A stable Petrov-Galerkin method for convection-dominated problems
✍ Scribed by Regina C. Almeida; Renato S. Silva
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 1004 KB
- Volume
- 140
- Category
- Article
- ISSN
- 0045-7825
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✦ Synopsis
In this paper, a new Petrov-Galerkin formulation for solving convection-dominated problems is presented. The method developed achieves the quasi-optimal convergence rates when the solution is regular and provides the necessary stability to avoid spurious oscillations when strong gradients are present. Such important properties allow the use of p refinement to improve the solution in regions with discontinuities because of the stability engendered by the new Petrov-Galerkin method. In this matter, a proper evaluation of the intrinsic time scale function, appearing in the design of this method, is crucial to guarantee the required accuracy.
📜 SIMILAR VOLUMES
The spectral Lagrange-Galerkin method is a numerical technique for time-dependent convection-diffusion problems based on combining a Lagrangian formulation of the equations with the spectral method. The resulting scheme can be shown to be unconditionally stable for linear advection-diffusion equatio
The Petrov-Galerkin method is applied to transient convective diffusion problems with convection dominance. Weighting functions are used which differ from the shape functions by both symmetric and non-symmetric modifications. It is proved that the symmetric modifications largely influence the accura
The nearly-optimal Petrov-Galerkin (NOPG) method is employed to improve finite element computation of convection-dominated transport phenomena. The design of the NOPG method for convection-diffusion is based on consideration of the advective limit. Nonetheless, the resulting method is applicable to
## Abstract In this work, a stable Petrov–Galerkin formulation is combined with an __hp__‐adaptive refinement strategy. The stability engendered by this formulation allows the use of high interpolation element order in regions with steep gradients. The new __hp__‐adaptive strategy, originally propo