+.. #########
+
.. raw:: html
+.. ##########
+
.. raw:: html
-
+
.. only:: html
- .. image:: images/thumb/sphx_glr_tse-020-PCB_thumb.png
- :alt: Dynamic simulation of a printed circuit board assembly
-
- :ref:`sphx_glr_ex_20-tecPCB.py`
+ .. image:: images/thumb/sphx_glr_tse-015-calvalhyper_thumb.gif
+ :alt: Calibrating and Validating a Hyperelastic Constitutive Model
+
+ :ref:`sphx_glr_ex_15-teccalvalhyper.rst`
.. raw:: html
-
Dynamic simulation of a printed circuit board assembly
+
Calibrating and Validating a Hyperelastic Constitutive Model
+.. #########
.. raw:: html
-
+
.. only:: html
- .. image:: images/thumb/sphx_glr_tse-028-fricstir_thumb.png
- :alt: Friction Stir Welding (FSW) Simulation
+ .. image:: images/thumb/sphx_glr_tse-020-PCB_thumb.png
+ :alt: Dynamic simulation of a printed circuit board assembly
- :ref:`sphx_glr_ex_28-tecfricstir.py`
+ :ref:`sphx_glr_ex_20-tecPCB.rst`
.. raw:: html
-
Friction Stir Welding (FSW) Simulation
+
Dynamic simulation of a printed circuit board assembly
+.. #########
+
.. raw:: html
-
+
+.. only:: html
-.. ##########
+ .. image:: images/thumb/sphx_glr_tse-025-stent_thumb.png
+ :alt: Cardiovascular Stent Simulation
+ :ref:`sphx_glr_ex_25-tecstent.rst`
.. raw:: html
-
-
-.. only:: html
+
Cardiovascular Stent Simulation
+
- .. image:: images/thumb/sphx_glr_tse-015-calvalhyper_thumb.gif
- :alt: Calibrating and Validating a Hyperelastic Constitutive Model
+.. #########
.. raw:: html
-
Calibrating and Validating a Hyperelastic Constitutive Model
-
+
+
+.. only:: html
+
+ .. image:: images/thumb/sphx_glr_tse-028-fricstir_thumb.png
+ :alt: Friction Stir Welding (FSW) Simulation
+
+ :ref:`sphx_glr_ex_28-tecfricstir.rst`
.. raw:: html
+
Friction Stir Welding (FSW) Simulation
-.. #########
-
.. toctree::
:hidden:
:includehidden:
techdemo-1/ex_0-tecbrakesqueal
- techdemo-15/ex-15-teccalvalhyper
+ techdemo-15/ex_15-teccalvalhyper
techdemo-20/ex_20-tecPCB
+ techdemo-25/ex_25-tecstent
techdemo-28/ex_28-tecfricstir
.. only:: html
diff --git a/doc/source/technology_showcase_examples/techdemo-1/ex_0-tecbrakesqueal.rst b/doc/source/technology_showcase_examples/techdemo-1/ex_0-tecbrakesqueal.rst
index dd2c92c28..7bd76f708 100644
--- a/doc/source/technology_showcase_examples/techdemo-1/ex_0-tecbrakesqueal.rst
+++ b/doc/source/technology_showcase_examples/techdemo-1/ex_0-tecbrakesqueal.rst
@@ -1,4 +1,4 @@
-.. _sphx_glr_ex_0-tecbrakesqueal.py:
+.. _sphx_glr_ex_0-tecbrakesqueal.rst:
.. _tech_demo_01:
diff --git a/doc/source/technology_showcase_examples/techdemo-15/ex-15-teccalvalhyper.rst b/doc/source/technology_showcase_examples/techdemo-15/ex_15-teccalvalhyper.rst
old mode 100755
new mode 100644
similarity index 99%
rename from doc/source/technology_showcase_examples/techdemo-15/ex-15-teccalvalhyper.rst
rename to doc/source/technology_showcase_examples/techdemo-15/ex_15-teccalvalhyper.rst
index 55ced5f9f..531654a7d
--- a/doc/source/technology_showcase_examples/techdemo-15/ex-15-teccalvalhyper.rst
+++ b/doc/source/technology_showcase_examples/techdemo-15/ex_15-teccalvalhyper.rst
@@ -1,5 +1,7 @@
-Technology Showcase Example 15: Calibrating and Validating a Hyperelastic Constitutive Model
-----------------------------------------------------------------------------------------------
+.. _sphx_glr_ex_15-teccalvalhyper.rst:
+
+Calibrating and Validating a Hyperelastic Constitutive Model
+------------------------------------------------------------
This example problem demonstrates the hyperelastic curve-fitting capabilities used to select constitutive model
parameters to fit experimental data. Several issues that influence the accuracy of the curve fit are discussed.
diff --git a/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.ipynb b/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.ipynb
index 10d887201..4f9e85935 100644
--- a/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.ipynb
+++ b/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.ipynb
@@ -15,14 +15,34 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Dynamic simulation of a printed circuit board assembly {#ref_dynamic_simulation_printed_circuit_board}\r\n\r\nThis examples shows how to use PyMAPDL to import an existing FE model\r\nand to run a modal and PSD analysis. PyDPF modules are also used for\r\npost-processing.\r\n\r\nThis example is inspired from the model and analysis defined in Chapter\r\n20 of the Mechanical APDL Technology Showcase Manual.\r\n\r\n## Additional Packages Used\r\n\r\n- [Matplotlib](https://matplotlib.org) is used for plotting purposes.\r\n"
+ "# Dynamic simulation of a printed circuit board assembly {#ref_dynamic_simulation_printed_circuit_board}\n",
+ "\n",
+ "This examples shows how to use PyMAPDL to import an existing FE model\n",
+ "and to run a modal and PSD analysis. PyDPF modules are also used for\n",
+ "post-processing.\n",
+ "\n",
+ "This example is inspired from the model and analysis defined in Chapter\n",
+ "20 of the Mechanical APDL Technology Showcase Manual.\n",
+ "\n",
+ "## Additional Packages Used\n",
+ "\n",
+ "- [Matplotlib](https://matplotlib.org) is used for plotting purposes.\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Setting up model\r\n\r\nThe original FE model is given in the Ansys Mechanical APDL Technology\r\nShowcase Manual. The .cdb contains a FE model of a single circuit board.\r\nThe model is meshed with SOLID186, SHELL181 and BEAM188 elements. All\r\ncomponents of the PCB model is assigned with linear elastic isotropic\r\nmaterials. Bonded and flexible surface-to-surface contact pairs are used\r\nto define the contact between the IC packages and the circuit board.\r\n\r\n## Starting MAPDL as a service and importing an external model\r\n"
+ "# Setting up model\n",
+ "\n",
+ "The original FE model is given in the Ansys Mechanical APDL Technology\n",
+ "Showcase Manual. The .cdb contains a FE model of a single circuit board.\n",
+ "The model is meshed with SOLID186, SHELL181 and BEAM188 elements. All\n",
+ "components of the PCB model is assigned with linear elastic isotropic\n",
+ "materials. Bonded and flexible surface-to-surface contact pairs are used\n",
+ "to define the contact between the IC packages and the circuit board.\n",
+ "\n",
+ "## Starting MAPDL as a service and importing an external model\n"
]
},
{
@@ -33,14 +53,35 @@
},
"outputs": [],
"source": [
- "import matplotlib.pyplot as plt\n\nfrom ansys.mapdl.core import launch_mapdl\nfrom ansys.mapdl.core.examples import download_tech_demo_data\n\n# start MAPDL as a service\nmapdl = launch_mapdl()\nprint(mapdl)\n\n# read model of single circuit board\n# download the cdb file\npcb_mesh_file = download_tech_demo_data(\"td-20\", \"pcb_mesh_file.cdb\")\n\n# enter preprocessor and read in cdb\nmapdl.prep7()\nmapdl.cdread(\"COMB\", pcb_mesh_file)\nmapdl.allsel()\nmapdl.eplot(background=\"w\")\nmapdl.cmsel(\"all\")"
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "from ansys.mapdl.core import launch_mapdl\n",
+ "from ansys.mapdl.core.examples import download_tech_demo_data\n",
+ "\n",
+ "# start MAPDL as a service\n",
+ "mapdl = launch_mapdl()\n",
+ "print(mapdl)\n",
+ "\n",
+ "# read model of single circuit board\n",
+ "# download the cdb file\n",
+ "pcb_mesh_file = download_tech_demo_data(\"td-20\", \"pcb_mesh_file.cdb\")\n",
+ "\n",
+ "# enter preprocessor and read in cdb\n",
+ "mapdl.prep7()\n",
+ "mapdl.cdread(\"COMB\", pcb_mesh_file)\n",
+ "mapdl.allsel()\n",
+ "mapdl.eplot(background=\"w\")\n",
+ "mapdl.cmsel(\"all\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Creating the complete layered model\r\n\r\nThe original model will be duplicated to create a layered PCB of three\r\nlayers that are binded together.\r\n"
+ "# Creating the complete layered model\n",
+ "\n",
+ "The original model will be duplicated to create a layered PCB of three\n",
+ "layers that are binded together.\n"
]
},
{
@@ -51,14 +92,75 @@
},
"outputs": [],
"source": [
- "# duplicate single PCB to get three layers\n# get the maximum node number for the single layers PCB in the input file\nmax_nodenum = mapdl.get(\"max_nodenum\", \"node\", \"\", \"num\", \"max\")\n\n# generate additional PCBs offset by 20 mm in the -y direction\nmapdl.egen(3, max_nodenum, \"all\", dy=-20)\n\n\n# bind the three layers together\n# select components of interest\nmapdl.cmsel(\"s\", \"N_JOINT_BOARD\")\nmapdl.cmsel(\"a\", \"N_JOINT_LEGS\")\nmapdl.cmsel(\"a\", \"N_BASE\")\n\n# get number of currently selected nodes\nnb_selected_nodes = mapdl.mesh.n_node\ncurrent_node = 0\nqueries = mapdl.queries\n\n# also select similar nodes for copies of the single PCB\n# and couple all dofs at the interface\nfor node_id in range(1, nb_selected_nodes + 1):\n current_node = queries.ndnext(current_node)\n mapdl.nsel(\"a\", \"node\", \"\", current_node + max_nodenum)\n mapdl.nsel(\"a\", \"node\", \"\", current_node + 2 * max_nodenum)\nmapdl.cpintf(\"all\")\n\n# define fixed support boundary condition\n# get max coupled set number\ncp_max = mapdl.get(\"cp_max\", \"cp\", 0, \"max\")\n\n# unselect nodes scoped in CP equations\nmapdl.nsel(\"u\", \"cp\", \"\", 1, \"cp_max\")\n\n# create named selection for base excitation\nmapdl.cm(\"n_base_excite\", \"node\")\n\n# fix displacement for base excitation nodes\nmapdl.d(\"all\", \"all\")\n\n# select all and plot the model using MAPDL's plotter and VTK's\nmapdl.allsel(\"all\")\nmapdl.cmsel(\"all\")\nmapdl.graphics(\"power\")\nmapdl.rgb(\"index\", 100, 100, 100, 0)\nmapdl.rgb(\"index\", 80, 80, 80, 13)\nmapdl.rgb(\"index\", 60, 60, 60, 14)\nmapdl.rgb(\"index\", 0, 0, 0, 15)\nmapdl.triad(\"rbot\")\nmapdl.pnum(\"type\", 1)\nmapdl.number(1)\nmapdl.hbc(1, \"on\")\nmapdl.pbc(\"all\", \"\", 1)\nmapdl.view(1, 1, 1, 1)\n# mapdl.eplot(vtk=False)\nmapdl.eplot(vtk=True)"
