A new uncertainty propagation method for problems with parameterized probability-boxes

被引：49

作者：

Liu, H. B. ^{[1
]}

Jiang, C. ^{[1
]}

Jia, X. Y. ^{[1
]}

Long, X. Y. ^{[1
]}

Zhang, Z. ^{[1
]}

Guan, F. J. ^{[2
]}

机构：

[1] Hunan Univ, Coll Mech & Vehicle Engn, State Key Lab Adv Design & Mfg Vehicle Body, Changsha 410082, Hunan, Peoples R China

[2] Natl Univ Def Technol, Sci & Technol Integrated Logist Support Lab, Changsha 410082, Hunan, Peoples R China

来源：

RELIABILITY ENGINEERING & SYSTEM SAFETY | 2018年 / 172卷

基金：

中国国家自然科学基金;

关键词：

Parameterized p-boxes; Uncertainty propagation; Dimension reduction method; Probability bounds; Johnson distribution; DIMENSION-REDUCTION METHOD; MULTIDIMENSIONAL INTEGRATION; IMPRECISE PROBABILITIES; POLYNOMIAL CHAOS; REPRESENTATION;

D O I：

10.1016/j.ress.2017.12.004

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This paper proposes a new uncertainty propagation method for problems with parameterized probability-boxes (p-boxes), which could efficiently compute the probability bounds of system response function. In practical engineering, these probability bounds are often very important for reliability analysis or risk assessment of a structure or system. First, based on the univariate dimension reduction method (UDRM), an optimized UDRM (OUDRM) is presented to calculate the bounds on statistical moments of response function. Then, utilizing the bounds on moments, a family of Johnson distributions fitting to the distribution function of response can be acquired using the moment matching method. Finally, by using an optimization approach based on percentiles, the probability bounds of the response function can be successfully obtained. Four numerical examples are investigated to demonstrate the effectiveness of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：64 / 73

页数：10

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