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Nonincremental proper generalized decomposition solution of parametric uncoupled models defined in evolving domains

Article dans une revue avec comité de lecture
Auteur
ccAMMAR, Amine
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccCUETO, Elias
161327 Aragón Institute of Engineering Research [Zaragoza] [I3A]
ccCHINESTA SORIA, Francisco
10921 Institut de Recherche en Génie Civil et Mécanique [GeM]

URI
http://hdl.handle.net/10985/10287
DOI
10.1002/nme.4413
Date
2012
Journal
International Journal for Numerical Methods in Engineering

Résumé

This work addresses the recurrent issue related to the existence of reduced bases related to the solution of parametric models defined in evolving domains. In this first part of the work, we address the case of decoupled kinematics, that is, models whose solution does not affect the domain in which they are defined. The chosen framework considers an updated Lagrangian description of the kinematics, solved by using natural neighbor Galerkin methods within a nonincremental space–time framework that can be generalized for addressing parametric models. Examples showing the performance and potentialities of the proposed methodology are included.

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  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)

Documents liés

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    Article dans une revue avec comité de lecture
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    Optimization of manufacturing processes or structures involves the optimal choice of many parameters (process parameters, material parameters or geometrical parameters). Usual strategies proceed by defining a trial choice ...
  • Towards a high-resolution numerical strategy based on separated representations 
    Article dans une revue avec comité de lecture
    ccCUETO, Elias; GONZALEZ, David; ccAMMAR, Amine; ccCHINESTA SORIA, Francisco (Springer Link, 2008)
    Many models in Science and Engineering are defined in spaces (the so-called conformation spaces) of high dimensionality. In kinetic theory, for instance, the micro scale of a fluid evolves in a space whose number of ...
  • Data-driven upscaling of orientation kinematics in suspensions of rigid fibres 
    Article dans une revue avec comité de lecture
    SCHEUER, Adrien; ccCUETO, Elias; KEUNINGS, Roland; ADVANI, Suresh G.; ccABISSET-CHAVANNE, Emmanuelle; ccAMMAR, Amine; ccCHINESTA SORIA, Francisco (Tech Science Press, 2018)
    Describing the orientation state of the particles is often critical in fibre suspension applications. Macroscopic descriptors, the so-called second-order orientation tensor (or moment) leading the way, are often preferred ...
  • A Multidimensional Data-Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition 
    Article dans une revue avec comité de lecture
    IBAÑEZ, Ruben; ccABISSET-CHAVANNE, Emmanuelle; ccAMMAR, Amine; GONZALEZ, David; ccCUETO, Elias; HUERTA, Antonio; DUVAL, Jean-Louis; ccCHINESTA SORIA, Francisco (Wiley, 2018)
    Sparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves the need for large amount of data, unfeasible in such a high dimensional ...
  • Advanced separated spatial representations for hardly separable domains 
    Article dans une revue avec comité de lecture
    GHNATIOS, Chady; ccABISSET-CHAVANNE, Emmanuelle; ccAMMAR, Amine; ccCUETO, Elias; ccDUVAL, Jean-Louis; ccCHINESTA SORIA, Francisco (Elsevier, 2019)
    This work aims at proposing a new procedure for parametric problems whose separated representation has been considered difficult, or whose SVD compression impacted the results in terms of performance and accuracy. The ...

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