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Journal of Scientific Computing

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13-11-2015

Goal-Oriented Error Estimation for the Reduced Basis Method, with Application to Sensitivity Analysis

Authors: Alexandre Janon, Maëlle Nodet, Clémentine Prieur

Published in: Journal of Scientific Computing | Issue 1/2016

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Abstract

The reduced basis method is a powerful model reduction technique designed to speed up the computation of multiple numerical solutions of parametrized partial differential equations. We consider a quantity of interest, which is a linear functional of the PDE solution. A new probabilistic error bound for the reduced model is proposed. It is efficiently and explicitly computable, and we show on different examples that this error bound is sharper than existing ones. We include application of our work to sensitivity analysis studies.

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Title: Goal-Oriented Error Estimation for the Reduced Basis Method, with Application to Sensitivity Analysis
Authors: Alexandre Janon
Maëlle Nodet
Clémentine Prieur
Publication date: 13-11-2015
Publisher: Springer US
Published in: Journal of Scientific Computing / Issue 1/2016
Print ISSN: 0885-7474
Electronic ISSN: 1573-7691
DOI: https://doi.org/10.1007/s10915-015-0127-z

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