Contribution to sample failure probability plot and its solution by Kriging method

Abstract

To analyze the effect of the region of the model inputs on the model output, a novel concept about contribution to the sample failure probability plot(CSFP) is proposed based on the contribution to the sample mean plot(CSM) and the contribution to the sample variance plot(CSV). The CSFP can be used to analyze the effect of the region of the model inputs on the failure probability. After the definition of CSFP, its property and the differences between CSFP and CSV/CSM are discussed. The proposed CSFP can not only provide the information about which input affects the failure probability mostly, but also identify the contribution of the regions of the input to the failure probability mostly. By employing the Kriging model method on optimized sample points, a solution for CSFP is obtained. The computational cost for solving CSFP is greatly decreased because of the efficiency of Kriging surrogate model. Some examples are used to illustrate the validity of the proposed CSFP and the applicability and feasibility of the Kriging surrogate method based solution for CSFP.