pytacsadapt #14
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pytacsadapt #14
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- added pyTACSAdapt class - added pyApproximationSpace class - added plate example that demonstrates pyTACSAdapt usage - updated TMR_AdjointErrorEst() error localization (quad only) - minor updates and added documentation to TMR.pyx
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You could compare the unit_tests.yml for tmr to that of funtofem since it has a similar conda build. It looks like you conda install mpi4py whereas ours is pip installed automatically with TACS (so doesn't appear directly in the yml file). That's the only difference I see. |
Merged
- updated error localization, dependent nodes no longer double counted - added return vector of nodal errors, for visualizing error field
- added functionality to sew IGES/STEP model - added functionality to apply shape fixing to a loaded compound
- EGADS IO updated to allow for setting units
- add sewModel() functionality - updated loadModel() to allow units to be specified - updated adjointError() for quads, returns node-wise errors - necessary changes made in .pxd file
- added writeField() to pyApproximationSpace - updated adaptation parameter specification in pyTACSAdapt - added evaluateResidual() to pyTACSAdapt - added collectErrors() to pyTACSAdapt - added refineModel() to pyTACSAdapt, simplifies mesh refinement - added adaptModelFixedGrowth() to pyTACSAdapt - added writeModelHistory() to pyTACSAdapt - added h5py as a dependency for writeModelHistory()
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I've put together a high-level interface for doing output-based mesh adaptation on static problems using TACS and TMR.
The
pyTACSAdaptclass contains the "coarse" and "fine" models consisting of their TACS/TMR finite-element and geometry information. This class also provides a higher-level interface for conducting the primal analysis and doing adjoint-based error estimation and mesh adaptation via routines implemented in TMR.The adjoint-based error estimation in TMR for Quads is currently in working order, I have not yet updated the Oct implementation. One significant change made to the code was the method used for error localization from mesh nodes to the elements. Previously, a partition-of-unity basis was used to localize the error to the elements, which was implemented at the element level within TACS. I moved the adjoint-weighted residual computation to occur solely within TMR to avoid a lot of repeated code in the TACS elements. I removed the partition of unity basis, and now the error localization is simply a weighted sum of the nodal errors contained within each element, though there may be an issue with how dependent nodes are currently being accounted for which I'd like some feedback on.
Included here is a simple example that demonstrates
pyTACSAdaptusage. Essentially, the user must provide a geometry input file, a callback function for loading the geometry and initializing the coarse model, a callback function for creating elements for the TACS assembler, and a callback function for setting up the static TACS problem. The example should walk through the steps of the adaptive analysis in a straightforward manner.Please let me know if you have any comments, questions, or suggestions on ways to improve this.