Hybrid reliability analysis with uncertain statistical variables, sparse variables and interval variables

被引:26
|
作者
Peng, Xiang [1 ,2 ]
Wu, Tianji [1 ]
Li, Jiquan [1 ]
Jiang, Shaofei [1 ]
Qiu, Chan [2 ]
Yi, Bing [3 ]
机构
[1] Zhejiang Univ Technol, Key Lab E&M, Hangzhou, Zhejiang, Peoples R China
[2] Zhejiang Univ, State Key Lab CAD&CG, Hangzhou, Zhejiang, Peoples R China
[3] Cent S Univ, Sch Traff & Transportat Engn, Changsha, Hunan, Peoples R China
基金
中国国家自然科学基金;
关键词
Hybrid reliability analysis; sparse variables; interval variables; reliability index; MONTE-CARLO-SIMULATION; FIN HEAT-EXCHANGER; DESIGN OPTIMIZATION; ALGORITHM; INFORMATION; PARAMETERS;
D O I
10.1080/0305215X.2017.1400025
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
There are differences among sampling data and representation types of uncertain statistical variables, sparse variables and interval variables, which increase the complexity of structure reliability analysis. Therefore, a hybrid first order reliability analysis method considering the three types of uncertain variables is demonstrated in this article. First, distribution types and distribution parameters of sparse variables are identified and probabilistically estimated. Secondly, interval variables are transformed into probabilistic types using a uniformity approach. Thirdly, a unified hybrid reliability calculation method considering these uncertain variables simultaneously is demonstrated. The most probable point (MPP) is searched for using the first order reliability method, and then a linear approximation function of performance function is constructed in the neighbourhood of the MPP. Finally, the belief and plausibility measures of the reliability index are efficiently calculated using the theoretical analytical method. Three examples are investigated to demonstrate the effectiveness of the proposed method.
引用
收藏
页码:1347 / 1363
页数:17
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