Adaptive Finite Element Methods

Fuente: arXiv
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Autores principales: Bonito, Andrea, Canuto, Claudio, Nochetto, Ricardo H., Veeser, Andreas
Formato: Preprint
Publicado: 2024
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author Bonito, Andrea
Canuto, Claudio
Nochetto, Ricardo H.
Veeser, Andreas
author_facet Bonito, Andrea
Canuto, Claudio
Nochetto, Ricardo H.
Veeser, Andreas
contents This is a survey on the theory of adaptive finite element methods (AFEMs), which are fundamental in modern computational science and engineering but whose mathematical assessment is a formidable challenge. We present a self-contained and up-to-date discussion of AFEMs for linear second order elliptic PDEs and dimension d>1, with emphasis on foundational issues. After a brief review of functional analysis and basic finite element theory, including piecewise polynomial approximation in graded meshes, we present the core material for coercive problems. We start with a novel a posteriori error analysis applicable to rough data, which delivers estimators fully equivalent to the solution error. They are used in the design and study of three AFEMs depending on the structure of data. We prove linear convergence of these algorithms and rate-optimality provided the solution and data belong to suitable approximation classes. We also address the relation between approximation and regularity classes. We finally extend this theory to discontinuous Galerkin methods as prototypes of non-conforming AFEMs and beyond coercive problems to inf-sup stable AFEMs.
format Preprint
id arxiv_https___arxiv_org_abs_2402_07273
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Adaptive Finite Element Methods
Bonito, Andrea
Canuto, Claudio
Nochetto, Ricardo H.
Veeser, Andreas
Numerical Analysis
This is a survey on the theory of adaptive finite element methods (AFEMs), which are fundamental in modern computational science and engineering but whose mathematical assessment is a formidable challenge. We present a self-contained and up-to-date discussion of AFEMs for linear second order elliptic PDEs and dimension d>1, with emphasis on foundational issues. After a brief review of functional analysis and basic finite element theory, including piecewise polynomial approximation in graded meshes, we present the core material for coercive problems. We start with a novel a posteriori error analysis applicable to rough data, which delivers estimators fully equivalent to the solution error. They are used in the design and study of three AFEMs depending on the structure of data. We prove linear convergence of these algorithms and rate-optimality provided the solution and data belong to suitable approximation classes. We also address the relation between approximation and regularity classes. We finally extend this theory to discontinuous Galerkin methods as prototypes of non-conforming AFEMs and beyond coercive problems to inf-sup stable AFEMs.
title Adaptive Finite Element Methods
topic Numerical Analysis
url https://arxiv.org/abs/2402.07273