+ "# duplicate single PCB to get three layers\n",
+ "# get the maximum node number for the single layers PCB in the input file\n",
+ "max_nodenum = mapdl.get(\"max_nodenum\", \"node\", \"\", \"num\", \"max\")\n",
+ "\n",
+ "# generate additional PCBs offset by 20 mm in the -y direction\n",
+ "mapdl.egen(3, max_nodenum, \"all\", dy=-20)\n",
+ "\n",
+ "\n",
+ "# bind the three layers together\n",
+ "# select components of interest\n",
+ "mapdl.cmsel(\"s\", \"N_JOINT_BOARD\")\n",
+ "mapdl.cmsel(\"a\", \"N_JOINT_LEGS\")\n",
+ "mapdl.cmsel(\"a\", \"N_BASE\")\n",
+ "\n",
+ "# get number of currently selected nodes\n",
+ "nb_selected_nodes = mapdl.mesh.n_node\n",
+ "current_node = 0\n",
+ "queries = mapdl.queries\n",
+ "\n",
+ "# also select similar nodes for copies of the single PCB\n",
+ "# and couple all dofs at the interface\n",
+ "for node_id in range(1, nb_selected_nodes + 1):\n",
+ " current_node = queries.ndnext(current_node)\n",
+ " mapdl.nsel(\"a\", \"node\", \"\", current_node + max_nodenum)\n",
+ " mapdl.nsel(\"a\", \"node\", \"\", current_node + 2 * max_nodenum)\n",
+ "mapdl.cpintf(\"all\")\n",
+ "\n",
+ "# define fixed support boundary condition\n",
+ "# get max coupled set number\n",
+ "cp_max = mapdl.get(\"cp_max\", \"cp\", 0, \"max\")\n",
+ "\n",
+ "# unselect nodes scoped in CP equations\n",
+ "mapdl.nsel(\"u\", \"cp\", \"\", 1, \"cp_max\")\n",
+ "\n",
+ "# create named selection for base excitation\n",
+ "mapdl.cm(\"n_base_excite\", \"node\")\n",
+ "\n",
+ "# fix displacement for base excitation nodes\n",
+ "mapdl.d(\"all\", \"all\")\n",
+ "\n",
+ "# select all and plot the model using MAPDL's plotter and VTK's\n",
+ "mapdl.allsel(\"all\")\n",
+ "mapdl.cmsel(\"all\")\n",
+ "mapdl.graphics(\"power\")\n",
+ "mapdl.rgb(\"index\", 100, 100, 100, 0)\n",
+ "mapdl.rgb(\"index\", 80, 80, 80, 13)\n",
+ "mapdl.rgb(\"index\", 60, 60, 60, 14)\n",
+ "mapdl.rgb(\"index\", 0, 0, 0, 15)\n",
+ "mapdl.triad(\"rbot\")\n",
+ "mapdl.pnum(\"type\", 1)\n",
+ "mapdl.number(1)\n",
+ "mapdl.hbc(1, \"on\")\n",
+ "mapdl.pbc(\"all\", \"\", 1)\n",
+ "mapdl.view(1, 1, 1, 1)\n",
+ "# mapdl.eplot(vtk=False)\n",
+ "mapdl.eplot(vtk=True)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Modal Analysis\r\n\r\n## Run modal analysis\r\n\r\nA modal analysis is run using Block Lanzos. Only 10 modes are extracted\r\nfor the sake of run times, but using a higher number of nodes is\r\nrecommended (suggestion: 300 modes).\r\n"
+ "# Modal Analysis\n",
+ "\n",
+ "## Run modal analysis\n",
+ "\n",
+ "A modal analysis is run using Block Lanzos. Only 10 modes are extracted\n",
+ "for the sake of run times, but using a higher number of nodes is\n",
+ "recommended (suggestion: 300 modes).\n"
]
},
{
@@ -69,14 +171,29 @@
},
"outputs": [],
"source": [
- "# enter solution processor and define analysis settings\nmapdl.slashsolu()\nmapdl.antype(\"modal\")\n# set number of modes to extract\n# using a higher number of modes is recommended\nnb_modes = 10\n# use Block Lanzos to extract specified number of modes\nmapdl.modopt(\"lanb\", nb_modes)\nmapdl.mxpand(nb_modes)\noutput = mapdl.solve()\nprint(output)"
+ "# enter solution processor and define analysis settings\n",
+ "mapdl.slashsolu()\n",
+ "mapdl.antype(\"modal\")\n",
+ "# set number of modes to extract\n",
+ "# using a higher number of modes is recommended\n",
+ "nb_modes = 10\n",
+ "# use Block Lanzos to extract specified number of modes\n",
+ "mapdl.modopt(\"lanb\", nb_modes)\n",
+ "mapdl.mxpand(nb_modes)\n",
+ "output = mapdl.solve()\n",
+ "print(output)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Post-processing the modal results\r\n\r\nThis sections illustrates different methods to post-process the results\r\nof the modal analysis : PyMAPDL method, PyMAPDL result reader,\r\nPyDPF-Post and PyDPF-Core. All methods lead to the same result and are\r\njust given as an example of how each module can be used.\r\n"
+ "# Post-processing the modal results\n",
+ "\n",
+ "This sections illustrates different methods to post-process the results\n",
+ "of the modal analysis : PyMAPDL method, PyMAPDL result reader,\n",
+ "PyDPF-Post and PyDPF-Core. All methods lead to the same result and are\n",
+ "just given as an example of how each module can be used.\n"
]
},
{
@@ -87,14 +204,21 @@
},
"outputs": [],
"source": [
- "# using MAPDL methods\nmapdl.post1()\nmapdl.set(1, 1)\nmapdl.plnsol(\"u\", \"sum\")"
+ "# using MAPDL methods\n",
+ "mapdl.post1()\n",
+ "mapdl.set(1, 1)\n",
+ "mapdl.plnsol(\"u\", \"sum\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Using PyMAPDL result reader\r\n\r\n*Not recommended* - PyMAPDL reader library is in process to being\r\ndeprecated. It is recommended to use [DPF\r\nPost](https://postdocs.pyansys.com/).\r\n"
+ "# Using PyMAPDL result reader\n",
+ "\n",
+ "*Not recommended* - PyMAPDL reader library is in process to being\n",
+ "deprecated. It is recommended to use [DPF\n",
+ "Post](https://postdocs.pyansys.com/).\n"
]
},
{
@@ -105,14 +229,15 @@
},
"outputs": [],
"source": [
- "mapdl_result = mapdl.result\nmapdl_result.plot_nodal_displacement(0)"
+ "mapdl_result = mapdl.result\n",
+ "mapdl_result.plot_nodal_displacement(0)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Using DPF-Post\r\n"
+ "# Using DPF-Post\n"
]
},
{
@@ -123,14 +248,21 @@
},
"outputs": [],
"source": [
- "from ansys.dpf import post\n\nsolution_path = mapdl.result_file\nsolution = post.load_solution(solution_path)\nprint(solution)\ndisplacement = solution.displacement(time_scoping=1)\ntotal_deformation = displacement.norm\ntotal_deformation.plot_contour(show_edges=True, background=\"w\")"
+ "from ansys.dpf import post\n",
+ "\n",
+ "solution_path = mapdl.result_file\n",
+ "solution = post.load_solution(solution_path)\n",
+ "print(solution)\n",
+ "displacement = solution.displacement(time_scoping=1)\n",
+ "total_deformation = displacement.norm\n",
+ "total_deformation.plot_contour(show_edges=True, background=\"w\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Using DPF-Core\r\n"
+ "# Using DPF-Core\n"
]
},
{
@@ -141,14 +273,25 @@
},
"outputs": [],
"source": [
- "from ansys.dpf import core\n\nmodel = core.Model(solution_path)\nresults = model.results\nprint(results)\ndisplacements = results.displacement()\ntotal_def = core.operators.math.norm_fc(displacements)\ntotal_def_container = total_def.outputs.fields_container()\nmesh = model.metadata.meshed_region\nmesh.plot(total_def_container.get_field_by_time_id(1))"
+ "from ansys.dpf import core\n",
+ "\n",
+ "model = core.Model(solution_path)\n",
+ "results = model.results\n",
+ "print(results)\n",
+ "displacements = results.displacement()\n",
+ "total_def = core.operators.math.norm_fc(displacements)\n",
+ "total_def_container = total_def.outputs.fields_container()\n",
+ "mesh = model.metadata.meshed_region\n",
+ "mesh.plot(total_def_container.get_field_by_time_id(1))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Run PSD analysis\r\n\r\nThe response spectrum analysis is defined, solved and post-processed.\r\n"
+ "# Run PSD analysis\n",
+ "\n",
+ "The response spectrum analysis is defined, solved and post-processed.\n"
]
},
{
@@ -159,21 +302,73 @@
},
"outputs": [],
"source": [
- "# define PSD analysis with input spectrum\nmapdl.slashsolu()\nmapdl.antype(\"spectr\")\n\n# power spectral density\nmapdl.spopt(\"psd\")\n\n# use input table 1 with acceleration spectrum in terms of acceleration due to gravity\nmapdl.psdunit(1, \"accg\", 9.81 * 1000)\n\n# define the frequency points in the input table 1\nmapdl.psdfrq(1, \"\", 1, 40, 50, 70.71678, 100, 700, 900)\n\n# define the PSD values in the input table 1\nmapdl.psdval(1, 0.01, 0.01, 0.1, 1, 10, 10, 1)\n\n# set the damping ratio as 5%\nmapdl.dmprat(0.05)\n\n# apply base excitation on the set of nodes N_BASE_EXCITE in the y-direction from table 1\nmapdl.d(\"N_BASE_EXCITE\", \"uy\", 1)\n\n# calculate the participation factor for PSD with base excitation from input table 1\nmapdl.pfact(1, \"base\")\n\n# write the displacent solution relative to the base excitation to the results file from the PSD analysis\nmapdl.psdres(\"disp\", \"rel\")\n\n# write the absolute velocity solution to the results file from the PSD analysis\nmapdl.psdres(\"velo\", \"abs\")\n\n# write the absolute acceleration solution to the results file from the PSD analysis\nmapdl.psdres(\"acel\", \"abs\")\n\n# combine only those modes whose significance level exceeds 0.0001\nmapdl.psdcom()\noutput = mapdl.solve()\nprint(output)"
+ "# define PSD analysis with input spectrum\n",
+ "mapdl.slashsolu()\n",
+ "mapdl.antype(\"spectr\")\n",
+ "\n",
+ "# power spectral density\n",
