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Ideal minimal residual-based proper generalized decomposition for non-symmetric multi-field models – Application to transient elastodynamics in space-time domain

Article dans une revue avec comité de lecture
Author
BOUCINHA, Lucas
31214 Laboratoire de Mécanique des Contacts et des Structures [Villeurbanne] [LaMCoS]
AMMAR, Amine
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
GRAVOUIL, Anthony
56663 Institut Universitaire de France [IUF]
31214 Laboratoire de Mécanique des Contacts et des Structures [Villeurbanne] [LaMCoS]
NOUY, Anthony
10921 Institut de Recherche en Génie Civil et Mécanique [GeM]

URI
http://hdl.handle.net/10985/8456
DOI
10.1016/j.cma.2014.01.019
Date
2014
Journal
Computer Methods in Applied Mechanics and Engineering

Abstract

It is now well established that separated representations built with the help of proper generalized decomposition (PGD) can drastically reduce computational costs associated with solution of a wide variety of problems. However, it is still an open question to know if separated representations can be efficiently used to approximate solutions of hyperbolic evolution problems in space-time domain. In this paper, we numerically address this issue and concentrate on transient elastodynamic models. For such models, the operator associated with the space-time problem is non-symmetric and low-rank approximations are classically computed by minimizing the space-time residual in a natural L2 sense, yet leading to non optimal approximations in usual solution norms. Therefore, a new algorithm has been recently introduced by one of the authors and allows to find a quasi-optimal low-rank approximation a priori with respect to a target norm. We presently extend this new algorithm to multi-field models. The proposed algorithm is applied to elastodynamics formulated over space-time domain with the Time Discontinuous Galerkin method in displacement and velocity. Numerical examples demonstrate convergence of the proposed algorithm and comparisons are made with classical a posteriori and a priori approaches.

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