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hal.structure.identifierInstitut de Recherche en Génie Civil et Mécanique [GeM]
dc.contributor.authorCHINESTA, Francisco
hal.structure.identifierLaboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
dc.contributor.authorAMMAR, Amine
dc.date.accessioned2021-05-14T09:45:32Z
dc.date.available2021-05-14T09:45:32Z
dc.date.conference2007
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76944
dc.description.abstractEnDescription of macromolecular materials involves numerous computational challenges. Accurate descriptions of such materials need for a multiscale description and the definition of pertinent bridges between the different scales. The finest description starts at the atomic level where quantum mechanics leads to molecular dynamics simulations. The next description scale introduces some molecular simplifications leading to a coarse grained molecular dynamics, the DPD being one of such approaches. Other descriptions consider molecules as interacting multi-bead-springs or multi-bead-rods. At this level Brownian dynamics simulations are usually employed. However, this level of description requires intensive computation resources with its significant unfavorable impact on the simulation performances (CPU time). For this reasons sometimes kinetic theory descriptions are preferred. In that description, the molecular conformation is described from a probability density function whose evolution is governed by the Fokker-Planck equation. This approach, despite its mathematical simplicity, introduces a density function that is defined in a multidimensional space, and then the associated partial differential equations must be solved in a multidimensional domain. To circumvent the curse of dimensionality that these high-dimensional partial differential equations induce, stochastic techniques have been applied intensively in the last decade. Some improvements have been proposed, the Brownian Configurations Fields being one of such approaches. Recently some incipient techniques based on sparse grids or those based on separated representations have allowed solving models defined in highly multidimensional spaces. The aim of this paper is identify the main challenges and recent advances in the multiscale modeling just described.
dc.language.isoen
dc.subject.enModel reduction
dc.subject.enNano-science
dc.subject.enComplex fluids
dc.subject.enNumerical Modeling
dc.title.enSome Unsolved Issues in the Multi-scale Modeling of Complex Fluids and the Related Forming Processes
dc.typeCommunication dans un congrès avec actes
dc.subject.halSciences de l'ingénieur [physics]/Mécanique [physics.med-ph]
dc.subject.halSciences de l'ingénieur [physics]/Matériaux
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.countryJP
bordeaux.title.proceeding11th International Conference on the Enhancement and Promotion of Computational Methods in Engineering and Science (EPMESC XI)
bordeaux.conference.cityKyoto
bordeaux.peerReviewedoui
hal.identifierhal-01008941
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01008941v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=CHINESTA,%20Francisco&AMMAR,%20Amine&rft.genre=proceeding


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