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Reliability intelligence analysis of concrete arch bridge based on Kriging model and PSOSA hybrid algorithm

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Abstract

The traditional probabilistic reliability analysis method has problems such as poor convergence, low calculation accuracy, and long time consumption in calculating the reliability of concrete arch bridges due to factors such as the uncertainty of the structural parameters and the performance function being highly nonlinear. This paper proposes a method for calculating the reliability of concrete arch bridges based on the Kriging model and particle swarm optimization algorithm (PSOSA) of the simulated annealing algorithm. This method takes advantage of the Kriging model in small samples and high-dimensional nonlinear data processing capabilities and establishes a response surface model to approximate the actual limit state function. The optimization of the PSO algorithm is realized through the self-adaptive and variable probability mutation operation of the SA algorithm, which enhances the ability of the PSO algorithm to get rid of the local minimum, effectively avoids falling into the local minimum, and finally makes the calculation result tend to the global optimum. It overcomes the problems of slow convergence speed and premature maturity of traditional PSO algorithms. The correctness and effectiveness of the method proposed in this paper are verified through the example analysis and the actual engineering application of a concrete arch bridge. The research results show that the method proposed in this paper has obvious advantages in sample size, calculation accuracy, and iteration times compared with the existing reliability calculation methods for concrete arch bridges. This paper provides a fast and effective method for the structural reliability calculation of concrete arch bridges.

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Acknowledgements

The authors gratefully acknowledge the financial support provided the Science and Technology Project of Zhejiang Provincial Department of Transportation (Grant No. 2018010 and 2019H14) and A Project Supported by Scientific Research Fund of Zhejiang Provincial Education Department (Grant No. Y202250418). The Science and Technology Agency of Zhejiang Province (Grant No. LTGG23E080006).

Funding

This work is supported by the Science and Technology Project of Zhejiang Provincial Department of Transportation (Grant No. 2018010, 2019H17 and 2019H14).

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Authors and Affiliations

  1. Zhejiang University of Technology, Hangzhou, 310014, China

    Dengguo Li, Pengzhen Lu, Liu Yang & Jiahao Wang

  2. Jiaxing Nanhu University, Jiaxing, 3140001, China

    Ying Wu

  3. Transportation Bureau, Longquan, 323700, China

    Zhouling Ye

Authors
  1. Dengguo Li
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  2. Zhouling Ye
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  3. Pengzhen Lu
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  4. Ying Wu
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  5. Liu Yang
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  6. Jiahao Wang
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Contributions

LP proposed the general idea, LD wrote the full text, WY revised and polished it, YL simulation analysis, WJ data sorting.

Corresponding author

Correspondence to Pengzhen Lu.

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The authors declare no competing interests.

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Li, D., Ye, Z., Lu, P. et al. Reliability intelligence analysis of concrete arch bridge based on Kriging model and PSOSA hybrid algorithm. Artif Intell Rev 56 (Suppl 2), 2667–2685 (2023). https://doi.org/10.1007/s10462-023-10587-0

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