747 research outputs found

    Preconditioning of weighted H(div)-norm and applications to numerical simulation of highly heterogeneous media

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    In this paper we propose and analyze a preconditioner for a system arising from a finite element approximation of second order elliptic problems describing processes in highly het- erogeneous media. Our approach uses the technique of multilevel methods and the recently proposed preconditioner based on additive Schur complement approximation by J. Kraus (see [8]). The main results are the design and a theoretical and numerical justification of an iterative method for such problems that is robust with respect to the contrast of the media, defined as the ratio between the maximum and minimum values of the coefficient (related to the permeability/conductivity).Comment: 28 page

    Space Decompositions and Solvers for Discontinuous Galerkin Methods

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    We present a brief overview of the different domain and space decomposition techniques that enter in developing and analyzing solvers for discontinuous Galerkin methods. Emphasis is given to the novel and distinct features that arise when considering DG discretizations over conforming methods. Connections and differences with the conforming approaches are emphasized.Comment: 2 pages 2 figures no table

    Analysis of a Helmholtz preconditioning problem motivated by uncertainty quantification

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    This paper analyses the following question: let Aj\mathbf{A}_j, j=1,2,j=1,2, be the Galerkin matrices corresponding to finite-element discretisations of the exterior Dirichlet problem for the heterogeneous Helmholtz equations ∇⋅(Aj∇uj)+k2njuj=−f\nabla\cdot (A_j \nabla u_j) + k^2 n_j u_j= -f. How small must ∥A1−A2∥Lq\|A_1 -A_2\|_{L^q} and ∥n1−n2∥Lq\|{n_1} - {n_2}\|_{L^q} be (in terms of kk-dependence) for GMRES applied to either (A1)−1A2(\mathbf{A}_1)^{-1}\mathbf{A}_2 or A2(A1)−1\mathbf{A}_2(\mathbf{A}_1)^{-1} to converge in a kk-independent number of iterations for arbitrarily large kk? (In other words, for A1\mathbf{A}_1 to be a good left- or right-preconditioner for A2\mathbf{A}_2?). We prove results answering this question, give theoretical evidence for their sharpness, and give numerical experiments supporting the estimates. Our motivation for tackling this question comes from calculating quantities of interest for the Helmholtz equation with random coefficients AA and nn. Such a calculation may require the solution of many deterministic Helmholtz problems, each with different AA and nn, and the answer to the question above dictates to what extent a previously-calculated inverse of one of the Galerkin matrices can be used as a preconditioner for other Galerkin matrices

    Preconditioning of block tridiagonal matrices

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    Preconditioning methods via approximate block factorization for block tridiagonal matrices are studied. Bounds for the resulting condition numbers are given, and two methods for the recursive construction of the approximate Schur complements are presented. Illustrations for elliptic problems are also given, including a study of sensitivity to jumps in the coefficients and of a suitably motidied Poincaré-Steklov operator on the continuous level

    Nonoverlapping domain decomposition preconditioners for discontinuous Galerkin approximations of Hamilton--Jacobi--Bellman equations

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    We analyse a class of nonoverlapping domain decomposition preconditioners for nonsymmetric linear systems arising from discontinuous Galerkin finite element approximation of fully nonlinear Hamilton--Jacobi--Bellman (HJB) partial differential equations. These nonsymmetric linear systems are uniformly bounded and coercive with respect to a related symmetric bilinear form, that is associated to a matrix A\mathbf{A}. In this work, we construct a nonoverlapping domain decomposition preconditioner P\mathbf{P}, that is based on A\mathbf{A}, and we then show that the effectiveness of the preconditioner for solving the} nonsymmetric problems can be studied in terms of the condition number κ(P−1A)\kappa(\mathbf{P}^{-1}\mathbf{A}). In particular, we establish the bound κ(P−1A)≲1+p6H3/q3h3\kappa(\mathbf{P}^{-1}\mathbf{A}) \lesssim 1+ p^6 H^3 /q^3 h^3, where HH and hh are respectively the coarse and fine mesh sizes, and qq and pp are respectively the coarse and fine mesh polynomial degrees. This represents the first such result for this class of methods that explicitly accounts for the dependence of the condition number on qq; our analysis is founded upon an original optimal order approximation result between fine and coarse discontinuous finite element spaces. Numerical experiments demonstrate the sharpness of this bound. Although the preconditioners are not robust with respect to the polynomial degree, our bounds quantify the effect of the coarse and fine space polynomial degrees. Furthermore, we show computationally that these methods are effective in practical applications to nonsymmetric, fully nonlinear HJB equations under hh-refinement for moderate polynomial degrees
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