped on "zone" and "phase", with the ID and name of each
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# phase shown below.
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labels = rinfo.available_qualifier_labels
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print(labels)
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phase_names = rinfo.qualifier_label_support(labels[1]).string_field_support_by_property("names")
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print(phase_names)
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###############################################################################
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# Each result holds more detailed information while explored individually. Static
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# Pressure is only available for phase 1 ("<Mixture>"), and several cell and face
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# zones.
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print(rinfo.available_results[7])
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###############################################################################
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# Thermal conductivity, however, exists for phases 2 and 3 ("Copper" and "Water at 25 C",
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# respectively), and several face and cell zones.
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print(rinfo.available_results[4])

‎examples/12-fluids/01-fluids_mesh.py‎

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"""
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.. _ref_fluids_mesh:
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Explore Fluids mesh
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-------------------
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"""
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###############################################################################
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# Exploring an Ansys Fluent mesh
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# ------------------------------
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# This example demonstrates how you can explore an Ansys Fluent mesh. Import
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# the result file
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import ansys.dpf.core as dpf
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from ansys.dpf.core import examples
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path = examples.download_fluent_axial_comp()["flprj"]
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ds = dpf.DataSources(path)
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streams = dpf.operators.metadata.streams_provider(data_sources=ds)
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###############################################################################
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# Using the ``mesh_provider``
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# The ``mesh_provider`` operator can be used to retrieve the whole mesh of the
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# model or the `MeshedRegion` restricted to a particular body or face zone. The
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# behavior will differ depending on the inputs to the ``region_scoping`` pin.
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# If no scoping is connected, the mesh for the whole model is obtained. This
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# is the same mesh that is obtained if the ``Model.metadata.meshed_region``
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# API is employed.
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mesh_whole = dpf.operators.mesh.mesh_provider(streams_container=streams).eval()
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print(mesh_whole)
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mesh_whole.plot()
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###############################################################################
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# If the ``region_scoping`` pin is connected, a ``Scoping`` with 1 zone ID is
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# expected, or an integer list with one item, or a single integer. The supported
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# zone IDs are either face zone IDs or body IDs. The zones of this particular model
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# are explored in :ref:`ref_fluids_model`. ID 4 (rotor-shroud) corresponds to a
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# face zone, and thus its mesh is only comprised of faces and nodes. ID 13 (fluid-rotor)
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# is a body, and thus its mesh has elements (cells), faces and nodes.
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mesh_4 = dpf.operators.mesh.mesh_provider(streams_container=streams, region_scoping=4).eval()
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print(mesh_4)
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mesh_4.plot()
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mesh_13 = dpf.operators.mesh.mesh_provider(streams_container=streams, region_scoping=[13]).eval()
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print(mesh_13)
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mesh_13.plot()
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###############################################################################
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# Using the ``meshes_provider``
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# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# The ``meshes_provider`` operator can be used to retrieve the mesh for several
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# zones and time steps of the model. The behavior will differ depending on the
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# inputs to the ``region_scoping`` pin. If no region_scoping is connected, the
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# ``MeshedRegion`` for all body and face zones is retrieved in a ``MeshesContainer``.
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# If no time_scoping is connected and the simulation is transient, only the meshes
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# for the first time step are extracted.
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meshes_all = dpf.operators.mesh.meshes_provider(streams_container=streams).eval()
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print(meshes_all)
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print("\n".join([str(meshes_all.get_label_space(i)) for i in range(len(meshes_all))]))
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###############################################################################
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# If the ``region_scoping`` pin is connected, the mesh extraction is restricted to
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# the zone IDs contained in the input Scoping/list (in this case, a face zone connected
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# to body 18 and body 13).
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meshes_23_13 = dpf.operators.mesh.meshes_provider(
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streams_container=streams, region_scoping=[23, 13], time_scoping=[3]
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).eval()
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print(meshes_23_13)
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meshes_23_13.plot()

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