adapted design of experiments for dimension decomposition-based meta-model in structural reliability analysis

Reliability analysis of structures is often problematic for the structures with nonlinear and complex limit state functions (lsf). for these cases, simulation methods often provide accurate failure probability, but with high number of structure’s lsf analysis. this paper presents an efficient combination of monte carlo simulation (mcs) method and univariate dimension reduction (udr) based meta-model to approximate the failure probability of structures with few lsfs evaluation. for this purpose, the design of experiment used in the meta model is adapted such that the expected failure samples in mcs being approximated with higher accuracy. several numerical and engineering reliability problems are solved by the proposed approach and the results are verified by mcs. results show that the proposed approach highly reduces the required number of structural analysis to provide proper results.