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Nataf-based probabilistic buffeting prediction of overhead transmission lines under multi-dimensional turbulent wind excitation

Author

Listed:
  • Du, Wen-Long
  • Fu, Xing
  • Zhu, Deng-Jie
  • Li, Gang
  • Li, Hong-Nan
  • Huang, Zeng-Hao
  • Liu, Ying-Zhou

Abstract

The overhead transmission line (OTL) is a complex nonlinear system susceptible to turbulence-induced buffeting. Classical one-dimensional buffeting analysis overlooks potential vertical turbulence. Additionally, the turbulence parameters associated with stochastic wind fields are simply assumed to be deterministic. Such simplified schemes might cause severe misestimation of extreme responses. Therefore, this paper presents a Nataf-based probabilistic buffeting prediction framework of OTLs under multi-dimensional turbulent wind. Initially, a two-dimensional influence line method is introduced to replace the time-consuming nonlinear finite element analysis (NFEA). Subsequently, Nataf transformation is employed to generate turbulence parameter samples, effectively preserving the marginal probability distribution and correlation structure. Then, the three-dimensional wind speeds are simultaneously synthesized, and the impact of turbulence parameter uncertainty on wind field characteristics is investigated. Next, the time-frequency buffeting responses are analytically estimated, and a quantile-based approach is proposed to quantify the uncertainty of extreme buffeting responses. Finally, the stochastic sensitivity analyses are performed to determine the relative sensitivity of various responses to each turbulence parameter. The results demonstrate that the two-dimensional influence line method exhibits significant efficiency advantages; All deterministic extreme responses are less than the 0.5 quantile of uncertain results; The top three turbulence parameters in sensitivity ranking are identical under different conditions.

Suggested Citation

  • Du, Wen-Long & Fu, Xing & Zhu, Deng-Jie & Li, Gang & Li, Hong-Nan & Huang, Zeng-Hao & Liu, Ying-Zhou, 2025. "Nataf-based probabilistic buffeting prediction of overhead transmission lines under multi-dimensional turbulent wind excitation," Reliability Engineering and System Safety, Elsevier, vol. 257(PA).
  • Handle: RePEc:eee:reensy:v:257:y:2025:i:pa:s0951832025000493
    DOI: 10.1016/j.ress.2025.110846
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    References listed on IDEAS

    as
    1. Liu, Juncai & Tian, Li & Yang, Meng & Meng, Xiangrui, 2024. "Probabilistic framework for seismic resilience assessment of transmission tower-line systems subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. 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).
    3. Bi, Wenzhe & Tian, Li & Li, Chao & Ma, Zhen & Pan, Haiyang, 2023. "Wind-induced failure analysis of a transmission tower-line system with long-term measured data and orientation effect," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. 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).
    5. Jiang, Xia & Lu, Zhenzhou, 2024. "A novel quantile-based sequential optimization and reliability assessment method for safety life analysis," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    6. Dikshit, Saransh & Alipour, Alice, 2023. "A moment-matching method for fragility analysis of transmission towers under straight line winds," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    7. Ma, Liyang & Christou, Vasileios & Bocchini, Paolo, 2022. "Framework for probabilistic simulation of power transmission network performance under hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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