A double Kriging model method based on optimization sample points for importance measure analysis

For the engineering problems involving implicit limit state functions, a double Kriging model method based on optimization sample points for importance measure analysis is discussed in this paper. Firstly, in this method, a small amount of initial sample points are employed to build the Kriging surrogate model which relates the basic variables to the response. Then the subsequent points with relatively high uncertainty can be added to the sample points with global optimization method. Finally, the Kriging surrogate model can give fairly good accuracy with a minimum number of sample points. The relationship between the basic variables and the response function and that between the basic variables and the conditional probability of failure are substituted by Kriging models; so the computation cost of the importance measure is reduced largely. To illustrate the engineering applicability and feasibility of the method, numerical and engineering examples are provided and discussed.