首页|Iterative Subregion Correction Preconditioners with Adaptive Tolerance for Problems with Geometrically Localized Stiffness

Iterative Subregion Correction Preconditioners with Adaptive Tolerance for Problems with Geometrically Localized Stiffness

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We present a class of preconditioners for the linear systems resulting from a finite ele-ment or discontinuous Galerkin discretizations of advection-dominated problems.These preconditioners are designed to treat the case of geometrically localized stiffness,where the convergence rates of iterative methods are degraded in a localized subregion of the mesh.Slower convergence may be caused by a number of factors,including the mesh size,ani-sotropy,highly variable coefficients,and more challenging physics.The approach taken in this work is to correct well-known preconditioners such as the block Jacobi and the block incomplete LU(ILU)with an adaptive inner subregion iteration.The goal of these precon-ditioners is to reduce the number of costly global iterations by accelerating the convergence in the stiff region by iterating on the less expensive reduced problem.The tolerance for the inner iteration is adaptively chosen to minimize subregion-local work while guarantee-ing global convergence rates.We present analysis showing that the convergence of these preconditioners,even when combined with an adaptively selected tolerance,is independ-ent of discretization parameters(e.g.,the mesh size and diffusion coefficient)in the sub-region.We demonstrate significant performance improvements over black-box precondi-tioners when applied to several model convection-diffusion problems.Finally,we present performance results of several variations of iterative subregion correction preconditioners applied to the Reynolds number 2.25 x 106 fluid flow over the NACA 0012 airfoil,as well as massively separated flow at 30° angle of attack.

Subregion correctionNested KrylovGeometrically localized stiffness

Michael Franco、Per-Olof Persson、Will Pazner

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Department of Mathematics,University of California,Berkeley,Berkeley,CA 94720-3840,USA

Fariborz Maseeh Department of Mathematics and Statistics,Portland State University,Portland,OR 97201,USA

2024

应用数学与计算数学学报
上海大学

应用数学与计算数学学报

影响因子:0.165
ISSN:1006-6330
年,卷(期):2024.6(2)