A multiplicative Schwarz method with active subdomains for transient convection-diffusion problems

An efficient algorithm to find the solution of transient convection–diffusion problems with dominant convection is presented. The main idea is to follow the solution front and activate those subdomains where the solution satisfies a given threshold value. We call this novel method ‘the multiplicativ...

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Veröffentlicht in:International journal for numerical methods in biomedical engineering Jg. 26; H. 12; S. 1573 - 1585
Hauptverfasser: Sandoval, M. L., Rodríguez-Ferran, A.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Chichester, UK John Wiley & Sons, Ltd 01.12.2010
Wiley
Schlagworte:
activated-carbon filters
active subdomains
Algorithms
Automotive components
Automotive industry
Cholesky factorization
Conjugate gradient method
Convection
Convection and heat transfer
convection-diffusion
Emissions control
Exact sciences and technology
Fluid dynamics
Fundamental areas of phenomenology (including applications)
General theory
Mathematical models
multiplicative Schwarz method
Physics
symmetric linear systems
Turbulent flows, convection, and heat transfer
Transient response
Convection diffusion equation
Matrix factorization
Conjugate gradient methods
Experimental study
symmetric linear systems
Convection
convection-diffusion
active subdomains
Filters
activated-carbon filters
Activated carbon
Automotive industry
Diffusion equation
Domain decomposition
Preconditioning
Cholesky factorization
Heat transfer
multiplicative Schwarz method
ISSN:2040-7939, 2040-7947, 2040-7947
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Beschreibung
Zusammenfassung:An efficient algorithm to find the solution of transient convection–diffusion problems with dominant convection is presented. The main idea is to follow the solution front and activate those subdomains where the solution satisfies a given threshold value. We call this novel method ‘the multiplicative Schwarz method with active subdomains’, and it is motivated by the solution of a problem from activated‐carbon filters used in the automotive industry to reduce emissions. Numerical experiments show that this method is more efficient than the preconditioned conjugate gradient method with an incomplete Cholesky factorization. Copyright © 2009 John Wiley & Sons, Ltd.
Bibliographie:Ministerio de Ciencia e Innovación - No. CGL2008-06003-C03-02/CLI; No. DPI2007-62395
istex:E1751912513EEADD47DEB1B1BDF0291FB95C74E0
ArticleID:CNM1239
ark:/67375/WNG-FF6KWK1J-F
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:2040-7939
2040-7947
2040-7947
DOI:10.1002/cnm.1239