An efficient reliability-based optimization scheme for uncertain linear systems subject to general Gaussian excitation

H. A. Jensen, M. A. Valdebenito, G. I. Schuëller

Resultado de la investigación: Contribución a una revistaArtículorevisión exhaustiva

57 Citas (Scopus)

Resumen

A very efficient methodology to carry out reliability-based optimization of linear systems with random structural parameters and random excitation is presented. The reliability-based optimization problem is formulated as the minimization of an objective function for a specified reliability. The probability that design conditions are satisfied within a given time interval is used as a measure of the system reliability. Approximation concepts are used to construct high quality approximations of dynamic responses in terms of the design variables and uncertain structural parameters during the design process. The approximations are combined with an efficient simulation technique to generate explicit approximations of the reliability measures with respect to the design variables. In particular, an efficient importance sampling technique is used to estimate the failure probabilities. The number of dynamic analyses as well as reliability estimations required during the optimization process are reduced dramatically. Several example problems are presented to illustrate the effectiveness and feasibility of the suggested approach.

Idioma originalInglés
Páginas (desde-hasta)72-87
Número de páginas16
PublicaciónComputer Methods in Applied Mechanics and Engineering
Volumen198
N.º1
DOI
EstadoPublicada - 15 nov. 2008

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