General most probable point based approach for reliability index computation
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- Category: Geotechnical and mining mechanical engineering, machine building
- Last Updated on 22 June 2016
- Published on 22 June 2016
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Authors:
Xiongming Lai, Huaqiao University, Xiamen, China
Jianhang Su, Huaqiao University, Xiamen, China
Cheng Wang, Huaqiao University, Xiamen, China, Xi’an Jiaotong University, Xi’an, China
Yong Zhang, Huaqiao University, Xiamen, China
He Huang, Huaqiao University, Xiamen, China
Abstract:
Purpose. As for the reliability analysis of complex engineer problems, the nonlinearity and implicitness of the limit state functions always stand in the way. On one hand, the nonlinearity influences the convergence computation of some reliability problems when using most methods of reliability analysis. On the other hand, the implicitness means that information of the partial derivatives of the limit state function is impossible to obtain, which is necessary for most of the reliability methods. In order to overcome these difficulties, the paper presents a new general most probable point based (MPP-based) approach for computing the reliability.
Methodology. Within the framework of the proposed iterative algorithm, we presented new strategies for searching three types of the approximate MPPs by merely using the input and output information of the limit state function. In addition, the found MPPs can be used for updating the constructed response surface of the limit state function, which in its turn helps to find a more accurate MPP.
Findings. As illustrated by the examples, the proposed method provides excellent precision and convergence for the calculation results.
Originality. Three types of the approximate MPPs are firstly presented for updating the constructed response surface of the limit state function, whose input and output information is sufficient.
Practical value. The proposed method does not necessitate any requirements for the detailed format and complexity of the limit state functions, which is an advantage. Hence, it is especially applicable to the implicit case of complex engineer problems.
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