Skip to Main content Skip to Navigation
Journal articles

Bayesian posteriors of uncertainty quantification in computational structural dynamics for low- and medium-frequency ranges

Abstract : The paper is devoted to the modeling and identification of uncertainties in computational structural dynamics for low- and medium-frequency ranges. A complete methodology is presented for the identification procedure. The first eigenfrequencies are used to quantify the uncertainties in the low-frequency band while the frequency response functions are used to quantify the uncertainties in the medium-frequency band. The system-parameter uncertainties are taken into account with the parametric probabilistic approach. The model uncertainties are taken in to account with the nonparametric probabilistic approach. The posterior stochastic model of systemparameter uncertainties is identified using the Bayes method.
Complete list of metadatas

Cited literature [85 references]  Display  Hide  Download

https://hal-upec-upem.archives-ouvertes.fr/hal-00806363
Contributor : Christian Soize <>
Submitted on : Saturday, March 30, 2013 - 9:01:56 AM
Last modification on : Thursday, March 19, 2020 - 11:52:02 AM
Long-term archiving on: : Sunday, April 2, 2017 - 10:57:40 PM

File

publi-2013-C_S-soize-preprint....
Files produced by the author(s)

Identifiers

Collections

Citation

Christian Soize. Bayesian posteriors of uncertainty quantification in computational structural dynamics for low- and medium-frequency ranges. Computers and Structures, Elsevier, 2013, 126 (-), pp.41-55. ⟨10.1016/j.compstruc.2013.03.020⟩. ⟨hal-00806363⟩

Share

Metrics

Record views

534

Files downloads

1030