Enhanced goal‐oriented error assessment and computational strategies in adaptive reduced basis solver for stochastic problems |
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Authors: | Kevin Serafin Benoît Magnain Eric Florentin Núria Parés Pedro Díez |
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Affiliation: | 1. INSA‐CVL / Université d'Orléans ‐ PRISME, Bourges, France;2. Laboratori de Càlcul Numèric (LaCàN) ‐ Universitat Politècnica de Catalunya, Barcelona, Spain |
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Abstract: | This work focuses on providing accurate low‐cost approximations of stochastic finite elements simulations in the framework of linear elasticity. In a previous work, an adaptive strategy was introduced as an improved Monte‐Carlo method for multi‐dimensional large stochastic problems. We provide here a complete analysis of the method including a new enhanced goal‐oriented error estimator and estimates of CPU (computational processing unit) cost gain. Technical insights of these two topics are presented in details, and numerical examples show the interest of these new developments. Copyright © 2016 John Wiley & Sons, Ltd. |
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Keywords: | reduced basis adaptivity stochastic modeling goal‐oriented error assessment. |
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