Abstract
An accurate and efficient Monte Carlo simulation method is presented for limit-state-based reliability analysis at both component and system levels, using a response surface approximation of the failure indicator function. The cross-validated moving least squares method is used to construct the response surface of the indicator function, based on an optimum symmetric Latin hypercube sampling technique. The proposed method can handle problems with complicated limit state(s). Also, it can easily handle implicit, highly nonlinear limit-state functions, with variables of any statistical distributions and correlations. The method appears to be particularly efficient for multiple limit state and multiple design point problems. Three structural reliability examples are used to highlight its superior accuracy and efficiency over traditional reliability methods.
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