Active Manifold and Model Order Reduction to Accelerate Multidisciplinary Analysis and Optimization - presented by Prof. Charbel Farhat

Active Manifold and Model Order Reduction to Accelerate Multidisciplinary Analysis and Optimization

Prof. Charbel Farhat

Prof. Charbel Farhat
Slide at 31:12
Charbel Energy-Conserving Sampling and Weighting (ECSW) for Hyperreduction Gauss quadrature in a hyperspace - e.g. in the finite element (FE) context eEECE where Ne(=I) << Ne(=|8|) and ge > 0 to preserve the strain energy for CSD (also beneficial in general to the solution of the associated optimization problem The reduced mesh ECE and the corresponding set of weights are determined by training the hyperreduction approximation on force functions/source terms (or tangent stiffness matrices/Jacobians) evaluated at the pre-computed solution snapshots Hyperreduction transforms a PROM into a hyperreduced PROM (HPROM)
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Summary (AI generated)

I am only showing the elements that are on the surface. In general, we go from 11,454,702 cells to 5,000 cells, which is less than 0.01% of the total elements, but still provides the necessary accuracy. This process is part of Structural Dynamics. The image on the left shows the full mesh, while the image on the right displays only a few elements in blue that were used for computation. The size of the finite element mesh decreased from 275,685 to 859 in order to accurately compute these projections.