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STOCHASTIC REPRESENTATIONS AND STATISTICAL INVERSE IDENTIFICATION FOR UNCERTAINTY QUANTIFICATION IN COMPUTATIONAL MECHANICS

Christian Soize · Christophe Desceliers · Johann Guilleminot · Tien-Thinh Le · Guillaume Perrin · Jean‐Marc Allain +3 more

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Probabilistic and Robust Engineering Design Control Systems and Identification Model Reduction and Neural Networks

Abstract

STOCHASTIC REPRESENTATIONS AND STATISTICAL INVERSE IDENTIFICATION FOR UNCERTAINTY QUANTIFICATION IN COMPUTATIONAL MECHANICS - 1st International Conference on Uncertainty Quantification in Computational Sciences and Engineering - 25 - 27 May 2015 Crete Island, Greece

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References

1991Stochastic Finite Elements: A Spectral Approach 2008Uncertainty Quantification and Polynomial Chaos Techniques in Computational Fluid Dynamics 2010Spectral methods for uncertainty quantification : with applications to computational fluid dynamics 2006Multi-Element Generalized Polynomial Chaos for Arbitrary Probability Measures 2004Numerical Challenges in the Use of Polynomial Chaos Representations for Stochastic Processes 2004Uncertainty propagation using Wiener–Haar expansions 2011On the convergence of generalized polynomial chaos expansions 1996Numerical solution of spectral stochastic finite element systems

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