一种新的矩独立重要性测度分析方法及高效算法

In order to analyze the effect of input random variables on the failure probability of structural systems more reasonably, a new moment-independent importance measure analysis method is proposed in this paper. The traditional importance measure index can only estimate the influence of input random variables on the output response of structural systems at fixed points, while the new index proposed in this paper can fully reflect the average influence of input random variables on the output response of structural systems when they change in all reduced intervals of their distribution areas, which is more in line with engineering practice. Seeking to find the new index, this paper presents two algorithms: the conventional double-loop-repeated-set Monte Carlo (DLRS MC) method and adaptive radial-based importance sampling (ARBIS) method. The results of DLRS MC method can be used as a reference solution, yet its calculation process is slow and strenuous. Under the condition of the precision of solving the new index is met, the calculation efficiency of ARBIS method is greatly improved. Finally, a numerical example and an engineering example are given to illustrate the significance of the new index and the efficiency of the proposed algorithm.