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dc.contributor.authorLiu, Lulu
dc.contributor.authorKeyes, David E.
dc.date.accessioned2015-09-09T13:47:49Z
dc.date.available2015-09-09T13:47:49Z
dc.date.issued2015-06-02
dc.identifier.citationField-Split Preconditioned Inexact Newton Algorithms 2015, 37 (3):A1388 SIAM Journal on Scientific Computing
dc.identifier.issn1064-8275
dc.identifier.issn1095-7197
dc.identifier.doi10.1137/140970379
dc.identifier.urihttp://hdl.handle.net/10754/577006
dc.description.abstractThe multiplicative Schwarz preconditioned inexact Newton (MSPIN) algorithm is presented as a complement to additive Schwarz preconditioned inexact Newton (ASPIN). At an algebraic level, ASPIN and MSPIN are variants of the same strategy to improve the convergence of systems with unbalanced nonlinearities; however, they have natural complementarity in practice. MSPIN is naturally based on partitioning of degrees of freedom in a nonlinear PDE system by field type rather than by subdomain, where a modest factor of concurrency can be sacrificed for physically motivated convergence robustness. ASPIN, originally introduced for decompositions into subdomains, is natural for high concurrency and reduction of global synchronization. We consider both types of inexact Newton algorithms in the field-split context, and we augment the classical convergence theory of ASPIN for the multiplicative case. Numerical experiments show that MSPIN can be significantly more robust than Newton methods based on global linearizations, and that MSPIN can be more robust than ASPIN and maintain fast convergence even for challenging problems, such as high Reynolds number Navier--Stokes equations.
dc.language.isoen
dc.publisherSociety for Industrial & Applied Mathematics (SIAM)
dc.relation.urlhttp://epubs.siam.org/doi/10.1137/140970379
dc.rightsArchived with thanks to SIAM Journal on Scientific Computing
dc.subjectnonlinear equations
dc.subjectnonlinear preconditioning
dc.subjectfield splitting
dc.subjectNewton method
dc.subjectNavier–Stokes equations
dc.titleField-Split Preconditioned Inexact Newton Algorithms
dc.typeArticle
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentExtreme Computing Research Center
dc.identifier.journalSIAM Journal on Scientific Computing
dc.eprint.versionPublisher's Version/PDF
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personKeyes, David E.
kaust.personLiu, Lulu
refterms.dateFOA2018-06-14T09:15:56Z
dc.date.published-online2015-06-02
dc.date.published-print2015-01


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