Issue |
ESAIM: M2AN
Volume 53, Number 2, March-April 2019
|
|
---|---|---|
Page(s) | 503 - 522 | |
DOI | https://doi.org/10.1051/m2an/2018054 | |
Published online | 24 April 2019 |
Hybrid Discontinuous Galerkin methods with relaxed H(div)-conformity for incompressible flows. Part II
1
Institute for Analysis and Scientific Computing, TU Wien, Austria
2
Institute for Numerical and Applied Mathematics, University of Göttingen, Germany
* Corresponding author: lehrenfeld@math.uni-goettingen.de
Received:
17
May
2018
Accepted:
18
September
2018
The present work is the second part of a pair of papers, considering Hybrid Discontinuous Galerkin methods with relaxed H(div)-conformity. The first part mainly dealt with presenting a robust analysis with respect to the mesh size h and the introduction of a reconstruction operator to restore divergence-conformity and pressure robustness (pressure independent velocity error estimates) using a modified force discretization. The aim of this part is the presentation of a high order polynomial robust analysis for the relaxed H(div)-conforming Hybrid Discontinuous Galerkin discretization of the two dimensional Stokes problem. It is based on the recently proven polynomial robust LBB-condition for BDM elements, Lederer and Schöberl (IMA J. Numer. Anal. (2017)) and is derived by a direct approach instead of using a best approximation Céa like result. We further treat the impact of the reconstruction operator on the hp analysis and present a numerical investigation considering polynomial robustness. We conclude the paper presenting an efficient operator splitting time integration scheme for the Navier–Stokes equations which is based on the methods recently presented in Lehrenfeld and Schöberl (Comp. Methods Appl. Mech. Eng. 307 (2016) 339–361) and includes the ideas of the reconstruction operator.
Mathematics Subject Classification: 35Q30 / 65N12 / 65N22 / 65N30
Key words: Stokes equations / Hybrid Discontinuous Galerkin methods / H(div)-conforming finite elements / pressure robustness / high order methods
© EDP Sciences, SMAI 2019
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