[en] This paper addresses the inversion of probabilistic models for the dynamical behaviour of structures using experimental data sets of measured frequency-domain transfer functions. The inversion is formulated as the minimization, with respect to the unknown parameters to be identified, of an objective function that measures a distance between the data and the model. Two such distances are proposed, based on either the loglikelihood function, or the relative entropy. As a comprehensive example, a probabilistic model for the dynamical behaviour of a slender beam is inverted using simulated data. The methodology is then applied to a civil and environmental engineering case history involving the identification of a probabilistic model for ground-borne vibrations from real experimental data.
Disciplines :
Mechanical engineering
Author, co-author :
Arnst, Maarten ; Ecole Centrale Paris > Laboratoire des Sols, Structures et Matériaux
Clouteau, Didier; Ecole Centrale Paris > Laboratoire des Sols, Structures et Matériaux
Bonnet, Marc; Ecole Polytechnique (France) > Laboratoire de Mécanique des Solides
Language :
English
Title :
Inversion of probabilistic structural models using measured transfer functions
Publication date :
January 2008
Journal title :
Computer Methods in Applied Mechanics and Engineering
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