Skip to Main content Skip to Navigation
Conference papers

Advanced methodologies for the identification of stochastic models in computational mechanics. Case of uncertainty quantification for dynamical systems and case of mesoscale elasticity random fields for heterogeneous microstructures

Abstract : The main concepts, the formulations and some advances are presented for the stochastic modeling and the identification of uncertainties and of random fields in computational mechanics. Then the identification of the generalized probabilistic approach of uncertainties in computational structural dynamics is introduced. The prior stochastic models of both uncertain model-system parameters and modeling errors, are introduced. The posterior stochastic model of the uncertain model-system parameters, in presence of the modeling errors, are carried out using the Bayes method and the experimental observations. Finally, an adavanced methodology for the experimenal identification of stochastic models for materials elasticity property is presented.
Complete list of metadatas

https://hal-upec-upem.archives-ouvertes.fr/hal-00701601
Contributor : Christian Soize <>
Submitted on : Friday, May 25, 2012 - 4:36:21 PM
Last modification on : Thursday, March 19, 2020 - 11:52:02 AM

Identifiers

  • HAL Id : hal-00701601, version 1

Collections

Citation

Christian Soize. Advanced methodologies for the identification of stochastic models in computational mechanics. Case of uncertainty quantification for dynamical systems and case of mesoscale elasticity random fields for heterogeneous microstructures. (Keynote Lecture) 1st International Symposium on Uncertainty Quantification and Stochastic Modeling (Uncertainties 2012), Feb 2012, Maresias, SP, Brazil. ⟨hal-00701601⟩

Share

Metrics

Record views

303