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) (Barrault et al. C R Acad Sci Paris Ser I 339(9):667–672, 2004) 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 (Daversin et al. ESAIM proceedings, EDP Sciences, Paris, vol. 43, pp. 225–254, 2013). 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 in Daversin and Prud’homme (C R Acad Sci Paris Ser I 353:1105–1109, 2015) through which it is illustrated on a 2D benchmark itself introduced in Grepl et al. (Modél Math Anal Numér 41(03):575–605, 2007). 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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References
Barrault, M., Maday, Y., Nguyen, N.C., Patera, A.T.: An empirical interpolation method: application to efficient reduced-basis discretization of partial differential equations. C.R. Acad. Sci. Paris Ser. I 339(9), 667–672 (2004)
Daversin, C., Prud’homme, C.: Simultaneous empirical interpolation and reduced basis method for non-linear problems. C.R. Acad. Sci. Paris Ser. I 353, 1105–1109 (2015)
Daversin, C., Veys, S., Trophime, C., Prud’homme, C.: A reduced basis framework: application to large scale non-linear multi-physics problems. In: ESAIM Proceedings, vol. 43, pp. 225–254. EDP Science, Paris (2013)
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Grepl, M.A., Maday Y., Nguyen, N.C. Patera, A.T.: Efficient reduced-basis treatment of nonaffine and nonlinear partial differential equations. Modél. Math. Anal. Numér. 41(03), 575–605 (2007)
Veroy, K., Prud’homme, C., Rovas, D.V, Patera, A.T.: A Posteriori Error Bounds for Reduced-Basis Approximation of Parametrized Noncoercive and Nonlinear Elliptic Partial Differential Equations. American Institute of Aeronautics and Astronautics Paper, 2003–3847 (2003)
Acknowledgements
The authors would like to thank A.T. Patera (MIT) for the fruitful discussions we had as well as Vincent Chabannes (U. Strasbourg) and Christophe Trophime (CNRS). The authors acknowledge also the financial support of the ANR Chorus and the Labex IRMIA, and would like to thank PRACE for awarding us access to resource Curie based in France at CCRT as well as GENCI for awarding us access to resource Occigen based in France at Cines.
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Daversin, C., Prud’homme, C. (2017). Simultaneous Empirical Interpolation and Reduced Basis Method: Application to Non-linear Multi-Physics Problem. In: Benner, P., Ohlberger, M., Patera, A., Rozza, G., Urban, K. (eds) Model Reduction of Parametrized Systems. MS&A, vol 17. Springer, Cham. https://doi.org/10.1007/978-3-319-58786-8_2
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DOI: https://doi.org/10.1007/978-3-319-58786-8_2
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