Abstract
With complex limit state functions and small failure probability, the analysis of engineering structure reliability is a challenging problem. Most of the traditional methods require a lot of calculation time, which results in delaying the progress of solving engineering. To overcome this issue, a new structural reliability analysis method aiming to select a set of better initial design of experiment (DoE) is proposed in this study. The proposed method combines a weighted sampling based on sample probability and a novel selection strategy to select DoE and conduct active learning. Weighted sampling based on sample probability density makes the DoE uniformly distributed in the sampling space. The novel selection strategy is proposed to make selected DoE near limit state surface (LSS) and has better predictive ability. Numerical examples and engineering examples show that this method can perform energy efficiency analysis in important areas. The results show that the method is accurate and efficient in solving low failure probability and nonlinearity problems.
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Acknowledgments
This work was sponsored by the Fund for National Natural Science Foundation of China (51805348), sponsored by the Fund for Shanxi “1331 Project” Key Subjects Construction.
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Yang Ruigang received the B.S. degree in Mechanical Engineering from Taiyuan University of Technology, in 1998 and the Ph.D. degree in Mechanical Engineering from Taiyuan University of Technology, in 2009. He is a Professor of Taiyuan University of Science and Technology of China. He has published more than 50 journal articles and conference papers.
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Li, W., Yang, R., Qi, Q. et al. A novel structural reliability method based on active Kriging and weighted sampling. J Mech Sci Technol 35, 2459–2469 (2021). https://doi.org/10.1007/s12206-021-0517-0
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DOI: https://doi.org/10.1007/s12206-021-0517-0