A new relaxed PSS preconditioner for nonsymmetric saddle point problems

Ke Zhang, Ju-Li Zhang and Chuan-Qing Gu

Applied Mathematics and Computation, 2017, vol. 308, issue C, 115-129

Abstract: A new relaxed PSS-like iteration scheme for the nonsymmetric saddle point problem is proposed. As a stationary iterative method, the new variant is proved to converge unconditionally. When used for preconditioning, the preconditioner differs from the coefficient matrix only in the upper-right components. The theoretical analysis shows that the preconditioned matrix has a well-clustered eigenvalues around (1, 0) with a reasonable choice of the relaxation parameter. This sound property is desirable in that the related Krylov subspace method can converge much faster, which is validated by numerical examples.

Keywords: Saddle point problem; Preconditioning; Krylov subspace method; Navier–Stokes equation; GMRES (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:308:y:2017:i:c:p:115-129

DOI: 10.1016/j.amc.2017.03.022

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