The adaptive finite element method (AFEM) is an effective numerical tool for solving linear and nonlinear PDEs. A proper local refinement plays a key role in AFEM and relies on proper a posteriori error estimators. In this contribution, we introduce a pointwise a posteriori error estimator for the symmetric interior penalty discontinuous Galerkin (SIPG) approximation of the elliptic obstacle problem.

Ayuso de Dios, B., Gudi, T., Porwal, K. (2022). A Posteriori Error Estimates in Maximum Norm for Interior Penalty Discontinuous Galerkin Approximation of the Obstacle Problem. In Domain Decomposition Methods in Science and Engineering XXVI (pp.205-212). Springer [10.1007/978-3-030-95025-5_20].

A Posteriori Error Estimates in Maximum Norm for Interior Penalty Discontinuous Galerkin Approximation of the Obstacle Problem

Ayuso de Dios, B
Primo
;
2022

Abstract

The adaptive finite element method (AFEM) is an effective numerical tool for solving linear and nonlinear PDEs. A proper local refinement plays a key role in AFEM and relies on proper a posteriori error estimators. In this contribution, we introduce a pointwise a posteriori error estimator for the symmetric interior penalty discontinuous Galerkin (SIPG) approximation of the elliptic obstacle problem.
paper
Discontinuous Galerkin; obstacle problem; a-posteriori error analysis
English
26th International Conference on Domain Decomposition Methods, 2020 - 7 December 2020 through 12 December 2020
2020
Brenner, SC; Chung, E; Klawonn, A; Kwok, F; Xu, J; Zou, J
Domain Decomposition Methods in Science and Engineering XXVI
978-3-030-95024-8
16-mar-2023
2022
145
205
212
reserved
Ayuso de Dios, B., Gudi, T., Porwal, K. (2022). A Posteriori Error Estimates in Maximum Norm for Interior Penalty Discontinuous Galerkin Approximation of the Obstacle Problem. In Domain Decomposition Methods in Science and Engineering XXVI (pp.205-212). Springer [10.1007/978-3-030-95025-5_20].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/411279
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