Abstract : We propose a new method to approximate stochastic solutions of uncertain PDEs using Polynomial Chaos expansions of their level sets. The method is non-intrusive and targets solutions with steep gradients with random locations. An adaptive choice of the level set is used to control the approximation error, ensuring high accuracy at a significantly lower cost compared to classical non-intrusive projection approach. We apply and validate the method on subsurface flows exhibiting steep fronts.
Type de document :
Communication dans un congrès
SIAM conference on Uncertainty quantification, Apr 2016, Lausanne, Switzerland. 2016
https://hal-brgm.archives-ouvertes.fr/hal-01266242
Contributeur : Pierre Sochala
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Soumis le : mardi 2 février 2016 - 12:37:28
Dernière modification le : mardi 20 novembre 2018 - 14:04:02
Pierre Sochala, Olivier Le Maitre. Level set Methods for Polynomial Chaos expansion of stochastic PDEs outputs. SIAM conference on Uncertainty quantification, Apr 2016, Lausanne, Switzerland. 2016. 〈hal-01266242〉
