Abstract
An approach is developed to locally estimate the failure probability of a system under various design values by using simple Monte Carlo simulation. Although it seems to require numerous reliability analysis runs to locally estimate the failure probability function, which is a function of the design variables, the approach only requires simple Monte Carlo simulations. It is also possible to find the confidence interval of the failure probability function as well as estimate the gradient of the logarithm of that function with respect to the design variables. The use of the new approach is demonstrated with two simulated examples. The results show that the new approach can effectively locally estimate the entire failure probability function and the confidence interval. The approach should be valuable for reliability-based design and reliability sensitivity analysis.
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