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Modelling and simulation of a polluted water pumping process

dc.contributor.authorAlavani, Chitra
dc.contributor.authorGlowinski, Roland
dc.contributor.authorGomez, Susana
dc.contributor.authorIvorra, Benjamín Pierre Paul
dc.contributor.authorJoshi, Pallavi
dc.contributor.authorRamos Del Olmo, Ángel Manuel
dc.date.accessioned2023-06-20T00:22:43Z
dc.date.available2023-06-20T00:22:43Z
dc.date.issued2010
dc.description.abstractThe objective of this article is to discuss the modelling and simulation of the motion of oil spots in the open sea, and the effect on the pollutant concentration when a polluted water pumping ship follows a pre-assigned trajectory to remove the pollutant. We assume here that the oil spots motion is due to the coupling of diffusion, the transport from the wind, sea currents and pumping process and the reaction due to the extraction of oil, implying that the mathematical model will be of advection-reaction-diffusion type. Our discussion includes the description of a parallelization of the selected numerical procedure. We present some results of numerical experiments showing that indeed the parallelization makes the model evaluation more efficient
dc.description.departmentDepto. de Análisis Matemático y Matemática Aplicada
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.facultyInstituto de Matemática Interdisciplinar (IMI)
dc.description.refereedTRUE
dc.description.sponsorshipSpanish Ministry of Science and Innovation
dc.description.sponsorshipMOMAT
dc.description.sponsorshipScientific Computing Advanced Training
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/17681
dc.identifier.doi10.1016/j.mcm.2009.11.023
dc.identifier.issn0895-7177
dc.identifier.officialurlhttp://www.sciencedirect.com/science/article/pii/S0895717709004221
dc.identifier.relatedurlhttp://www.sciencedirect.com
dc.identifier.urihttps://hdl.handle.net/20.500.14352/42480
dc.issue.number5-6
dc.journal.titleMathematical and Computer Modelling
dc.language.isoeng
dc.page.final472
dc.page.initial461
dc.publisherPergamon-Elsevier Science LTD
dc.relation.projectIDMTM2008-04621
dc.relation.projectID910480
dc.relation.projectID2005-2008
dc.rights.accessRightsrestricted access
dc.subject.cdu517.95
dc.subject.keywordModelling
dc.subject.keywordAdvection-reaction-diffusion equation
dc.subject.keywordUpwind scheme
dc.subject.keywordFinite volume scheme
dc.subject.keywordParallelization
dc.subject.keywordEa pollution
dc.subject.ucmAnálisis matemático
dc.subject.unesco1202 Análisis y Análisis Funcional
dc.titleModelling and simulation of a polluted water pumping process
dc.typejournal article
dc.volume.number51
dcterms.referencesR. Eymard, T. Gallouet, R. Herbin, A. Michel, Convergence of a finite volume scheme for nonlinear degenerate parabolic equations, Numer. Math. 92 (1) (2002) 4182. C. Lanczos, Solution of systems of linear equations by minimized iterations, J. Res. Natl. Bur. Stand. 49 (1952) 33-53. R. Fletcher, Conjugate gradient methods for indefinite systems, in: G.A. Watson (Ed.), Proc. Dundee Conference on Numerical Analysis, in: Lecture Notes in Mathematics, vol. 506, Springer-Verlag, Berlin, 1976, pp. 73-89. R. Freund, N. Nachtigal, QMR: A quasi-minimal residual method for non-hermitian linear systems, Numer. Math. 60 (1991) 315-339. Q. Ye, A convergence analysis of nonsymmetric Lanczos algorithms, Math. Comp. 56 (1991) 677-691. H.A. Van der Vorst, Bi-CGSTAB: A fast and smoothly converging variant of Bi-CG for the solution of nonsymmetric linear systems, SIAM J. Sci. Stat.Comput. 13 (1992) 631-644. G.L.G. Sleijpen, H.A. van der Vorst, Maintaining convergence properties of BiCGstab methods in finite precision arithmetic, Numer. Algorithms 10 (1995) 203-223. T. Gu, X. Zuo, X. Liu, P. Li, An improved parallel hybrid bi-conjugate gradient method suitable for distributed parallel computing, J. Comput. Appl. Math.226 (1) (2009) 55-65. G. Golub, J.M. Ortega, Scientific Computing: An Introduction with Parallel Computing, Academic Press, CA,San Diego, 1993. J.G. Lewis, D.G. Payne, R.A. van de Gejin, Matrix-vector multiplication and conjugate gradient algorithms on distributed memory computers, in:Proceedings ofn Supercomputing'93, 1993, pp. 15-19. R. Glowinski, P. Neittaanmaki, Partial Differential Equations, in: Modelling and Numerical Simulation, Series: Computational Methods in Applied Sciences, vol. 16,Springer, 2008. W. Hundsdorfer, J.G. Verwer, Numerical Solution of Time-Dependent Advection-Diffusion-Reaction Equations, in:Springer Series in Comput. Math.,vol. 33, 2003. J.G. Verwer, B.P. Sommeijer, W. Hundsdorfer, RKC time-stepping for advection-diffusion-reaction problems, J.Comput. Phys. 201 (2004) 61-79. M.P. Calvo, J. de Frutos, J. Novo, Linearly implicit RungeKutta methods for advection-reaction-diffusion equations, Appl. Numer. Math. 37 (4) (2001) 535-549. R.J. LeVeque, Finite Volume Methods for Hyperbolic Problems, first ed., Cambridge University Press, 2002.
dspace.entity.typePublication
relation.isAuthorOfPublication6d5e1204-9b8a-40f4-b149-02d32e0bbed2
relation.isAuthorOfPublication581c3cdf-f1ce-41e0-ac1e-c32b110407b1
relation.isAuthorOfPublication.latestForDiscovery6d5e1204-9b8a-40f4-b149-02d32e0bbed2

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