Non-modal analysis of multigrid schemes for the high-order flux reconstruction method

Aurelio Hurtado-De-mendoza, Jiaqing Kou, Saumitra Joshi, Kunal Puri, Charles Hirsch, Esteban Ferrer

Research output: Contribution to journalConference articlepeer-review

Abstract

The present study introduces an application of the non-modal analysis to multigrid operators with explicit Runge-Kutta smoothers in the context of Flux Reconstruction discretizations of the linear convection-diffusion equation. A dissipation curve is obtained that reflects upon the convergence properties of the multigrid operator. The number of smoothing steps, the type of cycle (V/W) and the combination of p-and h-multigrid are taken into account in order to find those configurations which yield faster convergence rates. The analysis is carried out for polynomial orders up to P = 6, in 1D and 2D for varying degrees of convection (Péclet number), as well as for high aspect ratio cells. The non-modal analysis can support existing evidence on the behaviour of multigrid schemes. W-cycles, a higher number of coarse-level sweeps or the combined use of hp-multigrid are shown to increase the error dissipation, while higher degrees of convection and/or high aspect-ratio cells both decrease the error dissipation rate.

Original languageEnglish
Pages (from-to)1-12
Number of pages12
JournalWorld Congress in Computational Mechanics and ECCOMAS Congress
Volume700
DOIs
StatePublished - 2021
Externally publishedYes
Event14th World Congress of Computational Mechanics and ECCOMAS Congress, WCCM-ECCOMAS 2020 - Virtual, Online
Duration: 11 Jan 202115 Jan 2021

Keywords

  • Convergence acceleration
  • Flux Reconstruction
  • High-order
  • Multigrid
  • Non-modal analysis
  • Stability

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