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hal-00701601, version 1

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

C. Soize (, http://msme.univ-mlv.fr/staff/meca/soize-christian/) 1

(Keynote Lecture) 1st International Symposium on Uncertainty Quantification and Stochastic Modeling (Uncertainties 2012) (2012)

Résumé : 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.

  • 1 :  Laboratoire de Modélisation et Simulation Multi Echelle (MSME)
  • Université Paris-Est Marne-la-Vallée (UPEMLV) – Université Paris-Est Créteil Val-de-Marne (UPEC) – CNRS : UMR8208
  • Domaine : Sciences de l'ingénieur/Mécanique
    Mathématiques/Probabilités
    Mathématiques/Statistiques
    Statistiques/Théorie
  • Commentaire : Keynote Lecture
 
  • hal-00701601, version 1
  • http://hal-upec-upem.archives-ouvertes.fr/hal-00701601
  • oai:hal-upec-upem.archives-ouvertes.fr:hal-00701601
  • Contributeur : Christian Soize <>
  • Soumis le : Vendredi 25 Mai 2012, 16:36:21
  • Dernière modification le : Mercredi 19 Décembre 2012, 21:36:24