Random matrix models and nonparametric method for uncertainty quantification

Abstract : This paper deals with the fundamental mathematical tools and the associated computational aspects for constructing the stochastic models of random matrices that appear in the nonparametric method of uncertainties and in the random consti-tutive equations for multiscale stochastic modeling of heterogeneous materials. The explicit construction of ensembles of random matrices, but also the presentation of numerical tools for constructing general ensembles of random matrices are presented and can be used for high stochastic dimension. The developments presented are illustrated for the nonparametric method for multiscale stochastic mod-eling of heterogeneous linear elastic materials and for the nonparametric stochas-tic models of uncertainties in computational structural dynamics.
Complete list of metadatas

Cited literature [128 references]  Display  Hide  Download

https://hal-upec-upem.archives-ouvertes.fr/hal-01284669
Contributor : Christian Soize <>
Submitted on : Monday, March 7, 2016 - 8:27:24 PM
Last modification on : Friday, October 4, 2019 - 1:31:52 AM
Long-term archiving on : Sunday, November 13, 2016 - 9:51:31 AM

File

publi-2016-HUQ-chapt2-soize-pr...
Files produced by the author(s)

Identifiers

Collections

Citation

Christian Soize. Random matrix models and nonparametric method for uncertainty quantification. R. Ghanem, D. Higdon, and H. Owhadi. Handbook for Uncertainty Quantification, 1, Springer International Publishing Switzerland, pp.219-287, 2017, 978-3-319-12384-4. ⟨10.1007/978-3-319-11259-6\_5-1⟩. ⟨hal-01284669⟩

Share

Metrics

Record views

343

Files downloads

881