Sensitivity of Sample for Simulation-Based Reliability Analysis Methods

In structural reliability analysis, simulation methods are widely used. The statistical characteristics of failure probability estimate of these methods have been well investigated. In this study, the sensitivities of the failure probability estimate and its statistical characteristics with regard to sample, called 'contribution indexes', are proposed to measure the contribution of sample. The contribution indexes in four widely simulation methods, i.e., Monte Carlo simulation (MCS), importance sampling (IS), line sampling (LS) and subset simulation (SS) are derived and analyzed. The proposed contribution indexes of sample can provide valuable information understanding the methods deeply, and enlighten potential improvement of methods. It is found that the main differences between these investigated methods lie in the contribution indexes of the safety samples, which are the main factors to the efficiency of the methods. Moreover, numerical examples are used to validate these findings.

Automated summary

This study proposed contribution indexes to measure the sensitivity of failure probability estimate with regards to sample, and derived and analyzed them for four simulation methods. The main differences between these methods lie in the contribution indexes of the safety samples, which are key factors to the efficiency of the methods. Numerical examples were used to validate the findings.