A posterior% error estimates are derived for a stabilized discontinuous Galerkin method (DGM) [l]. Equivalence between the error norm and the norm of the residual functional is proved, and consequently, global error estimates are obtained by estimating the norm of the residual. Oneand two-dimensiona
A posteriori estimates for the Bubble Stabilized Discontinuous Galerkin Method
β Scribed by Benjamin Stamm
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 1010 KB
- Volume
- 235
- Category
- Article
- ISSN
- 0377-0427
No coin nor oath required. For personal study only.
β¦ Synopsis
a b s t r a c t
In this paper, two reliable and efficient a posteriori error estimators for the Bubble Stabilized Discontinuous Galerkin (BSDG) method for diffusion-reaction problems in two and three dimensions are derived. The theory is followed by some numerical illustrations.
π SIMILAR VOLUMES
In this paper we present a residual-based a posteriori error estimate of a natural mesh dependent energy norm of the error in a family of discontinuous Galerkin approximations of elliptic problems. The theory is developed for an elliptic model problem in two and three spatial dimensions and general
## Abstract In this article, we develop functional a posteriori error estimates for discontinuous Galerkin (DG) approximations of elliptic boundaryβvalue problems. These estimates are based on a certain projection of DG approximations to the respective energy space and functional a posteriori estim
We analyze the spatial discretization errors associated with solutions of one-dimensional hyperbolic conservation laws by discontinuous Galerkin methods (DGMs) in space. We show that the leading term of the spatial discretization error with piecewise polynomial approximations of degree p is proporti
We consider some (anisotropic and piecewise constant) diffusion problems in domains of R 2 , approximated by a discontinuous Galerkin method with polynomials of any fixed degree. We propose an a posteriori error estimator based on gradient recovery by averaging. It is shown that this estimator gives