Reliability-oriented global sensitivity analysis using subset simulation and space partition.

• The inherent information in conditional samples in Subset Simulation is leveraged. • The reasoning of the first order indices is extended to the higher order. • Partition scheme is optimized considering coefficient of variation of the indices. This paper presents a novel reliability-oriented global sensitivity analysis method using the Subset Simulation (SS) method and the Space Partition (SP) scheme. It can exploit the inherent information of uncertainty within all the conditional samples in each simulation level of SS along the spirit of the SP scheme. The reasoning of the first order indices is firstly provided, followed by a heuristic study on the influence of parametric settings upon the statistical properties of the indices. By extending the calculation process to the higher order indices and formally optimizing the partition scheme considering the coefficient of variation of all the indices, the framework of the proposed reliability-oriented global sensitivity for arbitrary order of indices can be formed. The performance of the direct Monte Carlo method, the Quasi-Monte Carlo method, SP and the proposed method is compared through three numerical examples and two engineering applications, to demonstrate the merits of the proposed one. [ABSTRACT FROM AUTHOR]