This paper discusses research into an alternative for characterizing the reliability of complex systems. The approach is unique in two respects: it is based o na determinstic sampling of the likelihood function and non pseudo-Monte Carlo sampling, and second, it uses a probabilistic membership function as opposed to the 'crisp' indicator function commonly used in importance sampling. In particular, the new procedure suggested in this paper also does not require identification of the limit state function or the MPP. Through the use of regionalized random variable,s the response of the system is modeled as a random field, which permits probabilistic membership statements for any feasible input vector relative to the failure domain. Preliminary results indicate that the proposed method is superior to traditional as well as stratified sampling methods.
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