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Probabilistic modeling of disrupted infrastructures due to fallen trees subjected to extreme winds in urban community

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Listed:
  • Guangyang Hou

    (Colorado State University)

  • Suren Chen

    (Colorado State University)

Abstract

Tree failures due to strong winds in urban areas cause extensive direct and indirect economic and environmental loss, including disrupting adjacent infrastructures, such as buildings, underground pipelines, roads and overhead powerlines. To effectively improve the resilience of a community subjected to extreme wind events through prevention, response and recovery, it becomes critical to rationally assess the risks of wind-induced tree failures and the disruptions to different types of infrastructures due to fallen trees. An integrated probabilistic methodology to model the performance of disrupted infrastructures is developed for fallen urban trees subjected to extreme winds in a typical community. Firstly, the finite element modeling of the trees subjected to wind loads is conducted and based on which the windthrow fragility curves of several typical urban tree species are developed. Secondly, a probabilistic framework is developed based on the fragility results to characterize the disrupted scenarios and further predict the disruption probability of some critical infrastructures due to fallen trees. The matrix-based system reliability (MSR) method is introduced to assess the transportation network performance. The proposed framework and MSR method are demonstrated in detail on studying the overhead powerline and transportation network of a small urban community in the city of Fort Collins, Colorado. In the demonstrative example, the probabilities of powerline disruption, road closure, and origin–destination disconnection and travel time reliability under different wind conditions are predicted. Finally, mitigation efforts such as crown thinning of trees are discussed to reduce possible risks of disrupting the infrastructures.

Suggested Citation

  • Guangyang Hou & Suren Chen, 2020. "Probabilistic modeling of disrupted infrastructures due to fallen trees subjected to extreme winds in urban community," 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. 102(3), pages 1323-1350, July.
  • Handle: RePEc:spr:nathaz:v:102:y:2020:i:3:d:10.1007_s11069-020-03969-y
    DOI: 10.1007/s11069-020-03969-y
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    References listed on IDEAS

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    1. Ayberk Kocatepe & