Space-time proper generalized decompositions for the resolution of transient elastodynamic modelsReportar como inadecuado

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1 LaMCoS - Laboratoire de Mécanique des Contacts et des Structures Villeurbanne 2 IUF - Institut Universitaire de France 3 LAMPA-ECPS - Laboratoire Arts et Métiers ParisTech - Ecoulements Complexes Photonique et Surfaces

Abstract : In this paper, we investigate ability of proper generalized decomposition PGD to solve transient elastodynamic models in space-time domain. Classical methods use time integration schemes and an incremental resolution process. We propose here to use standard time integration methods in a non-incremental strategy. As a result, PGD gives a separated representation of the space-time solution as a sum of tensorial products of space and time vectors, that we interpret as space-time modes. Recent time integration schemes are based on multi-field formulations. In this case, separated representation can be constructed using state vectors in space and same vectors in time. However, we have experienced bad convergence order using this decomposition. Furthermore, temporal approximation must be the same for all fields. Thus, we propose an extension of classical separated representation for multi-field problems. This multi-field PGD MF-PGD uses space and time vectors that are different for each field. Calculation of decomposition is done using a monolithic approach in space and time, potentially allowing the use of different approximations in space and time. Finally, several simulations are performed with the transient elastodynamic problem with one dimension in space. Different approximations in time are investigated: Newmark scheme, single field time discontinuous Galerkin method and two fields time continuous and discontinuous Galerkin methods.

Keywords : Model reduction Elastodynamic Singular value decomposition SVD Proper generalized decomposition PGD Multi-field proper generalized decomposition MF-PGD Tensorial formalism

Autor: Lucas Boucinha - Anthony Gravouil - Amine Ammar -



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