A Kriging surrogate model method for moment-independent importance analysis

Structural importance analysis is one of the research focuses on the fields of structural uncertainty analysis. As a kind of moment-independent importance measure index, the failure probability-based importance measure attracts attention of the researchers for the reason of that it can be used to effectively reflect the influence of the input uncertainties on the failure probability. However, compared with other kinds of importance measure indices, there are still some difficulties to accurately and efficiently estimate the failure probability-based moment-independent importance measure. In this context, a highly efficient method for moment-independent importance analysis is proposed. The proposed method firstly constructs a Kriging surrogate model with a slight number of experimental design samples to fully approximate the actual input-output response function. Then, the numerical simulation strategy is adopted to carry out the importance measure analysis of the constructed Kriging model. Finally, the main effect and total effect indices of the failure probability-based importance measure for each input variables can be obtained, the effect ranking order of each input variables on the failure probability can be provided as well. Compared with the existing methods, because of the introduction of Kriging surrogate model, the calculating times of the actual response function are greatly decreased and the computing accuracy is guaranteed as well. The application results of two engineering examples illustrate the superiorities of the proposed method in the aspect of calculating efficiency and accuracy, and indicate its excellent applicability.