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A Kriging-based probabilistic framework for multi-hazard performance assessment of transmission tower-line systems under coupled wind and rain loads

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  • Bi, Wenzhe
  • Tian, Li
  • Li, Chao
  • Ma, Zhen

Abstract

The increasing severity and occurrence of multiple hazards attributed to climate change exacerbate the failure risk of infrastructure systems. This paper proposes a Kriging-based probabilistic framework for the multi-hazard performance assessment of structures, which is applied to a transmission tower-line system (TTLS) subjected to combined wind and rain loads, considering the dependency and directionality effects of wind and rain related variables. Based on the long-term meteorological data, the joint probability distribution (JPD) of wind speed, wind direction, and rain intensity is modeled using vine copulas. Meanwhile, a Kriging surrogate demand model is developed and facilitates the multi-hazard fragility analysis. The fragility estimates are finally integrated with the JPD model through the importance sampling technique to estimate the actual failure probability of the regional TTLS. The results indicate that rainfall can generally increase the structural vulnerability, especially for the multi-hazard scenario of strong wind accompanied by torrential rain. The underlying correlations among multi-hazard variables, if not accounted for, will result in an overestimation of the failure probability. The results of the case study verify the rationality and efficiency of the proposed framework.

Suggested Citation

  • Bi, Wenzhe & Tian, Li & Li, Chao & Ma, Zhen, 2023. "A Kriging-based probabilistic framework for multi-hazard performance assessment of transmission tower-line systems under coupled wind and rain loads," Reliability Engineering and System Safety, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:reensy:v:240:y:2023:i:c:s095183202300529x
    DOI: 10.1016/j.ress.2023.109615
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    References listed on IDEAS

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    1. Sancetta, Alessio & Satchell, Stephen, 2004. "The Bernstein Copula And Its Applications To Modeling And Approximations Of Multivariate Distributions," Econometric Theory, Cambridge University Press, vol. 20(3), pages 535-562, June.
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    Cited by:

    1. Fang, Chen & Xu, You-Lin & Li, Yongle & Li, Jinrong, 2024. "Serviceability analysis of sea-crossing bridges under correlated wind and wave loads," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
    2. Macedo, Felipe C. & Alminhana, Fábio & Fadel Miguel, Leandro F. & Beck, André T., 2024. "Performance-based reliability assessment of transmission lines under tornado actions," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    3. Francioli, M. & Petrini, F., 2024. "Performance-based multi-hazard engineering (PB-MH-E): The case of steel buildings under earthquake and wind," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    4. Meng, Xiangrui & Tian, Li & Li, Chao & Liu, Juncai, 2024. "Copula-based wind-induced failure prediction of overhead transmission line considering multiple temperature factors," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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