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A copula-function-based structural system reliability analysis method

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Abstract

In this study, a copula-function-based system reliability analysis method is proposed for reliability evaluation of structures with multiple failure modes. The vine copula function is used to process the correlations that exist between performance functions. The joint probability density function of the performance function random vector is then converted into multiple bivariate copula functions. The maximum likelihood estimation method and Akaike information criteria are used for optimal selection of each bivariate copula function. Based on this process, a joint probability density function of the performance function random vector is constructed. Then, based on the joint probability density function, a Monte Carlo simulation method is given to calculate the system reliability of the structure. Finally, the effectiveness of the method proposed in this study is verified using 4 numerical examples.

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Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant No. 52105253), the National Science Fund for Distinguished Young Scholars (Grant No. 51725502), the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51621004).

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Authors and Affiliations

  1. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, College of Mechanical and Vehicle Engineering, Hunan University, Changsha, 410082, People’s Republic of China

    D. Mi, J. W. Li & C. Jiang

  2. AECC Hunan Aviation Powerplant Research Institute, Zhuzhou, 412002, People’s Republic of China

    D. Mi

  3. Engineering Product Development, Singapore University of Technology and Design, Singapore, 487372, Singapore

    W. Zhang

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  1. D. Mi
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Correspondence to C. Jiang.

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Mi, D., Zhang, W., Li, J.W. et al. A copula-function-based structural system reliability analysis method. Acta Mech 233, 1371–1391 (2022). https://doi.org/10.1007/s00707-022-03160-3

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  • DOI: https://doi.org/10.1007/s00707-022-03160-3

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