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Reduced Basis Techniques for Stochastic Problems

  • École des ponts
  • INRIA Institut National de Recherche en Informatique et en Automatique
  • UPMC Université de Paris VI
  • Women and Infants Hospital of Rhode Island-Warren Alpert Medical School of Brown University
  • Massachusetts Institute of Technology

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

107 Citations (Scopus)

Résumé

We report here on the recent application of a now classical general reduction technique, the Reduced-Basis (RB) approach initiated by C. Prud'homme et al. in J. Fluids Eng. 124(1), 70-80, 2002, to the specific context of differential equations with random coefficients. After an elementary presentation of the approach, we review two contributions of the authors: in Comput. Methods Appl. Mech. Eng. 198(41-44), 3187-3206, 2009, which presents the application of the RB approach for the discretization of a simple second order elliptic equation supplied with a random boundary condition, and in Commun. Math. Sci., 2009, which uses a RB type approach to reduce the variance in the Monte-Carlo simulation of a stochastic differential equation. We conclude the review with some general comments and also discuss possible tracks for further research in the direction.

langue originaleAnglais
Pages (de - à)435-454
Nombre de pages20
journalArchives of Computational Methods in Engineering
Volume17
Numéro de publication4
Les DOIs
étatPublié - 1 janv. 2010

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