<i>A priori</i> error estimates for finite element discretization of semilinear elliptic equations with non-Lipschitz nonlinearities

In this paper we develop numerical analysis for finite element discretization of semilinear elliptic equations with potentially non-Lipschitz nonlinearites. The nonlinearity is essecially assumed to be continuous and monotonically non-decreasing including the case of non-Lipschitz or even non-Hölder continuous nonlinearities. For a direct discretization (without any regularization) with linear finite elements we derive error estimates with respect to various norms and illustrate these results with a numerical example.

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Publication Details

Journal
ESAIM. Mathematical modelling and numerical analysis
Published
2025-03-01
DOI
https://doi.org/10.1051/m2an/2025019
Citations
1
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
1.33
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article

A priori error estimates for finite element discretization of semilinear elliptic equations with non-Lipschitz nonlinearities

Boris Vexler
1 citations
ESAIM. Mathematical modelling and numerical analysis
Advanced Numerical Methods in Computational Mathematics
1.33
article

A priori error estimates for finite element discretization of semilinear elliptic equations with non-Lipschitz nonlinearities

Boris Vexler
article en
1 citations

Abstract

In this paper we develop numerical analysis for finite element discretization of semilinear elliptic equations with potentially non-Lipschitz nonlinearites. The nonlinearity is essecially assumed to be continuous and monotonically non-decreasing including the case of non-Lipschitz or even non-Hölder continuous nonlinearities. For a direct discretization (without any regularization) with linear finite elements we derive error estimates with respect to various norms and illustrate these results with a numerical example.

ESAIM. Mathematical modelling and numerical analysisVol. 59(2)
Technical University of Munich (DE)
Openalex Percentile: Top 25%
Advanced Numerical Methods in Computational Mathematics
1.33
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