Abstract
This paper is concerned with a reliability assessment of structural systems based on an improved importance sampling simulation, in which the importance sampling density is determined within the limit of the failure region. Basic random variables are assumed to be stochastically independent normal variates and the minimum reliability index β of the system to be known beforehand. The first step of the proposed method is to execute simulations, refered to the preliminary simulations, to get a rough estimate of the failure probability and data about the sample distribution. These data are utilized to determine the importance sampling density as a frequency distribution with respect to radius in polar coordinates. In the second step, the structural failure probabilities are estimated through the importance sampling simulations, samples of which are generated from the estimator of the importance sampling density determined in the first step.The proposed method is compared in a numerical example with the Monte Carlo simulation combined with partition of the region technique and ISPUD for multi mode failure etc. It can be said that the proposed method is effective for the estimation of structural failure probabilities.
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