An empirical interpolation method: application to efficient reduced-basis discretization of partial differential equations

Abstract

We present an efficient reduced-basis discretization procedure for partial differential equations with nonaffine parameter dependence. The method replaces nonaffine coefficient functions with a collateral reduced-basis expansion which then permits an (effectively affine) offline?online computational decomposition. The essential components of the approach are (i) a good collateral reduced-basis approximation space, (ii) a stable and inexpensive interpolation procedure, and (iii) an effective a posteriori estimator to quantify the newly introduced errors. Theoretical and numerical results respectively anticipate and confirm the good behavior of the technique.

Publication
Comptes Rendus Mathematique
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Ngoc Cuong Nguyen
Ngoc Cuong Nguyen
Principal Research Scientist

My research interests include computational mechanics, molecular mechanics, nanophotonics, scientific computing, and machine learning.