+ "mapdl.spopt(\"psd\")\n",
+ "\n",
+ "# use input table 1 with acceleration spectrum in terms of acceleration due to gravity\n",
+ "mapdl.psdunit(1, \"accg\", 9.81 * 1000)\n",
+ "\n",
+ "# define the frequency points in the input table 1\n",
+ "mapdl.psdfrq(1, \"\", 1, 40, 50, 70.71678, 100, 700, 900)\n",
+ "\n",
+ "# define the PSD values in the input table 1\n",
+ "mapdl.psdval(1, 0.01, 0.01, 0.1, 1, 10, 10, 1)\n",
+ "\n",
+ "# set the damping ratio as 5%\n",
+ "mapdl.dmprat(0.05)\n",
+ "\n",
+ "# apply base excitation on the set of nodes N_BASE_EXCITE in the y-direction from table 1\n",
+ "mapdl.d(\"N_BASE_EXCITE\", \"uy\", 1)\n",
+ "\n",
+ "# calculate the participation factor for PSD with base excitation from input table 1\n",
+ "mapdl.pfact(1, \"base\")\n",
+ "\n",
+ "# write the displacent solution relative to the base excitation to the results file from the PSD analysis\n",
+ "mapdl.psdres(\"disp\", \"rel\")\n",
+ "\n",
+ "# write the absolute velocity solution to the results file from the PSD analysis\n",
+ "mapdl.psdres(\"velo\", \"abs\")\n",
+ "\n",
+ "# write the absolute acceleration solution to the results file from the PSD analysis\n",
+ "mapdl.psdres(\"acel\", \"abs\")\n",
+ "\n",
+ "# combine only those modes whose significance level exceeds 0.0001\n",
+ "mapdl.psdcom()\n",
+ "output = mapdl.solve()\n",
+ "print(output)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Post-process PSD analysis\r\n\r\nThe response spectrum analysis is post-processed. First, the standard\r\nMAPDL POST1 postprocessor is used. Then, the MAPDL time-history POST26\r\npostprocessor is used to generate the response power spectral density.\r\n\r\n::: note\r\n::: title\r\nNote\r\n:::\r\n\r\nThe graph generated through POST26 is exported as a picture in the\r\nworking directory. Finally, the results from POST26 are saved to Python\r\nvariables to be plotted in the Python environment with the use of\r\nMatplotlib library.\r\n:::\r\n"
+ "# Post-process PSD analysis\n",
+ "\n",
+ "The response spectrum analysis is post-processed. First, the standard\n",
+ "MAPDL POST1 postprocessor is used. Then, the MAPDL time-history POST26\n",
+ "postprocessor is used to generate the response power spectral density.\n",
+ "\n",
+ "::: note\n",
+ "::: title\n",
+ "Note\n",
+ ":::\n",
+ "\n",
+ "The graph generated through POST26 is exported as a picture in the\n",
+ "working directory. Finally, the results from POST26 are saved to Python\n",
+ "variables to be plotted in the Python environment with the use of\n",
+ "Matplotlib library.\n",
+ ":::\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Post-process PSD analysis in POST1\r\n"
+ "# Post-process PSD analysis in POST1\n"
]
},
{
@@ -184,14 +379,18 @@
},
"outputs": [],
"source": [
- "mapdl.post1()\nmapdl.set(1, 1)\nmapdl.plnsol(\"u\", \"sum\")\nmapdl.set(\"last\")\nmapdl.plnsol(\"u\", \"sum\")"
+ "mapdl.post1()\n",
+ "mapdl.set(1, 1)\n",
+ "mapdl.plnsol(\"u\", \"sum\")\n",
+ "mapdl.set(\"last\")\n",
+ "mapdl.plnsol(\"u\", \"sum\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Post-process PSD analysis in POST26 (time-history post-processing)\r\n"
+ "# Post-process PSD analysis in POST26 (time-history post-processing)\n"
]
},
{
@@ -202,14 +401,43 @@
},
"outputs": [],
"source": [
- "mapdl.post26()\n\n# allow storage for 200 variables\nmapdl.numvar(200)\nmapdl.cmsel(\"s\", \"MY_MONITOR\")\nmonitored_node = mapdl.queries.ndnext(0)\nmapdl.store(\"psd\")\n\n# store the psd analysis u_y data for the node MYMONITOR as the reference no 2\nmapdl.nsol(2, monitored_node, \"u\", \"y\")\n\n# compute the response power spectral density for displacement associated with variable 2\nmapdl.rpsd(3, 2)\nmapdl.show(\"png\")\n\n# plot the variable 3\nmapdl.plvar(3)\n\n# print the variable 3\nmapdl.prvar(3)\n\n# x-axis is set for Log X scale\nmapdl.gropt(\"logx\", 1)\n\n# y-axis is set for Log X scale\nmapdl.gropt(\"logy\", 1)\n\n# plot the variable 3\nmapdl.plvar(3)\nmapdl.show(\"close\")"
+ "mapdl.post26()\n",
+ "\n",
+ "# allow storage for 200 variables\n",
+ "mapdl.numvar(200)\n",
+ "mapdl.cmsel(\"s\", \"MY_MONITOR\")\n",
+ "monitored_node = mapdl.queries.ndnext(0)\n",
+ "mapdl.store(\"psd\")\n",
+ "\n",
+ "# store the psd analysis u_y data for the node MYMONITOR as the reference no 2\n",
+ "mapdl.nsol(2, monitored_node, \"u\", \"y\")\n",
+ "\n",
+ "# compute the response power spectral density for displacement associated with variable 2\n",
+ "mapdl.rpsd(3, 2)\n",
+ "mapdl.show(\"png\")\n",
+ "\n",
+ "# plot the variable 3\n",
+ "mapdl.plvar(3)\n",
+ "\n",
+ "# print the variable 3\n",
+ "mapdl.prvar(3)\n",
+ "\n",
+ "# x-axis is set for Log X scale\n",
+ "mapdl.gropt(\"logx\", 1)\n",
+ "\n",
+ "# y-axis is set for Log X scale\n",
+ "mapdl.gropt(\"logy\", 1)\n",
+ "\n",
+ "# plot the variable 3\n",
+ "mapdl.plvar(3)\n",
+ "mapdl.show(\"close\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Post-process PSD analysis using Matplotlib\r\n"
+ "# Post-process PSD analysis using Matplotlib\n"
]
},
{
@@ -220,14 +448,29 @@
},
"outputs": [],
"source": [
- "# store MAPDL results to python variables\nmapdl.dim(\"frequencies\", \"array\", 4000, 1)\nmapdl.dim(\"response\", \"array\", 4000, 1)\nmapdl.vget(\"frequencies(1)\", 1)\nmapdl.vget(\"response(1)\", 3)\nfrequencies = mapdl.parameters[\"frequencies\"]\nresponse = mapdl.parameters[\"response\"]\n\n# use Matplotlib to create graph\nfig = plt.figure()\nax = fig.add_subplot(111)\nplt.xscale(\"log\")\nplt.yscale(\"log\")\nax.plot(frequencies, response)\nax.set_xlabel(\"Frequencies\")\nax.set_ylabel(\"Response power spectral density\")"
+ "# store MAPDL results to python variables\n",
+ "mapdl.dim(\"frequencies\", \"array\", 4000, 1)\n",
+ "mapdl.dim(\"response\", \"array\", 4000, 1)\n",
+ "mapdl.vget(\"frequencies(1)\", 1)\n",
+ "mapdl.vget(\"response(1)\", 3)\n",
+ "frequencies = mapdl.parameters[\"frequencies\"]\n",
+ "response = mapdl.parameters[\"response\"]\n",
+ "\n",
+ "# use Matplotlib to create graph\n",
+ "fig = plt.figure()\n",
+ "ax = fig.add_subplot(111)\n",
+ "plt.xscale(\"log\")\n",
+ "plt.yscale(\"log\")\n",
+ "ax.plot(frequencies, response)\n",
+ "ax.set_xlabel(\"Frequencies\")\n",
+ "ax.set_ylabel(\"Response power spectral density\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Exit MAPDL\r\n"
+ "Exit MAPDL\n"
]
},
{
@@ -244,7 +487,7 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Python 3",
+ "display_name": ".venv",
"language": "python",
"name": "python3"
},
@@ -258,7 +501,12 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.9.7"
+ "version": "3.10.8 (tags/v3.10.8:aaaf517, Oct 11 2022, 16:50:30) [MSC v.1933 64 bit (AMD64)]"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "25ee88bf99fdb66867962637ab0ae1b8de27a896c2eb41e2fbf5e9143b58a926"
+ }
}
},
"nbformat": 4,
diff --git a/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.rst b/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.rst
index bcc0e6bfd..bee1dc451 100644
--- a/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.rst
+++ b/doc/source/technology_showcase_examples/techdemo-20/ex_20-tecPCB.rst
@@ -2,22 +2,14 @@
.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
-.. "examples\examples\technology_showcase_examples-techdemo\20-example-technology-showcase-dynamic-simulation-PCB.py"
+.. "technology_showcase_examples\techdemo-20\ex_20-tecPCB.py"
.. LINE NUMBERS ARE GIVEN BELOW.
-.. only:: html
-
- .. note::
- :class: sphx-glr-download-link-note
-
- Click :ref:`here
`
- to download the full example code
-
.. rst-class:: sphx-glr-example-title
-.. _sphx_glr_download_examples_examples_technology_showcase_examples-techdemo_20-example-technology-showcase-dynamic-simulation-PCB.py:
+.. _sphx_glr_download_examples_examples_technology_showcase_examples-ex_20-tecPCB.py:
-.. _sphx_glr_ex_20-tecPCB.py:
+.. _sphx_glr_ex_20-tecPCB.rst:
.. _ref_dynamic_simulation_printed_circuit_board:
.. _tech_demo_20:
@@ -53,7 +45,7 @@ Starting MAPDL as a service and importing an external model
.. GENERATED FROM PYTHON SOURCE LINES 33-54
-.. code-block:: default
+.. code:: ipython3
# sphinx_gallery_thumbnail_path = '_static/tse20_setup.png'
@@ -87,8 +79,6 @@ Starting MAPDL as a service and importing an external model
.. rst-class:: sphx-glr-script-out
- Out:
-
.. code-block:: none
Product: Ansys Mechanical Enterprise
@@ -109,7 +99,7 @@ that are binded together.
.. GENERATED FROM PYTHON SOURCE LINES 59-117
-.. code-block:: default
+.. code:: ipython3
# duplicate single PCB to get three layers
@@ -175,8 +165,6 @@ that are binded together.
:alt: 20 example technology showcase dynamic simulation PCB
:figclass: sphx-glr-single-img
-.. rst-class:: sphx-glr-script-out
-
.. GENERATED FROM PYTHON SOURCE LINES 118-128
@@ -193,7 +181,7 @@ number of nodes is recommended (suggestion: 300 modes).
.. GENERATED FROM PYTHON SOURCE LINES 128-142
-.. code-block:: default
+.. code:: ipython3
# enter solution processor and define analysis settings
@@ -209,14 +197,8 @@ number of nodes is recommended (suggestion: 300 modes).
print(output)
-
-
-
-
.. rst-class:: sphx-glr-script-out
- Out:
-
.. code-block:: none
*** NOTE *** CP = 0.781 TIME= 06:52:51
@@ -1971,7 +1953,7 @@ example of how each module can be used.
.. GENERATED FROM PYTHON SOURCE LINES 149-156
-.. code-block:: default
+.. code:: ipython3
# using MAPDL methods
@@ -1998,7 +1980,7 @@ It is recommended to use `DPF Post `_.
.. GENERATED FROM PYTHON SOURCE LINES 163-167
-.. code-block:: default
+.. code:: ipython3
mapdl_result = mapdl.result
@@ -2020,7 +2002,7 @@ Using DPF-Post
.. GENERATED FROM PYTHON SOURCE LINES 171-181
-.. code-block:: default
+.. code:: ipython3
from ansys.dpf import post
@@ -2043,8 +2025,6 @@ Using DPF-Post
.. rst-class:: sphx-glr-script-out
- Out:
-
.. code-block:: none
Modal Analysis Solution object.
@@ -2099,7 +2079,7 @@ Using DPF-Core
.. GENERATED FROM PYTHON SOURCE LINES 185-197
-.. code-block:: default
+.. code:: ipython3
from ansys.dpf import core
@@ -2122,8 +2102,6 @@ Using DPF-Core
.. rst-class:: sphx-glr-script-out
- Out:
-
.. code-block:: none
Modal analysis
@@ -2144,7 +2122,7 @@ The response spectrum analysis is defined, solved and post-processed.
.. GENERATED FROM PYTHON SOURCE LINES 201-241
-.. code-block:: default
+.. code:: ipython3
# define PSD analysis with input spectrum
@@ -2192,8 +2170,6 @@ The response spectrum analysis is defined, solved and post-processed.
.. rst-class:: sphx-glr-script-out
- Out:
-
.. code-block:: none
*** NOTE *** CP = 16.328 TIME= 06:53:12
@@ -2486,7 +2462,7 @@ Post-process PSD analysis in POST1
.. GENERATED FROM PYTHON SOURCE LINES 259-266
-.. code-block:: default
+.. code:: ipython3
mapdl.post1()
@@ -2510,7 +2486,7 @@ Post-process PSD analysis in POST26 (time-history post-processing)
.. GENERATED FROM PYTHON SOURCE LINES 269-301
-.. code-block:: default
+.. code:: ipython3
mapdl.post26()
@@ -2558,7 +2534,7 @@ Post-process PSD analysis using Matplotlib
.. GENERATED FROM PYTHON SOURCE LINES 304-322
-.. code-block:: default
+.. code:: ipython3
# store MAPDL results to python variables
@@ -2590,7 +2566,7 @@ Exit MAPDL
.. GENERATED FROM PYTHON SOURCE LINES 324-325
-.. code-block:: default
+.. code:: ipython3
mapdl.exit()
@@ -2606,7 +2582,7 @@ Exit MAPDL
**Total running time of the script:** ( 0 minutes 44.344 seconds)
-.. _sphx_glr_download_examples_gallery_examples_06-verif-manual_20-example-technology-showcase-dynamic-simulation-PCB.py:
+.. _sphx_glr_download_examples_gallery_examples_06-verif-ex_20-tecPCB.py:
.. only :: html
diff --git a/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.ipynb b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.ipynb
new file mode 100644
index 000000000..c6558fde1
--- /dev/null
+++ b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.ipynb
@@ -0,0 +1,951 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# Cardiovascular Stent Simulation"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "This example problem shows how to simulate stent-artery interaction during and after stent\n",
+ "placement in an occluded artery.\n",
+ "The analysis exposes advanced modeling techniques using PyMAPDL such as:\n",
+ "* Contact\n",
+ "* Element birth and death\n",
+ "* Mixed u-P formulation\n",
+ "* Nonlinear stabilization\n",
+ "\n",
+ "This example is inspired from the model and analysis defined in Chapter 25 of the Mechanical\n",
+ "APDL Technology Showcase Manual."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "import pyvista\n",
+ "import panel\n",
+ "pyvista.set_jupyter_backend('panel')\n",
+ "pyvista.global_theme.window_size = [600, 400]\n",
+ "pyvista.global_theme.background = 'grey'"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Starting MAPDL as a service"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# starting MAPDL as a service and importing an external model\n",
+ "from ansys.mapdl.core import launch_mapdl\n",
+ "\n",
+ "# start MAPDL as a service\n",
+ "mapdl = launch_mapdl()\n",
+ "print(mapdl)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Setting up the model"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Defining material properties
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# define 316L Stainless steel\n",
+ "mapdl.prep7()\n",
+ "mapdl.mptemp()\n",
+ "mapdl.mptemp(sloc=\"1\", t1=\"0\")\n",
+ "mapdl.mpdata(lab=\"EX\", mat=\"1\", c1=\"200e3\")\n",
+ "mapdl.mpdata(lab=\"PRXY\", mat=\"1\", c1=\"0.3\")\n",
+ "mapdl.mptemp()\n",
+ "mapdl.mptemp(sloc=\"1\", t1=\"0\")\n",
+ "mapdl.mpdata(lab=\"DENS\", mat=\"1\", c1=\"8000e-9\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Defining element types"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# for straight line segments\n",
+ "mapdl.et(itype=\"1\", ename=\"beam189\")\n",
+ "mapdl.sectype(secid=\"1\", type_=\"beam\", subtype=\"csolid\")\n",
+ "mapdl.secdata(val1=0.05)\n",
+ "\n",
+ "# for arcs\n",
+ "mapdl.et(itype=\"2\", ename=\"beam189\")\n",
+ "mapdl.sectype(secid=\"2\", type_=\"beam\", subtype=\"csolid\")\n",
+ "mapdl.secdata(val1=0.05)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Defining 5-parameter Mooney-Rivlin hyperelastic artery material model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "c10 = 18.90e-3\n",
+ "c01 = 2.75e-3\n",
+ "c20 = 590.43e-3\n",
+ "c11 = 857.2e-3\n",
+ "nu1 = 0.49\n",
+ "dd = 2 * (1 - 2 * nu1) / (c10 + c01)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.tb(lab=\"hyper\", mat=\"2\", npts=\"5\", tbopt=\"mooney\")\n",
+ "mapdl.tbdata(stloc=\"1\", c1=\"c10\", c2=\"c01\", c3=\"c20\", c4=\"c11\", c6=\"dd\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Defining linear elastic material model for stiff calcified plaque"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.mp(lab=\"EX\", mat=\"3\", c0=\".00219e3\")\n",
+ "mapdl.mp(lab=\"NUXY\", mat=\"3\", c0=\"0.49\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Define Solid185 element type to mesh both the artery and plaque"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# for artery\n",
+ "mapdl.et(itype=\"9\", ename=\"SOLID185\")\n",
+ "mapdl.keyopt(\n",
+ " itype=\"9\", knum=\"6\", value=\"1\") # Use mixed u-P formulation to avoid locking\n",
+ "mapdl.keyopt(itype=\"9\", knum=\"2\", value=\"3\") # Use Simplified Enhanced Strain method\n",
+ "\n",
+ "# for plaque\n",
+ "mapdl.et(itype=\"16\", ename=\"SOLID185\")\n",
+ "mapdl.keyopt(itype=\"16\", knum=\"2\", value=\"0\") # Use B-bar"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Defining settings to model the stent, the artery and the plaque\n",
+ "\n",
+ "Use force-distributed boundary constraints on 2 sides of artery wall to allow\n",
+ "for radial expansion of tissue without rigid body motion."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Settings for MPC Surface-based, force-distributed contact on proximal plane parallel to x-y plane"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.mat(\"2\")\n",
+ "mapdl.r(nset=\"3\")\n",
+ "mapdl.real(nset=\"3\")\n",
+ "mapdl.et(itype=\"3\", ename=\"170\")\n",
+ "mapdl.et(itype=\"4\", ename=\"174\")\n",
+ "mapdl.keyopt(itype=\"4\", knum=\"12\", value=\"5\")\n",
+ "mapdl.keyopt(itype=\"4\", knum=\"4\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"4\", knum=\"2\", value=\"2\")\n",
+ "mapdl.keyopt(itype=\"3\", knum=\"2\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"3\", knum=\"4\", value=\"111111\")\n",
+ "mapdl.type(itype=\"3\")\n",
+ "\n",
+ "mapdl.mat(\"2\")\n",
+ "mapdl.r(nset=\"4\")\n",
+ "mapdl.real(nset=\"4\")\n",
+ "mapdl.et(itype=\"5\", ename=\"170\")\n",
+ "mapdl.et(itype=\"6\", ename=\"174\")\n",
+ "mapdl.keyopt(itype=\"6\", knum=\"12\", value=\"5\")\n",
+ "mapdl.keyopt(itype=\"6\", knum=\"4\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"6\", knum=\"2\", value=\"2\")\n",
+ "mapdl.keyopt(itype=\"5\", knum=\"2\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"5\", knum=\"4\", value=\"111111\")\n",
+ "mapdl.type(itype=\"5\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Settings for standard contact between stent and inner plaque wall contact surface"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.mp(lab=\"MU\", mat=\"1\", c0=\"0\")\n",
+ "mapdl.mat(\"1\")\n",
+ "mapdl.mp(lab=\"EMIS\", mat=\"1\", c0=\"7.88860905221e-31\")\n",
+ "mapdl.r(nset=\"6\")\n",
+ "mapdl.real(nset=\"6\")\n",
+ "mapdl.et(itype=\"10\", ename=\"170\")\n",
+ "mapdl.et(itype=\"11\", ename=\"177\")\n",
+ "mapdl.r(nset=\"6\", r3=\"1.0\", r4=\"1.0\", r5=\"0\")\n",
+ "mapdl.rmore(r9=\"1.0E20\", r10=\"0.0\", r11=\"1.0\")\n",
+ "mapdl.rmore(r7=\"0.0\", r8=\"0\", r9=\"1.0\", r10=\"0.05\", r11=\"1.0\", r12=\"0.5\")\n",
+ "mapdl.rmore(r7=\"0\", r8=\"1.0\", r9=\"1.0\", r10=\"0.0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"5\", value=\"0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"7\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"8\", value=\"0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"9\", value=\"0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"10\", value=\"2\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"11\", value=\"0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"12\", value=\"0\")\n",
+ "mapdl.keyopt(itype=\"11\", knum=\"2\", value=\"3\")\n",
+ "mapdl.keyopt(itype=\"10\", knum=\"5\", value=\"0\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Settings for MPC based, force-distributed constraint on proximal stent nodes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.mat(\"1\")\n",
+ "mapdl.r(nset=\"7\")\n",
+ "mapdl.real(nset=\"7\")\n",
+ "mapdl.et(itype=\"12\", ename=\"170\")\n",
+ "mapdl.et(itype=\"13\", ename=\"175\")\n",
+ "mapdl.keyopt(itype=\"13\", knum=\"12\", value=\"5\")\n",
+ "mapdl.keyopt(itype=\"13\", knum=\"4\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"13\", knum=\"2\", value=\"2\")\n",
+ "mapdl.keyopt(itype=\"12\", knum=\"2\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"12\", knum=\"4\", value=\"111111\")\n",
+ "mapdl.type(itype=\"12\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Settings for MPC based, force-distributed constraint on distal stent nodes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.mat(\"1\")\n",
+ "mapdl.r(nset=\"8\")\n",
+ "mapdl.real(nset=\"8\")\n",
+ "mapdl.et(itype=\"14\", ename=\"170\")\n",
+ "mapdl.et(itype=\"15\", ename=\"175\")\n",
+ "mapdl.keyopt(itype=\"15\", knum=\"12\", value=\"5\")\n",
+ "mapdl.keyopt(itype=\"15\", knum=\"4\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"15\", knum=\"2\", value=\"2\")\n",
+ "mapdl.keyopt(itype=\"14\", knum=\"2\", value=\"1\")\n",
+ "mapdl.keyopt(itype=\"14\", knum=\"4\", value=\"111111\")\n",
+ "mapdl.type(itype=\"14\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Reading the geometry file"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.cdread(option=\"db\", fname=\"stent\", ext=\"cdb\")\n",
+ "mapdl.allsel(labt=\"all\")\n",
+ "mapdl.finish()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Static Analysis\n",
+ "\n",
+ "Run static analysis"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# enter solution processor and define analysis settings\n",
+ "mapdl.run(\"/solu\")\n",
+ "mapdl.antype(antype=\"0\")\n",
+ "mapdl.nlgeom(key=\"on\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Apply Load Step 1: Balloon angioplasty of the artery to expand it past the radius of the stent - IGNORE STENT"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.nsubst(nsbstp=\"20\", nsbmx=\"20\")\n",
+ "mapdl.nropt(option1=\"full\")\n",
+ "mapdl.cncheck(option=\"auto\")\n",
+ "mapdl.esel(type_=\"s\", item=\"type\", vmin=\"11\")\n",
+ "mapdl.cm(cname=\"contact2\", entity=\"elem\")\n",
+ "mapdl.ekill(elem=\"contact2\") # Kill contact elements in stent-plaque contact \n",
+ " #pair so that the stent is ignored in the first loadstep\n",
+ "mapdl.nsel(type_=\"s\", item=\"loc\", comp=\"x\", vmin=\"0\", vmax=\"0.01e-3\")\n",
+ "mapdl.nsel(type_=\"r\", item=\"loc\", comp=\"y\", vmin=\"0\", vmax=\"0.01e-3\")\n",
+ "mapdl.d(node=\"all\", lab=\"all\")\n",
+ "mapdl.allsel()\n",
+ "\n",
+ "mapdl.sf(nlist=\"load\", lab=\"pres\", value=\"10e-2\") # Apply 0.1 Pa/mm^2 pressure to inner plaque wall\n",
+ "mapdl.allsel()\n",
+ "mapdl.nldiag(label=\"cont\", key=\"iter\")\n",
+ "mapdl.solve()\n",
+ "mapdl.save()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Apply Load Step 2: Reactivate contact between stent and plaque"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.ealive(elem=\"contact2\")\n",
+ "mapdl.allsel()\n",
+ "\n",
+ "mapdl.nsubst(nsbstp=\"2\", nsbmx=\"2\")\n",
+ "mapdl.save()\n",
+ "mapdl.solve()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Apply Load Step 3"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.nsubst(nsbstp=\"1\", nsbmx=\"1\", nsbmn=\"1\")\n",
+ "mapdl.solve()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Apply Load Step 4: Apply blood pressure (13.3 kPa) load to inner wall of plaque and allow the stent to act as a scaffold"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.nsubst(nsbstp=\"300\", nsbmx=\"3000\", nsbmn=\"30\")\n",
+ "mapdl.sf(nlist=\"load\", lab=\"pres\", value=\"13.3e-3\")\n",
+ "mapdl.allsel()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Apply stabilization with energy option"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.stabilize(key=\"const\", method=\"energy\", value=\"0.1\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Solve the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.solve()\n",
+ "mapdl.save()\n",
+ "mapdl.finish()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Post-processing the results\n",
+ "\n",
+ "This section illustrates the use of PyDPF-Core to post-process the results."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from ansys.dpf import core as dpf\n",
+ "from ansys.dpf.core import operators as ops"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Mesh of the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Loading the result file\n",
+ "model = dpf.Model(mapdl.result_file)\n",
+ "ds = dpf.DataSources(mapdl.result_file)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mesh = model.metadata.meshed_region\n",
+ "mesh.plot(vtk_export=True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Computed displacements of the model"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Collecting the computed displacement\n",
+ "u = model.results.displacement(time_scoping=[4]).eval()\n",
+ "\n",
+ "u[0].plot(deform_by = u[0])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Von Mises stress"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Collecting the computed stress\n",
+ "s_op = model.results.stress(time_scoping=[3])\n",
+ "s_op.inputs.requested_location.connect(dpf.locations.nodal)\n",
+ "s = s_op.eval()\n",
+ "\n",
+ "# Calculating Von Mises stress\n",
+ "s_VM = dpf.operators.invariant.von_mises_eqv_fc(fields_container=s)\n",
+ "s_VM_plot = s_VM.eval()\n",
+ "\n",
+ "s_VM_plot[0].plot(deform_by = u[0])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Computed displacements of the stent"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Creating the mesh associated to the stent\n",
+ "esco = mesh.named_selection(\"STENT\")\n",
+ "print(esco)\n",
+ "\n",
+ "# Transposing elemental location to nodal one\n",
+ "op = dpf.operators.scoping.transpose()\n",
+ "op.inputs.mesh_scoping.connect(esco)\n",
+ "op.inputs.meshed_region.connect(mesh)\n",
+ "op.inputs.inclusive.connect(1)\n",
+ "nsco = op.eval()\n",
+ "print(nsco)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Collecting the computed displacements of the stent\n",
+ "u_stent = model.results.displacement(mesh_scoping=nsco, time_scoping=[4])\n",
+ "u_stent = u_stent.outputs.fields_container()\n",
+ "\n",
+ "# Linking the stent mesh to the global one\n",
+ "op = dpf.operators.mesh.from_scoping() # operator instantiation\n",
+ "op.inputs.scoping.connect(nsco)\n",
+ "op.inputs.inclusive.connect(1)\n",
+ "op.inputs.mesh.connect(mesh)\n",
+ "mesh_sco = op.eval()\n",
+ "mesh_sco.plot(vtk_export=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "u_stent[0].meshed_region = mesh_sco\n",
+ "u_stent[0].plot(deformed_by=u_stent[0])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mesh.plot(color=\"w\", show_edges=True, text='Mesh of the model', )\n",
+ "mesh_sco.plot(color=\"black\", show_edges=True, text='Mesh of the stent')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Exit MAPDL"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "mapdl.exit()"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Creating the files for the semi-dynamic example"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Exporting the plot to vtk files"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "grid_mesh = mesh.grid\n",
+ "grid_mesh.save('mesh.vtk')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "grid_mesh_sco = mesh_sco.grid\n",
+ "grid_mesh_sco.save('mesh_sco.vtk')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "vtk_export = model.operator(\"vtk_export\")\n",
+ "vtk_export.inputs.connect(0)\n",
+ "vtk_export.inputs.connect(r'u_1.vtk')\n",
+ "vtk_export.inputs.connect(mesh)\n",
+ "vtk_export.inputs.connect(u)\n",
+ "vtk_export.eval()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "vtk_export =model.operator(\"vtk_export\")\n",
+ "vtk_export.inputs.connect(0)\n",
+ "vtk_export.inputs.connect(r's_VM_1.vtk')\n",
+ "vtk_export.inputs.connect(mesh)\n",
+ "vtk_export.inputs.connect(s_VM)\n",
+ "vtk_export.eval()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "vtk_export = model.operator(\"vtk_export\")\n",
+ "vtk_export.inputs.connect(r'u_stent_1.vtk')\n",
+ "vtk_export.inputs.connect(mesh_sco)\n",
+ "vtk_export.inputs.connect(u_stent)\n",
+ "vtk_export.eval()"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Correct the exported files"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "f = open(\"u_1.vtk\", \"r\")\n",
+ "l = len(f.readlines())\n",
+ "f.close() \n",
+ "f1 = open(\"u_1.vtk\", \"r\")\n",
+ "f2 = open(\"u.vtk\", \"w\")\n",
+ "b = 'nan nan nan\\n'\n",
+ "c = 'VECTORS'\n",
+ "for i in range(l): \n",
+ " a = f1.readline() \n",
+ " if a == b: # nan value not supported\n",
+ " a = '0 0 0\\n'\n",
+ " elif a[:len(c)] == c : # renamming the data\n",
+ " a = 'VECTORS U double\\n'\n",
+ " f2.write(a)\n",
+ "f1.close() \n",
+ "f2.close()\n",
+ "os.remove(\"u_1.vtk\")\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "f = open(\"s_VM_1.vtk\", \"r\")\n",
+ "l = len(f.readlines())\n",
+ "f.close() \n",
+ "f1 = open(\"s_VM_1.vtk\", \"r\")\n",
+ "f2 = open(\"s_VM.vtk\", \"w\")\n",
+ "b = 'nan nan nan\\n'\n",
+ "c = 'SCALARS 2_'\n",
+ "for i in range(l): \n",
+ " a = f1.readline() \n",
+ " if a == b: # nan value not supported\n",
+ " a = '0 0 0\\n'\n",
+ " elif a[:len(c)] == c : # renamming the data\n",
+ " a = 'SCALARS S_VM double 1\\n'\n",
+ " f2.write(a)\n",
+ "f1.close() \n",
+ "f2.close()\n",
+ "os.remove(\"s_VM_1.vtk\")\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "f = open(\"u_stent_1.vtk\", \"r\")\n",
+ "l = len(f.readlines())\n",
+ "f.close() \n",
+ "f1 = open(\"u_stent_1.vtk\", \"r\")\n",
+ "f2 = open(\"u_stent.vtk\", \"w\")\n",
+ "b = 'nan nan nan\\n'\n",
+ "c = 'VECTORS'\n",
+ "for i in range(l): \n",
+ " a = f1.readline() \n",
+ " if a == b: # nan value not supported\n",
+ " a = '0 0 0\\n'\n",
+ " elif a[:len(c)] == c : # renamming the data\n",
+ " a = 'VECTORS U_STENT double\\n'\n",
+ " f2.write(a)\n",
+ "f1.close() \n",
+ "f2.close()\n",
+ "os.remove(\"u_stent_1.vtk\")\n"
+ ]
+ },
+ {
+ "attachments": {},
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Plots using the VTK files"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pyvista\n",
+ "import panel\n",
+ "pyvista.set_jupyter_backend('panel')\n",
+ "pyvista.global_theme.window_size = [600, 400]\n",
+ "pyvista.global_theme.background = 'grey'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "file = \"mesh.vtk\"\n",
+ "mesh_file = pyvista.read(file)\n",
+ "\n",
+ "file = \"mesh_sco.vtk\"\n",
+ "mesh_sco_file = pyvista.read(file)\n",
+ "\n",
+ "pl = pyvista.Plotter(shape=(1, 2))\n",
+ "pl.subplot(0, 0)\n",
+ "pl.add_mesh(mesh_file, cmap=\"jet\", show_scalar_bar=False, show_edges=True)\n",
+ "pl.add_text(\"Mesh\", color='w')\n",
+ "pl.subplot(0, 1)\n",
+ "pl.add_mesh(mesh_sco_file, color=\"black\", show_scalar_bar=False, show_edges=True)\n",
+ "pl.add_text(\"Mesh of the stent\", color='w')\n",
+ "pl.link_views()\n",
+ "pl.camera_position = 'iso'\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\n",
+ "# results from add_mesh method\n",
+ "\n",
+ "file = \"u.vtk\"\n",
+ "u_file = pyvista.read(file)\n",
+ "u_file = u_file.warp_by_scalar('U')\n",
+ "pl = pyvista.Plotter(notebook=True)\n",
+ "pl.add_mesh(u_file, scalars = 'U', scalar_bar_args={'title':'Displacement'}, color='blue')\n",
+ "pl.add_text(\"Displacements of the model\", color='w')\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# results from add_mesh method\n",
+ "\n",
+ "file = \"s_VM.vtk\"\n",
+ "s_VM_file = pyvista.read(file)\n",
+ "s_VM_file = s_VM_file.warp_by_scalar('S_VM')\n",
+ "pl = pyvista.Plotter(notebook=True)\n",
+ "pl.add_mesh(s_VM_file, scalars = \"S_VM\", scalar_bar_args={'title':'Displacement'}, show_scalar_bar=True, color='blue')\n",
+ "pl.add_text(\"Von Mises Stress\", color='w')\n",
+ "pl.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# method using point_arrays because add_mesh method doesn't support point scalars\n",
+ "\n",
+ "file = \"u_stent.vtk\"\n",
+ "u_stent_file = pyvista.read(file)\n",
+ "u_stent_file.warp_by_scalar('U_STENT')\n",
+ "data = u_stent_file.get_array('U_STENT')\n",
+ "u_stent_mesh = mesh_sco_file\n",
+ "u_stent_mesh.point_data['U_STENT'] = data\n",
+ "u_stent_mesh = mesh_sco_file.point_data_to_cell_data()\n",
+ "u_stent_mesh.plot(scalars='U_STENT', show_scalar_bar=True, scalar_bar_args={'title':'Displacements'}, cmap='jet', text='Displacements of the stent', color='black')\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3.10.8 ('.venv': venv)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.8 (tags/v3.10.8:aaaf517, Oct 11 2022, 16:50:30) [MSC v.1933 64 bit (AMD64)]"
+ },
+ "vscode": {
+ "interpreter": {
+ "hash": "25ee88bf99fdb66867962637ab0ae1b8de27a896c2eb41e2fbf5e9143b58a926"
+ }
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.py b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.py
new file mode 100644
index 000000000..cb0cf3eb7
--- /dev/null
+++ b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.py
@@ -0,0 +1,307 @@
+#
+# # Cardiovascular Stent Simulation
+
+#
+# This example problem shows how to simulate stent-artery interaction during and after stent
+# placement in an occluded artery.
+# The analysis exposes advanced modeling techniques using PyMAPDL such as:
+# * Contact
+# * Element birth and death
+# * Mixed u-P formulation
+# * Nonlinear stabilization
+#
+# This example is inspired from the model and analysis defined in Chapter 25 of the Mechanical
+# APDL Technology Showcase Manual.
+
+
+# ## Starting MAPDL as a service
+
+# starting MAPDL as a service and importing an external model
+from ansys.mapdl.core import launch_mapdl
+
+# start MAPDL as a service
+mapdl = launch_mapdl()
+print(mapdl)
+
+# # Setting up the model
+
+# ### Defining material properties
+
+# define 316L Stainless steel
+mapdl.prep7()
+mapdl.mptemp()
+mapdl.mptemp(sloc="1", t1="0")
+mapdl.mpdata(lab="EX", mat="1", c1="200e3")
+mapdl.mpdata(lab="PRXY", mat="1", c1="0.3")
+mapdl.mptemp()
+mapdl.mptemp(sloc="1", t1="0")
+mapdl.mpdata(lab="DENS", mat="1", c1="8000e-9")
+
+# ### Defining element types
+
+# for straight line segments
+mapdl.et(itype="1", ename="beam189")
+mapdl.sectype(secid="1", type_="beam", subtype="csolid")
+mapdl.secdata(val1=0.05)
+
+# for arcs
+mapdl.et(itype="2", ename="beam189")
+mapdl.sectype(secid="2", type_="beam", subtype="csolid")
+mapdl.secdata(val1=0.05)
+
+# ### Defining 5-parameter Mooney-Rivlin hyperelastic artery material model
+
+c10 = 18.90e-3
+c01 = 2.75e-3
+c20 = 590.43e-3
+c11 = 857.2e-3
+nu1 = 0.49
+dd = 2 * (1 - 2 * nu1) / (c10 + c01)
+
+mapdl.tb(lab="hyper", mat="2", npts="5", tbopt="mooney")
+mapdl.tbdata(stloc="1", c1="c10", c2="c01", c3="c20", c4="c11", c6="dd")
+
+# ### Defining linear elastic material model for stiff calcified plaque
+
+mapdl.mp(lab="EX", mat="3", c0=".00219e3")
+mapdl.mp(lab="NUXY", mat="3", c0="0.49")
+
+# ### Define Solid185 element type to mesh both the artery and plaque
+
+# for artery
+mapdl.et(itype="9", ename="SOLID185")
+mapdl.keyopt(
+ itype="9", knum="6", value="1"
+) # Use mixed u-P formulation to avoid locking
+mapdl.keyopt(itype="9", knum="2", value="3") # Use Simplified Enhanced Strain method
+
+# for plaque
+mapdl.et(itype="16", ename="SOLID185")
+mapdl.keyopt(itype="16", knum="2", value="0") # Use B-bar
+
+# ### Defining settings to model the stent, the artery and the plaque
+#
+# Use force-distributed boundary constraints on 2 sides of artery wall to allow
+# for radial expansion of tissue without rigid body motion.
+
+# #### Settings for MPC Surface-based, force-distributed contact on proximal plane
+# parallel to x-y plane
+
+mapdl.mat("2")
+mapdl.r(nset="3")
+mapdl.real(nset="3")
+mapdl.et(itype="3", ename="170")
+mapdl.et(itype="4", ename="174")
+mapdl.keyopt(itype="4", knum="12", value="5")
+mapdl.keyopt(itype="4", knum="4", value="1")
+mapdl.keyopt(itype="4", knum="2", value="2")
+mapdl.keyopt(itype="3", knum="2", value="1")
+mapdl.keyopt(itype="3", knum="4", value="111111")
+mapdl.type(itype="3")
+
+mapdl.mat("2")
+mapdl.r(nset="4")
+mapdl.real(nset="4")
+mapdl.et(itype="5", ename="170")
+mapdl.et(itype="6", ename="174")
+mapdl.keyopt(itype="6", knum="12", value="5")
+mapdl.keyopt(itype="6", knum="4", value="1")
+mapdl.keyopt(itype="6", knum="2", value="2")
+mapdl.keyopt(itype="5", knum="2", value="1")
+mapdl.keyopt(itype="5", knum="4", value="111111")
+mapdl.type(itype="5")
+
+# #### Settings for standard contact between stent and inner plaque wall contact surface
+
+mapdl.mp(lab="MU", mat="1", c0="0")
+mapdl.mat("1")
+mapdl.mp(lab="EMIS", mat="1", c0="7.88860905221e-31")
+mapdl.r(nset="6")
+mapdl.real(nset="6")
+mapdl.et(itype="10", ename="170")
+mapdl.et(itype="11", ename="177")
+mapdl.r(nset="6", r3="1.0", r4="1.0", r5="0")
+mapdl.rmore(r9="1.0E20", r10="0.0", r11="1.0")
+mapdl.rmore(r7="0.0", r8="0", r9="1.0", r10="0.05", r11="1.0", r12="0.5")
+mapdl.rmore(r7="0", r8="1.0", r9="1.0", r10="0.0")
+mapdl.keyopt(itype="11", knum="5", value="0")
+mapdl.keyopt(itype="11", knum="7", value="1")
+mapdl.keyopt(itype="11", knum="8", value="0")
+mapdl.keyopt(itype="11", knum="9", value="0")
+mapdl.keyopt(itype="11", knum="10", value="2")
+mapdl.keyopt(itype="11", knum="11", value="0")
+mapdl.keyopt(itype="11", knum="12", value="0")
+mapdl.keyopt(itype="11", knum="2", value="3")
+mapdl.keyopt(itype="10", knum="5", value="0")
+
+# #### Settings for MPC based, force-distributed constraint on proximal stent nodes
+
+mapdl.mat("1")
+mapdl.r(nset="7")
+mapdl.real(nset="7")
+mapdl.et(itype="12", ename="170")
+mapdl.et(itype="13", ename="175")
+mapdl.keyopt(itype="13", knum="12", value="5")
+mapdl.keyopt(itype="13", knum="4", value="1")
+mapdl.keyopt(itype="13", knum="2", value="2")
+mapdl.keyopt(itype="12", knum="2", value="1")
+mapdl.keyopt(itype="12", knum="4", value="111111")
+mapdl.type(itype="12")
+
+# #### Settings for MPC based, force-distributed constraint on distal stent nodes
+
+mapdl.mat("1")
+mapdl.r(nset="8")
+mapdl.real(nset="8")
+mapdl.et(itype="14", ename="170")
+mapdl.et(itype="15", ename="175")
+mapdl.keyopt(itype="15", knum="12", value="5")
+mapdl.keyopt(itype="15", knum="4", value="1")
+mapdl.keyopt(itype="15", knum="2", value="2")
+mapdl.keyopt(itype="14", knum="2", value="1")
+mapdl.keyopt(itype="14", knum="4", value="111111")
+mapdl.type(itype="14")
+
+# ### Reading the geometry file
+
+mapdl.cdread(option="db", fname="stent", ext="cdb")
+mapdl.allsel(labt="all")
+mapdl.finish()
+
+# ## Static Analysis
+#
+# Run static analysis
+
+# enter solution processor and define analysis settings
+mapdl.run("/solu")
+mapdl.antype(antype="0")
+mapdl.nlgeom(key="on")
+
+# ### Apply Load Step 1: Balloon angioplasty of the artery to expand it past the
+# radius of the stent - IGNORE STENT
+
+mapdl.nsubst(nsbstp="20", nsbmx="20")
+mapdl.nropt(option1="full")
+mapdl.cncheck(option="auto")
+mapdl.esel(type_="s", item="type", vmin="11")
+mapdl.cm(cname="contact2", entity="elem")
+mapdl.ekill(elem="contact2") # Kill contact elements in stent-plaque contact
+# pair so that the stent is ignored in the first loadstep
+mapdl.nsel(type_="s", item="loc", comp="x", vmin="0", vmax="0.01e-3")
+mapdl.nsel(type_="r", item="loc", comp="y", vmin="0", vmax="0.01e-3")
+mapdl.d(node="all", lab="all")
+mapdl.allsel()
+
+mapdl.sf(
+ nlist="load", lab="pres", value="10e-2"
+) # Apply 0.1 Pa/mm^2 pressure to inner plaque wall
+mapdl.allsel()
+mapdl.nldiag(label="cont", key="iter")
+mapdl.solve()
+mapdl.save()
+
+# ### Apply Load Step 2: Reactivate contact between stent and plaque
+
+mapdl.ealive(elem="contact2")
+mapdl.allsel()
+
+mapdl.nsubst(nsbstp="2", nsbmx="2")
+mapdl.save()
+mapdl.solve()
+
+# ### Apply Load Step 3
+
+mapdl.nsubst(nsbstp="1", nsbmx="1", nsbmn="1")
+mapdl.solve()
+
+# ### Apply Load Step 4: Apply blood pressure (13.3 kPa) load to inner wall of plaque
+# and allow the stent to act as a scaffold
+
+mapdl.nsubst(nsbstp="300", nsbmx="3000", nsbmn="30")
+mapdl.sf(nlist="load", lab="pres", value="13.3e-3")
+mapdl.allsel()
+
+# ### Apply stabilization with energy option
+
+mapdl.stabilize(key="const", method="energy", value="0.1")
+
+# # Solve the model
+
+mapdl.solve()
+mapdl.save()
+mapdl.finish()
+
+# # Post-processing the results
+#
+# This section illustrates the use of PyDPF-Core to post-process the results.
+
+from ansys.dpf import core as dpf
+
+# ## Mesh of the model
+
+# Loading the result file
+model = dpf.Model(mapdl.result_file)
+ds = dpf.DataSources(mapdl.result_file)
+
+mesh = model.metadata.meshed_region
+mesh.plot(vtk_export=True)
+
+# ## Computed displacements of the model
+
+# Collecting the computed displacement
+u = model.results.displacement(time_scoping=[4]).eval()
+
+u[0].plot(deform_by=u[0])
+
+# ## Von Mises stress
+
+# Collecting the computed stress
+s_op = model.results.stress(time_scoping=[3])
+s_op.inputs.requested_location.connect(dpf.locations.nodal)
+s = s_op.eval()
+
+# Calculating Von Mises stress
+s_VM = dpf.operators.invariant.von_mises_eqv_fc(fields_container=s)
+s_VM_plot = s_VM.eval()
+
+s_VM_plot[0].plot(deform_by=u[0])
+
+# ## Computed displacements of the stent
+
+# Creating the mesh associated to the stent
+esco = mesh.named_selection("STENT")
+print(esco)
+
+# Transposing elemental location to nodal one
+op = dpf.operators.scoping.transpose()
+op.inputs.mesh_scoping.connect(esco)
+op.inputs.meshed_region.connect(mesh)
+op.inputs.inclusive.connect(1)
+nsco = op.eval()
+print(nsco)
+
+# Collecting the computed displacements of the stent
+u_stent = model.results.displacement(mesh_scoping=nsco, time_scoping=[4])
+u_stent = u_stent.outputs.fields_container()
+
+# Linking the stent mesh to the global one
+op = dpf.operators.mesh.from_scoping() # operator instantiation
+op.inputs.scoping.connect(nsco)
+op.inputs.inclusive.connect(1)
+op.inputs.mesh.connect(mesh)
+mesh_sco = op.eval()
+mesh_sco.plot(vtk_export=True)
+
+u_stent[0].meshed_region = mesh_sco
+u_stent[0].plot(deformed_by=u_stent[0])
+
+mesh.plot(
+ color="w",
+ show_edges=True,
+ text="Mesh of the model",
+)
+mesh_sco.plot(color="black", show_edges=True, text="Mesh of the stent")
+
+# ## Exit MAPDL
+
+mapdl.exit()
diff --git a/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.rst b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.rst
new file mode 100644
index 000000000..4025e0c06
--- /dev/null
+++ b/doc/source/technology_showcase_examples/techdemo-25/ex_25-tecstent.rst
@@ -0,0 +1,525 @@
+.. _sphx_glr_ex_25-tecstent.rst:
+
+Cardiovascular Stent Simulation
+===============================
+
+This example problem shows how to simulate stent-artery interaction during and after stent
+placement in an occluded artery.
+The analysis exposes advanced modeling techniques using PyMAPDL such as:
+* Contact
+* Element birth and death
+* Mixed u-P formulation
+* Nonlinear stabilization
+
+This example is inspired from the model and analysis defined in Chapter 25 of the `Mechanical
+APDL Technology Showcase Manual `_.
+
+25.1. Introduction
+------------------
+
+
+25.1.1. Problem Description
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+A bare metal stent is an effective device for opening atherosclerotic arteries and
+other blockages:
+
+.. figure:: images/gtecstent1.png
+ :align: center
+ :alt: Effect of Stent Placement in Increasing Blood FlowCourtesy of Lakeview Center
+ :figclass: align-center
+
+ **Figure 25.1: Effect of Stent Placement in Increasing Blood Flow**
+ Courtesy of `LakeviewCenter `
+
+The success of stenting depends largely on how the stent and the artery interact
+mechanically. In both the stent-design process and in pre-clinical patient-specific
+evaluations, computer simulation using finite element analysis (FEA) has become an
+accepted tool for studying stent-artery interaction.
+
+A viable stent-artery finite element model must properly reflect the nonlinear nature
+of the phenomenon, such as the biological tissue properties, large arterial wall
+deformation, and the sliding contact between the stent and the artery wall.
+
+
+25.1.2. Starting MAPDL as a service
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code:: ipython3
+
+ # starting MAPDL as a service and importing an external model
+ from ansys.mapdl.core import launch_mapdl
+
+ # start MAPDL as a service
+ mapdl = launch_mapdl()
+ print(mapdl)
+
+
+25.2. Modeling
+--------------
+
+25.2.1. Setting up the model
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+First, we define the material properties.
+
+.. code:: ipython3
+
+ # define 316L Stainless steel
+ mapdl.prep7()
+ mapdl.mptemp()
+ mapdl.mptemp(sloc="1", t1="0")
+ mapdl.mpdata(lab="EX", mat="1", c1="200e3")
+ mapdl.mpdata(lab="PRXY", mat="1", c1="0.3")
+ mapdl.mptemp()
+ mapdl.mptemp(sloc="1", t1="0")
+ mapdl.mpdata(lab="DENS", mat="1", c1="8000e-9")
+
+
+Then, we can define the element technology_showcase_examples.
+
+.. code:: ipython3
+
+ # for straight line segments
+ mapdl.et(itype="1", ename="beam189")
+ mapdl.sectype(secid="1", type_="beam", subtype="csolid")
+ mapdl.secdata(val1=0.05)
+
+ # for arcs
+ mapdl.et(itype="2", ename="beam189")
+ mapdl.sectype(secid="2", type_="beam", subtype="csolid")
+ mapdl.secdata(val1=0.05)
+
+
+We define the 5-parameter Mooney-Rivlin hyperelastic artery material
+model.
+
+.. code:: ipython3
+
+ c10 = 18.90e-3
+ c01 = 2.75e-3
+ c20 = 590.43e-3
+ c11 = 857.2e-3
+ nu1 = 0.49
+ dd = 2 * (1 - 2 * nu1) / (c10 + c01)
+
+ mapdl.tb(lab="hyper", mat="2", npts="5", tbopt="mooney")
+ mapdl.tbdata(stloc="1", c1="c10", c2="c01", c3="c20", c4="c11", c6="dd")
+
+
+We define the linear elastic material model for stiff calcified plaque.
+
+.. code:: ipython3
+
+ mapdl.mp(lab="EX", mat="3", c0=".00219e3")
+ mapdl.mp(lab="NUXY", mat="3", c0="0.49")
+
+
+We define the Solid185 element type to mesh both the artery and plaque.
+
+.. code:: ipython3
+
+ # for artery
+ mapdl.et(itype="9", ename="SOLID185")
+ mapdl.keyopt(
+ itype="9", knum="6", value="1") # Use mixed u-P formulation to avoid locking
+ mapdl.keyopt(itype="9", knum="2", value="3") # Use Simplified Enhanced Strain method
+
+ # for plaque
+ mapdl.et(itype="16", ename="SOLID185")
+ mapdl.keyopt(itype="16", knum="2", value="0") # Use B-bar
+
+
+We define the settings to model the stent, the artery and the plaque.
+
+We use force-distributed boundary constraints on 2 sides of artery wall to allow
+for radial expansion of tissue without rigid body motion.
+
+Settings for MPC Surface-based, force-distributed contact on proximal plane
+parallel to x-y plane
+
+.. code:: ipython3
+
+ mapdl.mat("2")
+ mapdl.r(nset="3")
+ mapdl.real(nset="3")
+ mapdl.et(itype="3", ename="170")
+ mapdl.et(itype="4", ename="174")
+ mapdl.keyopt(itype="4", knum="12", value="5")
+ mapdl.keyopt(itype="4", knum="4", value="1")
+ mapdl.keyopt(itype="4", knum="2", value="2")
+ mapdl.keyopt(itype="3", knum="2", value="1")
+ mapdl.keyopt(itype="3", knum="4", value="111111")
+ mapdl.type(itype="3")
+
+ mapdl.mat("2")
+ mapdl.r(nset="4")
+ mapdl.real(nset="4")
+ mapdl.et(itype="5", ename="170")
+ mapdl.et(itype="6", ename="174")
+ mapdl.keyopt(itype="6", knum="12", value="5")
+ mapdl.keyopt(itype="6", knum="4", value="1")
+ mapdl.keyopt(itype="6", knum="2", value="2")
+ mapdl.keyopt(itype="5", knum="2", value="1")
+ mapdl.keyopt(itype="5", knum="4", value="111111")
+ mapdl.type(itype="5")
+
+
+Settings for standard contact between stent and inner plaque wall contact
+surface
+
+.. code:: ipython3
+
+ mapdl.mp(lab="MU", mat="1", c0="0")
+ mapdl.mat("1")
+ mapdl.mp(lab="EMIS", mat="1", c0="7.88860905221e-31")
+ mapdl.r(nset="6")
+ mapdl.real(nset="6")
+ mapdl.et(itype="10", ename="170")
+ mapdl.et(itype="11", ename="177")
+ mapdl.r(nset="6", r3="1.0", r4="1.0", r5="0")
+ mapdl.rmore(r9="1.0E20", r10="0.0", r11="1.0")
+ mapdl.rmore(r7="0.0", r8="0", r9="1.0", r10="0.05", r11="1.0", r12="0.5")
+ mapdl.rmore(r7="0", r8="1.0", r9="1.0", r10="0.0")
+ mapdl.keyopt(itype="11", knum="5", value="0")
+ mapdl.keyopt(itype="11", knum="7", value="1")
+ mapdl.keyopt(itype="11", knum="8", value="0")
+ mapdl.keyopt(itype="11", knum="9", value="0")
+ mapdl.keyopt(itype="11", knum="10", value="2")
+ mapdl.keyopt(itype="11", knum="11", value="0")
+ mapdl.keyopt(itype="11", knum="12", value="0")
+ mapdl.keyopt(itype="11", knum="2", value="3")
+ mapdl.keyopt(itype="10", knum="5", value="0")
+
+
+Settings for MPC based, force-distributed constraint on proximal stent nodes
+
+.. code:: ipython3
+
+ mapdl.mat("1")
+ mapdl.r(nset="7")
+ mapdl.real(nset="7")
+ mapdl.et(itype="12", ename="170")
+ mapdl.et(itype="13", ename="175")
+ mapdl.keyopt(itype="13", knum="12", value="5")
+ mapdl.keyopt(itype="13", knum="4", value="1")
+ mapdl.keyopt(itype="13", knum="2", value="2")
+ mapdl.keyopt(itype="12", knum="2", value="1")
+ mapdl.keyopt(itype="12", knum="4", value="111111")
+ mapdl.type(itype="12")
+
+
+
+Settings for MPC based, force-distributed constraint on distal stent
+nodes.
+
+.. code:: ipython3
+
+ mapdl.mat("1")
+ mapdl.r(nset="8")
+ mapdl.real(nset="8")
+ mapdl.et(itype="14", ename="170")
+ mapdl.et(itype="15", ename="175")
+ mapdl.keyopt(itype="15", knum="12", value="5")
+ mapdl.keyopt(itype="15", knum="4", value="1")
+ mapdl.keyopt(itype="15", knum="2", value="2")
+ mapdl.keyopt(itype="14", knum="2", value="1")
+ mapdl.keyopt(itype="14", knum="4", value="111111")
+ mapdl.type(itype="14")
+
+Once all the setups are ready, we read the geometry file.
+
+.. code:: ipython3
+
+ mapdl.cdread(option="db", fname="stent", ext="cdb")
+ mapdl.allsel(labt="all")
+ mapdl.finish()
+
+
+
+25.3. Analysis
+--------------
+
+25.3.1. Static Analysis
+^^^^^^^^^^^^^^^^^^^^^^^
+
+We, then, apply the static analysis.
+
+.. code:: ipython3
+
+ # enter solution processor and define analysis settings
+ mapdl.run("/solu")
+ mapdl.antype(antype="0")
+ mapdl.nlgeom(key="on")
+
+
+25.3.2. Loads
+^^^^^^^^^^^^^
+
+We apply the Load Step 1:
+Balloon angioplasty of the artery to expand it past the
+radius of the stent - IGNORE STENT
+
+.. code:: ipython3
+
+ mapdl.nsubst(nsbstp="20", nsbmx="20")
+ mapdl.nropt(option1="full")
+ mapdl.cncheck(option="auto")
+ mapdl.esel(type_="s", item="type", vmin="11")
+ mapdl.cm(cname="contact2", entity="elem")
+ mapdl.ekill(elem="contact2") # Kill contact elements in stent-plaque contact
+ #pair so that the stent is ignored in the first loadstep
+ mapdl.nsel(type_="s", item="loc", comp="x", vmin="0", vmax="0.01e-3")
+ mapdl.nsel(type_="r", item="loc", comp="y", vmin="0", vmax="0.01e-3")
+ mapdl.d(node="all", lab="all")
+ mapdl.allsel()
+
+ mapdl.sf(nlist="load", lab="pres", value="10e-2") # Apply 0.1 Pa/mm^2 pressure to inner plaque wall
+ mapdl.allsel()
+ mapdl.nldiag(label="cont", key="iter")
+ mapdl.solve()
+ mapdl.save()
+
+
+We then apply the Load Step 2: Reactivate contact between stent and plaque.
+
+.. code:: ipython3
+
+ mapdl.ealive(elem="contact2")
+ mapdl.allsel()
+
+ mapdl.nsubst(nsbstp="2", nsbmx="2")
+ mapdl.save()
+ mapdl.solve()
+
+
+We apply the Load Step 3.
+
+.. code:: ipython3
+
+ mapdl.nsubst(nsbstp="1", nsbmx="1", nsbmn="1")
+ mapdl.solve()
+
+
+We apply the Load Step 4: Apply blood pressure (13.3 kPa) load to
+inner wall of plaque and allow the stent to act as a scaffold.
+
+.. code:: ipython3
+
+ mapdl.nsubst(nsbstp="300", nsbmx="3000", nsbmn="30")
+ mapdl.sf(nlist="load", lab="pres", value="13.3e-3")
+ mapdl.allsel()
+
+
+Finally, we apply stabilization with energy option.
+
+.. code:: ipython3
+
+ mapdl.stabilize(key="const", method="energy", value="0.1")
+
+
+
+25.3. Solution of the model
+---------------------------
+
+.. code:: ipython3
+
+ mapdl.solve()
+ mapdl.save()
+ mapdl.finish()
+
+
+
+25.4. Results
+-------------
+
+This section illustrates the use of PyDPF-Core to post-process the results.
+
+.. code:: ipython3
+
+ from ansys.dpf import core as dpf
+ from ansys.dpf.core import operators as ops
+ import pyvista
+
+
+25.4.1. Mesh of the model
+^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code:: ipython3
+
+ # Loading the result file
+ model = dpf.Model(mapdl.result_file)
+ ds = dpf.DataSources(mapdl.result_file)
+
+ mesh = model.metadata.meshed_region
+ mesh.plot()
+
+.. jupyter-execute::
+ :hide-code:
+
+ import pyvista
+ import panel
+ pyvista.set_jupyter_backend('panel')
+ pyvista.global_theme.window_size = [1000, 800]
+ pyvista.global_theme.background = 'grey'
+
+ import warnings
+ warnings.filterwarnings('ignore')
+
+ file = "./source/technology_showcase_examples/techdemo-25/mesh.vtk"
+ mesh_file = pyvista.read(file)
+ pl = pyvista.Plotter()
+ pl.add_mesh(mesh_file, cmap='jet', show_scalar_bar=False, show_edges=True)
+ pl.add_text("Mesh of the model", color='w')
+ pl.show()
+
+
+25.4.2. Computed displacements of the model
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code:: ipython3
+
+ # Collecting the computed displacement
+ u = model.results.displacement(time_scoping=[4]).eval()
+
+ u[0].plot(deform_by = u[0])
+
+.. jupyter-execute::
+ :hide-code:
+
+ file = "./source/technology_showcase_examples/techdemo-25/u.vtk"
+ u_file = pyvista.read(file)
+ u_file = u_file.warp_by_scalar('U')
+ pl = pyvista.Plotter(notebook=True)
+ pl.add_mesh(u_file, scalars = 'U', show_scalar_bar=True, scalar_bar_args={'title':'Displacements'}, cmap='jet')
+ pl.add_text("Displacements of the model", color='w')
+ pl.show()
+
+
+25.4.3. Von Mises stress
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. code:: ipython3
+
+ # Collecting the computed stress
+ s_op = model.results.stress(time_scoping=[3])
+ s_op.inputs.requested_location.connect(dpf.locations.nodal)
+ s = s_op.eval()
+
+ # Calculating Von Mises stress
+ s_VM = dpf.operators.invariant.von_mises_eqv_fc(fields_container=s)
+ s_VM_plot = s_VM.eval()
+
+ s_VM_plot[0].plot(deform_by = u[0])
+
+.. jupyter-execute::
+ :hide-code:
+
+ file = "./source/technology_showcase_examples/techdemo-25/s_VM.vtk"
+ s_VM_file = pyvista.read(file)
+ s_VM_file = s_VM_file.warp_by_scalar('S_VM')
+ pl = pyvista.Plotter(notebook=True)
+ pl.add_mesh(s_VM_file, scalars = "S_VM", show_scalar_bar=True, scalar_bar_args={'title':'Von Mises Stress'}, cmap='jet')
+ pl.add_text("Von Mises Stress", color='w')
+ pl.show()
+
+
+25.4.4. Computed displacements of the stent
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+
+.. code:: ipython3
+
+ # Creating the mesh associated to the stent
+ esco = mesh.named_selection("STENT")
+ print(esco)
+
+ # Transposing elemental location to nodal one
+ op = dpf.operators.scoping.transpose()
+ op.inputs.mesh_scoping.connect(esco)
+ op.inputs.meshed_region.connect(mesh)
+ op.inputs.inclusive.connect(1)
+ nsco = op.eval()
+ print(nsco)
+
+
+.. code:: ipython3
+
+ # Collecting the computed displacements of the stent
+ u_stent = model.results.displacement(mesh_scoping=nsco, time_scoping=[4])
+ u_stent = u_stent.outputs.fields_container()
+
+ # Linking the stent mesh to the global one
+ op = dpf.operators.mesh.from_scoping() # operator instantiation
+ op.inputs.scoping.connect(nsco)
+ op.inputs.inclusive.connect(1)
+ op.inputs.mesh.connect(mesh)
+ mesh_sco = op.eval()
+ u_stent[0].meshed_region = mesh_sco
+
+ # Plotting the meshes
+ mesh.plot(color="w", show_edges=True, text='Mesh of the model', )
+ mesh_sco.plot(color="black", show_edges=True, text='Mesh of the stent')
+
+.. jupyter-execute::
+ :hide-code:
+
+ file = "./source/technology_showcase_examples/techdemo-25/mesh.vtk"
+ mesh_file = pyvista.read(file)
+
+ file = "./source/technology_showcase_examples/techdemo-25/mesh_sco.vtk"
+ mesh_sco_file = pyvista.read(file)
+
+ pl = pyvista.Plotter(shape=(1, 2))
+ pl.subplot(0, 0)
+ pl.add_mesh(mesh_file, cmap="jet", show_scalar_bar=False, show_edges=True)
+ pl.add_text("Mesh of the model", color='w')
+ pl.subplot(0, 1)
+ pl.add_mesh(mesh_sco_file, color="black", show_scalar_bar=False, show_edges=True)
+ pl.add_text("Mesh of the stent", color='w')
+ pl.link_views()
+ pl.camera_position = 'iso'
+ pl.show()
+
+
+.. code:: ipython3
+
+ u_stent[0].plot(deformed_by=u_stent[0])
+
+.. jupyter-execute::
+ :hide-code:
+
+ file = "./source/technology_showcase_examples/techdemo-25/u_stent.vtk"
+ u_stent_file = pyvista.read(file)
+ u_stent_file.warp_by_scalar('U_STENT')
+ data = u_stent_file.get_array('U_STENT')
+ u_stent_mesh = mesh_sco_file
+ u_stent_mesh.point_data['U_STENT'] = data
+ u_stent_mesh = mesh_sco_file.point_data_to_cell_data()
+ u_stent_mesh.title = 'Displacements of the stent'
+ u_stent_mesh.plot(scalars='U_STENT', show_scalar_bar=True, scalar_bar_args={'title':'Displacements'}, cmap='jet', text='Displacements of the stent')
+
+
+25.5. Exit MAPDL
+----------------
+
+.. code:: ipython3
+
+ mapdl.exit()
+
+
+25.6. Input Files
+-----------------
+
+The following files were used in this problem:
+
+* **stent.dat** -- Input file for the cardiovascular stent
+ problem.
+* **stent.cdb** -- The common database file containing the model
+ information for this problem (called by **stent.dat**).
+
++-----------------------------------------------------------------------------------------------------------------------------------+
+| `Download the zipped **td-25** file set for this problem