An efficient method for reliability analysis under epistemic uncertainty based on evidence theory and support vector regression

2015 ◽  
Vol 26 (10-12) ◽  
pp. 340-364 ◽  
Author(s):  
Mi Xiao ◽  
Liang Gao ◽  
Haihong Xiong ◽  
Zhen Luo
Author(s):  
Zhe Zhang ◽  
Chao Jiang ◽  
G. Gary Wang ◽  
Xu Han

Evidence theory has a strong ability to deal with the epistemic uncertainty, based on which the uncertain parameters existing in many complex engineering problems with limited information can be conveniently treated. However, the heavy computational cost caused by its discrete property severely influences the practicability of evidence theory, which has become a main difficulty in structural reliability analysis using evidence theory. This paper aims to develop an efficient method to evaluate the reliability for structures with evidence variables, and hence improves the applicability of evidence theory for engineering problems. A non-probabilistic reliability index approach is introduced to obtain a design point on the limit-state surface. An assistant area is then constructed through the obtained design point, based on which a small number of focal elements can be picked out for extreme analysis instead of using all the elements. The vertex method is used for extreme analysis to obtain the minimum and maximum values of the limit-state function over a focal element. A reliability interval composed of the belief measure and the plausibility measure is finally obtained for the structure. Two numerical examples are investigated to demonstrate the effectiveness of the proposed method.


2019 ◽  
Vol 126 ◽  
pp. 368-391 ◽  
Author(s):  
Jinwen Feng ◽  
Lei Liu ◽  
Di Wu ◽  
Guoyin Li ◽  
Michael Beer ◽  
...  

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