Simultaneous empirical interpolation and reduced basis method. Application to non-linear multi-physics problem

Abstract : This paper focuses on the reduced basis method in the case of non-linear and non-affinely parametrized partial differential equations where affine decomposition is not obtained. In this context, Empirical Interpolation Method (EIM) is commonly used to recover the affine decomposition necessary to deploy the Reduced Basis (RB) methodology. The build of each EIM approximation requires many finite element solves which increases significantly the computational cost hence making it inefficient on large problems. We propose a Simultaneous EIM and RB method (SER) whose principle is based on the use of reduced basis approximations into the EIM building step. The number of finite element solves required by SER can drop to N + 1 where N is the dimension of the RB approximation space, thus providing a huge computational gain. The SER method has already been introduced and illustrated on a 2D benchmark. This paper develops the SER method with some variants and in particular a multilevel SER, SER(l) which improves significantly SER at the cost of lN + 1 finite element solves. Finally we discuss these extensions on a 3D multi-physics problem.
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Chapitre d'ouvrage
Model Reduction of Parametrized Systems, Springer International Publishing, 2017, MS&A, 978-3-319-58786-8. 〈10.1007/978-3-319-58786-8〉
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Contributeur : Cécile Daversin <>
Soumis le : mercredi 15 juin 2016 - 18:05:26
Dernière modification le : mercredi 14 mars 2018 - 16:51:14

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Cécile Daversin, Christophe Prud'Homme. Simultaneous empirical interpolation and reduced basis method. Application to non-linear multi-physics problem. Model Reduction of Parametrized Systems, Springer International Publishing, 2017, MS&A, 978-3-319-58786-8. 〈10.1007/978-3-319-58786-8〉. 〈hal-01332437〉

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