ABSTRACT
ABSTRACT: A very efficient methodology to carry out reliability-based optimization of linear systems with random structural parameters and random excitation is presented. The reliabilitybased optimization problem is formulated as the minimization of an objective function for a specified failure probability. 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 optimal design process. The approximations are combined with an efficient simulation technique to generate explicit approximations of reliability measures with respect to the design variables. In particular, an efficient importance sampling technique is used to estimate the failure probability. The effectiveness and feasibility of the suggested approach is demonstrated by an example problem. At the same time the effect of uncertainty in the system parameters on the performance and reliability of the final design is investigated.
