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Evaluation of multilevel sequentially semiseparable preconditioners on computational fluid dynamics benchmark problems using Incompressible Flow and Iterative Solver Software
- Source :
- Mathematical Methods in the Applied Sciences, 41(3)
- Publication Year :
- 2018
-
Abstract
- This paper studies a new preconditioning technique for sparse systems arising from discretized partial differential equations in computational fluid dynamics problems. This preconditioning technique exploits the multilevel sequentially semiseparable (MSSS) structure of the system matrix. MSSS matrix computations give a data-sparse way to approximate the LU factorization of a sparse matrix from discretized partial differential equations in linear computational complexity with respect to the problem size. In contrast to the standard block diagonal and block upper-triangular preconditioners, we exploit the global MSSS structure of the 2×2 block system from the discretized Stokes equation and linearized Navier-Stokes equation. This avoids approximating the Schur complement explicitly, which is a big advantage over standard block preconditioners. Through numerical experiments on standard computational fluid dynamics benchmark problems in Incompressible Flow and Iterative Solver Software, we show the performance of the MSSS preconditioners. They indicate that the global MSSS preconditioner not only yields mesh size independent convergence but also gives viscosity parameter and Reynolds number independent convergence. Compared with the algebraic multigrid (AMG) method and the geometric multigrid (GMG) method for block preconditioners, the MSSS preconditioning technique is more robust than both the AMG method and GMG method, and considerably faster than the AMG method. Copyright © 2015 John Wiley & Sons, Ltd.
- Subjects :
- 0209 industrial biotechnology
Mathematical optimization
multilevel sequentially semiseparable matrices
General Mathematics
010103 numerical & computational mathematics
02 engineering and technology
01 natural sciences
law.invention
Mathematics::Numerical Analysis
preconditioners
020901 industrial engineering & automation
Multigrid method
law
computational fluid dynamics
partial differential equations
Applied mathematics
0101 mathematics
Mathematics
Sparse matrix
Partial differential equation
Preconditioner
General Engineering
Block matrix
Solver
Computer Science::Numerical Analysis
LU decomposition
Schur complement
multigrid method
Subjects
Details
- Language :
- English
- ISSN :
- 01704214
- Volume :
- 41
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Mathematical Methods in the Applied Sciences
- Accession number :
- edsair.doi.dedup.....09f2c1c5f9af444c508d175444d655dd