This was part of Reduced-Order Modeling for Complex Engineering Problems

Adaptive LOD-BDDC for elliptic problems with rough coefficients

Marcus Sarkis, Worcester Polytechnic Institute

Thursday, February 6, 2025



Slides
Abstract: We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with very rough coefficients. The methods are of Galerkin type and follow the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into multiscale and fine subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based on corners used on primal iterative substructuring methods, to functions of global minimal energy. This approach delivers quasi-optimal a priori error energy approximation with respect to the mesh size, but it is not robust with respect to high-contrast coefficients. In a second method, edge modes based on local generalized eigenvalue problems are added to the corner modes. As a result, optimal a priori error energy estimate is achieved which is mesh and contrast independent. The methods converge at optimal rate even if the solution is only in H1. Numerical experiments will be provided.