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Structural Engineering and Mechanics
  Volume 75, Number 6, September25 2020 , pages 771-784
DOI: https://doi.org/10.12989/sem.2020.75.6.771
 


A novel reliability analysis method based on Gaussian process classification for structures with discontinuous response
Yibo Zhang, Zhili Sun, Yutao Yan, Zhenliang Yu and Jian Wang

 
Abstract
    Reliability analysis techniques combining with various surrogate models have attracted increasing attention because of their accuracy and great efficiency. However, they primarily focus on the structures with continuous response, while very rare researches on the reliability analysis for structures with discontinuous response are carried out. Furthermore, existing adaptive reliability analysis methods based on importance sampling (IS) still have some intractable defects when dealing with small failure probability, and there is no related research on reliability analysis for structures involving discontinuous response and small failure probability. Therefore, this paper proposes a novel reliability analysis method called AGPC-IS for such structures, which combines adaptive Gaussian process classification (GPC) and adaptive-kernel-density-estimation-based IS. In AGPC-IS, an efficient adaptive strategy for design of experiments (DoE), taking into consideration the classification uncertainty, the sampling uniformity and the regional classification accuracy improvement, is developed with the purpose of improving the accuracy of Gaussian process classifier. The adaptive kernel density estimation is introduced for constructing the quasi-optimal density function of IS. In addition, a novel and more precise stopping criterion is also developed from the perspective of the stability of failure probability estimation.The efficiency, superiority and practicability of AGPC-IS are verified by three examples
 
Key Words
    reliability analysis; discontinuous response; Gaussian process classification; small failure probability; importance sampling
 
Address
School of Mechanical Engineering and Automation, Northeastern University, Wenhua Road, Heping District,
Shenyang 110819, Liaoning, People's Republic of China
 

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