Regional sensitivity analysis of aleatory and epistemic uncertainties on failure probability

• Proposing a regional sensitivity analysis (RSA) of aleatory and epistemic variables.
• The new RSA can identify regional contribution of inputs to failure probability.
• The properties of the proposed RSA are analyzed and proved.
• The high-efficient kriging-based solution for the proposed RSA is established.

To analyze the effects of specific regions of the aleatory and epistemic uncertain variables on the failure probability, a regional sensitivity analysis (RSA) technique called contribution to failure probability (CFP) plot is developed in this paper. This RSA technique can detect the important aleatory and epistemic uncertain variables, and also measure the contribution of specific regions of these important input variables to failure probability. When computing the proposed CFP, the aleatory and epistemic uncertain variables are modeled by random and interval variables, respectively. Then based on the hybrid probabilistic and interval model (HPIM) and the basic probability assignments in evidence theory, the failure probability of the structure with aleatory and epistemic uncertainties can be obtained through a successive construction of the second-level limit state function and the corresponding reliability analysis. Kriging method is used to establish the surrogate model of the second-level limit state function to improve the computational efficiency. Two practical examples are employed to test the effectiveness of the proposed RSA technique, and the efficiency and accuracy of the established kriging-based solution.