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examples/ansys/forum.md

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# Grid fin optimization with ANSYS SpaceClaim and PyANSYS
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We want to perform a parameter optimization on a SpaceX-style grid fin geometry to maximize stiffness while maintaining a strict mass limit. This ensures the fin remains rigid during re-entry Max-Q (maximum dynamic pressure) for robust aerodynamic control. To demonstrate a realistic engineering workflow, we demonstrate a gradient based end to optimization that plugs into ANSYS Spaceclaim as a design software and uses PyANSYS to setup a differentiable finite element simulation. The workflow involves three Tesseracts:
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We want to perform a parameter optimization on a SpaceX-style grid fin geometry to maximize stiffness while maintaining a strict mass limit. This ensures the fin remains rigid during re-entry Max-Q (maximum dynamic pressure) for robust aerodynamic control. The 3D mesh looks as follows:
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![Workflow](imgs/grid_mesh.png)
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![Workflow](imgs/boundary_conditions.png)
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To demonstrate a realistic engineering workflow, we demonstrate a gradient based end to optimization that plugs into ANSYS Spaceclaim as a design software and uses PyANSYS to setup a differentiable finite element simulation. The workflow involves three Tesseracts:
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- **Ansys SpaceClaim Tesseract** takes a set of differentiable and non differentiable parameters and injects them into a SpaceClaim script that generates the grid fin geometry. It then returns returns the resulting triangular surface mesh as a list of points and faces. More about this here: ...
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The Tesseracts are then composed into a fully differentiable workflow using Tesseract-JAX.
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![Workflow](workflow_1.png)
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![Workflow](imgs/workflow_1.png)
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In order to der
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examples/ansys/imgs/grid_mesh.png

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examples/ansys/spaceclaim_pymapdl.ipynb

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