Matrix-Free Monolithic Multigrid Methods for Stokes and Generalized Stokes Problems

Research output: Contribution to journalArticleResearchpeer review

Authors

  • Daniel Jodlbauer
  • Ulrich Langer
  • Thomas Wick
  • Walter Zulehner

External Research Organisations

  • Austrian Academy of Sciences
  • Johannes Kepler University of Linz (JKU)
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Details

Original languageEnglish
Pages (from-to)A1599-A1627
JournalSIAM Journal on Scientific Computing
Volume46
Issue number3
Early online date9 May 2024
Publication statusPublished - 2024

Abstract

We consider the widely used continuous \scrQk-\scrQk-1 quadrilateral or hexahedral Taylor-Hood elements for the finite element discretization of the Stokes and generalized Stokes systems in two and three spatial dimensions. For the fast solution of the corresponding symmetric, but indefinite system of finite element equations, we propose and analyze matrix-free monolithic geometric multigrid solvers that are based on appropriately scaled Chebyshev-Jacobi smoothers. The analysis is based on results by Schöberl and Zulehner (2003). We present and discuss several numerical results for typical benchmark problems.

Keywords

    matrix-free implementation, mixed finite element discretization, multigrid methods, Stokes and generalized Stokes problems

ASJC Scopus subject areas

Cite this

Matrix-Free Monolithic Multigrid Methods for Stokes and Generalized Stokes Problems. / Jodlbauer, Daniel; Langer, Ulrich; Wick, Thomas et al.
In: SIAM Journal on Scientific Computing, Vol. 46, No. 3, 2024, p. A1599-A1627.

Research output: Contribution to journalArticleResearchpeer review

Jodlbauer D, Langer U, Wick T, Zulehner W. Matrix-Free Monolithic Multigrid Methods for Stokes and Generalized Stokes Problems. SIAM Journal on Scientific Computing. 2024;46(3):A1599-A1627. Epub 2024 May 9. doi: 10.48550/arXiv.2205.15770, 10.1137/22M1504184
Jodlbauer, Daniel ; Langer, Ulrich ; Wick, Thomas et al. / Matrix-Free Monolithic Multigrid Methods for Stokes and Generalized Stokes Problems. In: SIAM Journal on Scientific Computing. 2024 ; Vol. 46, No. 3. pp. A1599-A1627.
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