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Practical aspects of p‐multigrid discontinuous Galerkin solver for steady and unsteady RANS simulations
Author(s) -
Jiang Zhenhua,
Yan Chao,
Yu Jian,
Yuan Wu
Publication year - 2015
Publication title -
international journal for numerical methods in fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 112
eISSN - 1097-0363
pISSN - 0271-2091
DOI - 10.1002/fld.4035
Subject(s) - multigrid method , reynolds averaged navier–stokes equations , solver , mathematics , discretization , computational fluid dynamics , discontinuous galerkin method , navier–stokes equations , robustness (evolution) , mathematical optimization , computer science , compressibility , finite element method , partial differential equation , mathematical analysis , mechanics , physics , biochemistry , chemistry , gene , thermodynamics
Summary Efficient and robust p ‐multigrid solvers are presented for solving the system arising from high‐order discontinuous Galerkin discretizations of the compressible Reynolds‐Averaged Navier–Stokes (RANS) equations. Two types of multigrid methods and a multigrid preconditioned Newton–Krylov method are investigated, and both steady and unsteady algorithms are considered in this paper. For steady algorithms, a new strategy is introduced to determine the CFL number, which has been proved to be critical in achieving the effective and stable convergence for p ‐multigrid methods. We also suggest a modified smoothing technique to further improve the efficiency of the algorithms. For unsteady algorithms, special attention has been paid to the cycling strategy and the full multigrid technique, and we point out a significant difference on the parameter selection for unsteady computations. The capabilities of the resulted solvers have been examined by performing steady and unsteady RANS simulations. Comparative assessment in terms of efficiency, robustness, and memory consumption are carried out for all solvers. Copyright © 2015 John Wiley & Sons, Ltd.

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