Modified Neumann–Neumann methods for semi- and quasilinear elliptic equations

The Neumann–Neumann method is a commonly employed domain decomposition method for linear elliptic equations. However, the method exhibits slow convergence when applied to semilinear equations and does not seem to converge at all for certain quasilinear equations. We therefore propose two modified Neumann–Neumann methods that have better convergence properties and require fewer computations. We provide numerical results that show the advantages of these methods when applied to both semilinear and quasilinear equations. We also prove linear convergence with mesh-independent error reduction under certain assumptions on the equation. The analysis is carried out on general Lipschitz domains and relies on the theory of nonlinear Steklov–Poincaré operators.

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Publication Details

Journal
Applied Numerical Mathematics
Published
2024-08-22
DOI
https://doi.org/10.1016/j.apnum.2024.08.011
Citations
1
Primary Topic
Advanced Numerical Methods in Computational Mathematics
Type
article
Field-Weighted Citation Impact
0.37

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article

Modified Neumann–Neumann methods for semi- and quasilinear elliptic equations

Emil Engström, Eskil Hansen
1 citations
Applied Numerical Mathematics
Advanced Numerical Methods in Computational Mathematics
0.37
article

Modified Neumann–Neumann methods for semi- and quasilinear elliptic equations

Emil Engström, Eskil Hansen
article en
1 citations

Abstract

The Neumann–Neumann method is a commonly employed domain decomposition method for linear elliptic equations. However, the method exhibits slow convergence when applied to semilinear equations and does not seem to converge at all for certain quasilinear equations. We therefore propose two modified Neumann–Neumann methods that have better convergence properties and require fewer computations. We provide numerical results that show the advantages of these methods when applied to both semilinear and quasilinear equations. We also prove linear convergence with mesh-independent error reduction under certain assumptions on the equation. The analysis is carried out on general Lipschitz domains and relies on the theory of nonlinear Steklov–Poincaré operators.

Applied Numerical MathematicsVol. 206
Vetenskapsrådet
Openalex Percentile: Top 44%
Advanced Numerical Methods in Computational Mathematics
0.37
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