probability failure

epistemic uncertainty

Reliability Engineering & System Safety

The moment-independent importance measure proposed by Borgonovo, which is defined as the average shift between the unconditional and conditional probability density functions (PDFs) of model output, is widely used to evaluate the influence of input uncertainty on the entire output distribution. And how to exactly and efficiently estimate the PDFs remains a crucial and challenging problem. In this paper, a novel PDF estimation based method is proposed to efficiently evaluate the moment-independent index. Firstly, the PDF of the model output is obtained based on the concepts of maximum entropy, fractional moment and high dimensional model representation. Secondly, the Nataf transformation is utilized to estimate the joint PDF of the output and input variable. Finally, the index can be easily computed using the generated correlated standard normal samples. Thus the importance measure can be calculated with high efficiency and accuracy using this proposed composited method. Several examples are employed to demonstrate the advantages of the proposed method. Meanwhile, the importance analysis of a stiffening rib of the wing leading edge in a certain aircraft also verifies its good engineering applicability.

A new method for evaluating Borgonovo moment-independent importance measure with its application in an aircraft structure