Robust Spectral Preconditioning for High-Péclet Number Convection-Diffusion

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Authors: Lukas Holbach, Peter Bastian, Robert Scheichl
Cited by: 0

Abstract

Abstract We introduce a two-level hybrid restricted additive Schwarz (RAS) preconditioner for heterogeneous steady-state convection-diffusion equations at high Péclet numbers. Our construction builds on the multiscale spectral generalized finite element method (MS-GFEM), wherein the coarse space is spanned by locally optimal basis functions obtained from local generalized eigenproblems on operator-harmonic spaces. Extending the theory of [36] to convection-diffusion problems in conservation form, we establish exponential convergence of the MS-GFEM approximation with respect to the dimension of the local approximation space. Rewriting MS-GFEM as a RAS-type iteration, we show for coercive problems that this exponential convergence property is inherited by the RAS-type iterative method (at least in the continuous setting). Employed as a preconditioner within the generalized minimal residual method (GMRES), the resulting method requires only a few iterations for high accuracy even with low-dimensional coarse spaces. Through extensive numerical experiments on problems with high-contrast diffusion and non-divergence-free, rotating velocity fields, we demonstrate robustness with respect to the grid Péclet number and the number of subdomains (tested up to $$10^5$$ 10 5 subdomains), while coarse-space dimensions remain small as grid Péclet numbers increase. By adapting the coarse space and oversampling size, we are able to achieve arbitrarily fast convergence of preconditioned GMRES. As an extension, for which we do not have theory yet, we show effectiveness of the method even for indefinite problems and in the vanishing-diffusion limit.

Fields of Study & Subjects

Advanced Numerical Methods in Computational Mathematics Model Reduction and Neural Networks NMR spectroscopy and applications

Publication details

Journal / source
Journal of Scientific Computing
Volume
108
Issue
2
Publication date
13 June 2026
Language
EN