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Integrating Models and Data to Estimate the Structural Reliability of Utility Poles During Hurricanes

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  • Seung‐Ryong Han
  • David Rosowsky
  • Seth Guikema

Abstract

Utility systems such as power and communication systems regularly experience significant damage and loss of service during hurricanes. A primary damage mode for these systems is failure of wooden utility poles that support conductors and communication lines. In this article, we present an approach for combining structural reliability models for utility poles with observed data on pole performance during past hurricanes. This approach, based on Bayesian updating, starts from an imperfect but informative prior and updates this prior with observed performance data. We consider flexural and foundation failure mechanisms in the prior, acknowledging that these are an incomplete, but still informative, subset of the possible failure mechanisms for utility poles during hurricanes. We show how a model‐based prior can be updated with observed failure data, using pole failure data from Hurricane Katrina as a case study. The results of this integration of model‐based estimates and observed performance data then offer a more informative starting point for power system performance estimation for hurricane conditions.

Suggested Citation

  • Seung‐Ryong Han & David Rosowsky & Seth Guikema, 2014. "Integrating Models and Data to Estimate the Structural Reliability of Utility Poles During Hurricanes," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1079-1094, June.
  • Handle: RePEc:wly:riskan:v:34:y:2014:i:6:p:1079-1094
    DOI: 10.1111/risa.12102
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    1. Liu, Haibin & Davidson, Rachel A. & Apanasovich, Tatiyana V., 2008. "Spatial generalized linear mixed models of electric power outages due to hurricanes and ice storms," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 897-912.
    2. Seung‐Ryong Han & Seth D. Guikema & Steven M. Quiring, 2009. "Improving the Predictive Accuracy of Hurricane Power Outage Forecasts Using Generalized Additive Models," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1443-1453, October.
    3. Roshanak Nateghi & Seth D. Guikema & Steven M. Quiring, 2011. "Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1897-1906, December.
    4. Winkler, James & Dueñas-Osorio, Leonardo & Stein, Robert & Subramanian, Devika, 2010. "Performance assessment of topologically diverse power systems subjected to hurricane events," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 323-336.
    5. Han, Seung-Ryong & Guikema, Seth D. & Quiring, Steven M. & Lee, Kyung-Ho & Rosowsky, David & Davidson, Rachel A., 2009. "Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 199-210.
    6. M. Elisabeth Paté‐Cornell & Robin L. Dillon & Seth D. Guikema, 2004. "On the Limitations of Redundancies in the Improvement of System Reliability," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1423-1436, December.
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    Cited by:

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    7. Ye Zheng & Yazhou Xie & Xuejiao Long, 2021. "A comprehensive review of Bayesian statistics in natural hazards engineering," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 63-91, August.
    8. Saraygord Afshari, Sajad & Enayatollahi, Fatemeh & Xu, Xiangyang & Liang, Xihui, 2022. "Machine learning-based methods in structural reliability analysis: A review," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    9. Zhang, Jintao & Bagtzoglou, Yiannis & Zhu, Jin & Li, Baikun & Zhang, Wei, 2023. "Fragility-based system performance assessment of critical power infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).

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