Inscrição na biblioteca: Guest
Portal Digital Begell Biblioteca digital da Begell eBooks Diários Referências e Anais Coleções de pesquisa
International Journal for Multiscale Computational Engineering
Fator do impacto: 1.016 FI de cinco anos: 1.194 SJR: 0.554 SNIP: 0.68 CiteScore™: 1.18

ISSN Imprimir: 1543-1649
ISSN On-line: 1940-4352

International Journal for Multiscale Computational Engineering

DOI: 10.1615/IntJMultCompEng.v1.i4.50
14 pages

A Multi-Time-Scale Strategy for Multiphysics Problems: Application to Poroelasticity

David Dureisseix
Laboratoire de Mécanique et Génie Civil (LMGC), Laboratoire de Micromécanique et d'lntégrité des Structures (MIST), IRSN DPAM, CNRS UMR 5508, University Montpellier 2, F-34095 Montpellier CEDEX 5, France
Pierre Ladeveze
Laboratoire de Mecanique et Technologie ENS de Cachan C.N.R.S., University Paris VI 61 Av. du President Wilson 94235 Cachan Cedex, France
David Neron
LMT-Cachan (ENS Cachan / CNRS / University Paris 6), 61, avenue du President Wilson, F-94235 Cachan CEDEX, France
Bernhard Schrefler
Department of Ingegneria Civile, Edile e Strutturale e Trasporti University of Padua, Via Marzolo 9, 35131 Padua, Italy

RESUMO

Usually, multiphysics phenomena and coupled-field problems lead to computationally intensive structural analysis. Strategies to keep these problems computationally affordable are of special interest. For coupled fluid-structure problems, for instance, partitioned procedures and staggered algorithms are often preferable to direct analysis.
In a previous article, a new strategy derived from the LArge Time INcrement (LATIN) method was described. This strategy was applied to the consolidation of saturated porous soils, which is a highly coupled fluid-solid problem. The feasibility of the method and the comparison of its performance with that of a standard partitioning scheme (the so-called ISPP method) was presented.
Here, we go one step further and use the LATIN method to take into account the different time scales that usually arise from the different physics. We propose a multi-time-scale strategy, which improves the existing method.