Robust Methods for Multiscale Coarse Approximations of Diffusion Models in Perforated Domains

Fuente: arXiv
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Autores principales: Boutilier, Miranda, Brenner, Konstantin, Dolean, Victorita
Formato: Preprint
Publicado: 2023
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author Boutilier, Miranda
Brenner, Konstantin
Dolean, Victorita
author_facet Boutilier, Miranda
Brenner, Konstantin
Dolean, Victorita
contents For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical methods, this coarse space is spanned by locally discrete harmonic basis functions. Along the subdomain boundaries, the basis functions are piecewise polynomial. The main contribution of this article is an error estimate regarding the H1-projection over the coarse space which depends only on the regularity of the solution over the edges of the coarse partitioning. For a specific edge refinement procedure, the error analysis establishes superconvergence of the method even if the true solution has a low general regularity. Combined with domain decomposition (DD) methods, the coarse space leads to an efficient two-level iterative linear solver which reaches the fine-scale finite element error in few iterations. It also bodes well as a preconditioner for Krylov methods and provides scalability with respect to the number of subdomains. Numerical experiments showcase the increased precision of the coarse approximation as well as the efficiency and scalability of the coarse space as a component of a DD algorithm.
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id arxiv_https___arxiv_org_abs_2310_15669
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Robust Methods for Multiscale Coarse Approximations of Diffusion Models in Perforated Domains
Boutilier, Miranda
Brenner, Konstantin
Dolean, Victorita
Numerical Analysis
For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical methods, this coarse space is spanned by locally discrete harmonic basis functions. Along the subdomain boundaries, the basis functions are piecewise polynomial. The main contribution of this article is an error estimate regarding the H1-projection over the coarse space which depends only on the regularity of the solution over the edges of the coarse partitioning. For a specific edge refinement procedure, the error analysis establishes superconvergence of the method even if the true solution has a low general regularity. Combined with domain decomposition (DD) methods, the coarse space leads to an efficient two-level iterative linear solver which reaches the fine-scale finite element error in few iterations. It also bodes well as a preconditioner for Krylov methods and provides scalability with respect to the number of subdomains. Numerical experiments showcase the increased precision of the coarse approximation as well as the efficiency and scalability of the coarse space as a component of a DD algorithm.
title Robust Methods for Multiscale Coarse Approximations of Diffusion Models in Perforated Domains
topic Numerical Analysis
url https://arxiv.org/abs/2310.15669