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    Robust Solvers for Symmetric Positive Definite Operators and Weighted Poincaré Inequalities

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    Type
    Book Chapter
    Authors
    Efendiev, Yalchin R. cc
    Galvis, Juan
    Lazarov, Raytcho
    Willems, Joerg
    KAUST Grant Number
    KUS-C1-016-04
    Date
    2012
    Permanent link to this record
    http://hdl.handle.net/10754/599528
    
    Metadata
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    Abstract
    An abstract setting for robustly preconditioning symmetric positive definite (SPD) operators is presented. The term "robust" refers to the property of the condition numbers of the preconditioned systems being independent of mesh parameters and problem parameters. Important instances of such problem parameters are in particular (highly varying) coefficients. The method belongs to the class of additive Schwarz preconditioners. The paper gives an overview of the results obtained in a recent paper by the authors. It, furthermore, focuses on the importance of weighted Poincaré inequalities, whose notion is extended to general SPD operators, for the analysis of stable decompositions. To demonstrate the applicability of the abstract preconditioner the scalar elliptic equation and the stream function formulation of Brinkman's equations in two spatial dimensions are considered. Several numerical examples are presented. © 2012 Springer-Verlag.
    Citation
    Efendiev Y, Galvis J, Lazarov R, Willems J (2012) Robust Solvers for Symmetric Positive Definite Operators and Weighted Poincaré Inequalities. Lecture Notes in Computer Science: 43–51. Available: http://dx.doi.org/10.1007/978-3-642-29843-1_4.
    Sponsors
    The research of Y. Efendiev was partially supported bythe DOE and NSF (DMS 0934837, DMS 0724704, and DMS 0811180). The re-search of Y. Efendiev, J. Galvis, and R. Lazarov was supported in parts by awardKUS-C1-016-04, made by King Abdullah University of Science and Technology(KAUST). The research of R. Lazarov and J. Willems was supported in partsby NSF Grant DMS-1016525.
    Publisher
    Springer Nature
    Journal
    Lecture Notes in Computer Science
    DOI
    10.1007/978-3-642-29843-1_4
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-3-642-29843-1_4
    Scopus Count
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