A priori and a posteriori error analysis of a staggered discontinuous Galerkin method for convection dominant diffusion equations

Lina Zhao, Eun Jae Park

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

An upwind staggered discontinuous Galerkin (upwind-SDG) method for convection dominant diffusion problems is developed. Optimal a priori error estimates can be achieved for both the scalar and vector functions approximated by the method. To efficiently capture the layer problems, we propose a robust a posteriori error estimator for upwind-SDG method measured in a natural norm and a semi-norm associated with the convective derivative. The semi-norm can be neglected when the mesh Péclet number is sufficiently small. The key is to bound the conforming contribution by the dual norm of the residual, and the robustness arises from the incorporation of the semi-norm associated with the convective derivative. Finally, various numerical examples are tested to illustrate the performance of the robust a posteriori error estimator. The results indicate that optimal convergence rates can be achieved and the singularity can be well-captured by the proposed error estimator.

Original languageEnglish
Pages (from-to)63-83
Number of pages21
JournalJournal of Computational and Applied Mathematics
Volume346
DOIs
Publication statusPublished - 2019 Jan 15

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A Posteriori Error Analysis
Seminorm
Discontinuous Galerkin Method
Galerkin methods
Diffusion equation
Error analysis
Convection
A Posteriori Error Estimators
Norm
Derivative
Optimal Convergence Rate
A Priori Error Estimates
Optimal Error Estimates
Error Estimator
Diffusion Problem
Derivatives
Scalar
Mesh
Singularity
Robustness

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics

Cite this

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abstract = "An upwind staggered discontinuous Galerkin (upwind-SDG) method for convection dominant diffusion problems is developed. Optimal a priori error estimates can be achieved for both the scalar and vector functions approximated by the method. To efficiently capture the layer problems, we propose a robust a posteriori error estimator for upwind-SDG method measured in a natural norm and a semi-norm associated with the convective derivative. The semi-norm can be neglected when the mesh P{\'e}clet number is sufficiently small. The key is to bound the conforming contribution by the dual norm of the residual, and the robustness arises from the incorporation of the semi-norm associated with the convective derivative. Finally, various numerical examples are tested to illustrate the performance of the robust a posteriori error estimator. The results indicate that optimal convergence rates can be achieved and the singularity can be well-captured by the proposed error estimator.",
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