Identification of Bayesian posteriors for coefficients of chaos expansions - Archive ouverte HAL Access content directly
Journal Articles Journal of Computational Physics Year : 2010

Identification of Bayesian posteriors for coefficients of chaos expansions

Abstract

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.
Fichier principal
Vignette du fichier
publi-2010-JCP-229_9_3134-3154-arnst-ghanem-soize-preprint.pdf (325.22 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00684317 , version 1 (01-04-2012)

Identifiers

Cite

M. Arnst, R. Ghanem, Christian Soize. Identification of Bayesian posteriors for coefficients of chaos expansions. Journal of Computational Physics, 2010, 229 (9), pp.3134-3154. ⟨10.1016/j.jcp.2009.12.033⟩. ⟨hal-00684317⟩
107 View
468 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More