Article (Scientific journals)
Identification of Bayesian posteriors for coefficients of chaos expansions
Arnst, Maarten; Ghanem, Roger; Soize, Christian
2010In Journal of Computational Physics, 229 (9), p. 3134-3154
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Keywords :
Stochastic inversion; Identification; Bayesian
Abstract :
[en] This article is concerned with the identification of probabilistic characterizations of random variables and fields from experimental data. The data used for the identification consist of measurements of several realizations of the uncertain quantities that must be characterized. The random variables and fields are approximated by a polynomial chaos expansion, and the coefficients of this expansion are viewed as unknown parameters to be identified. It is shown how the Bayesian paradigm can be applied to formulate and solve the inverse problem. The estimated polynomial chaos coefficients are hereby themselves characterized as random variables whose probability density function is the Bayesian posterior. This allows to quantify the impact of missing experimental information on the accuracy of the identified coefficients, as well as on subsequent predictions. An illustration in stochastic aeroelastic stability analysis is provided to demonstrate the proposed methodology.
Disciplines :
Mechanical engineering
Author, co-author :
Arnst, Maarten ;  University of Southern California > Department of Civil and Environmental Engineering
Ghanem, Roger;  University of Southern California > Department of Civil and Environmental Engineering
Soize, Christian;  Université Paris-Est > Laboratoire de Modélisation et Simulation Multi Echelle
Language :
English
Title :
Identification of Bayesian posteriors for coefficients of chaos expansions
Publication date :
01 May 2010
Journal title :
Journal of Computational Physics
ISSN :
0021-9991
eISSN :
1090-2716
Publisher :
Academic Press
Volume :
229
Issue :
9
Pages :
3134-3154
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 14 November 2011

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