期刊
RELIABILITY ENGINEERING & SYSTEM SAFETY
卷 147, 期 -, 页码 123-131出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.ress.2015.11.006
关键词
Sensitivity analysis; Multivariate output; Multivariate probability integral transformation; Cumulative distribution function
资金
- National Natural Science Foundation of China [NSFC 51505382]
- Fundamental Research Funds for the Central Universities [3102015ZY004]
Mathematical and computational models with correlated multivariate output are commonly used for risk assessment and decision support in engineering. Traditional methods for sensitivity analysis of the model with scalar output fail to provide satisfactory results for this multivariate case. In this work, we introduce a new sensitivity index which looks at the influence of input uncertainty on the entire distribution of the multivariate output without reference to a specific moment of the output. The definition of the new index is based on the multivariate probability integral transformation (PIT), which can take into account both of the uncertainties and the correlations among multivariate output. The mathematical properties of the proposed sensitivity index are discussed and its differences with the sensitivity indices previously introduced in the literature are highlighted. Two numerical examples and a rotating shaft model of an aircraft wing are employed to illustrate the validity and potential benefits of the new sensitivity index. (C) 2015 Elsevier Ltd. All rights reserved.
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