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Robust domain decomposition methods for high-contrast multiscale problems on irregular domains with virtual element discretizations

Numerical Analysis 2023-06-28 v1 Numerical Analysis

Abstract

Our research focuses on the development of domain decomposition preconditioners tailored for second-order elliptic partial differential equations. Our approach addresses two major challenges simultaneously: i) effectively handling coefficients with high-contrast and multiscale properties, and ii) accommodating irregular domains in the original problem, the coarse mesh, and the subdomain partition. The robustness of our preconditioners is crucial for real-world applications, such as the efficient and accurate modeling of subsurface flow in porous media and other important domains. The core of our method lies in the construction of a suitable partition of unity functions and coarse spaces utilizing local spectral information. Leveraging these components, we implement a two-level additive Schwarz preconditioner. We demonstrate that the condition number of the preconditioned systems is bounded with a bound that is independent of the contrast. Our claims are further substantiated through selected numerical experiments, which confirm the robustness of our preconditioners.

Keywords

Cite

@article{arxiv.2306.15424,
  title  = {Robust domain decomposition methods for high-contrast multiscale problems on irregular domains with virtual element discretizations},
  author = {Juan G. Calvo and Juan Galvis},
  journal= {arXiv preprint arXiv:2306.15424},
  year   = {2023}
}
R2 v1 2026-06-28T11:15:37.981Z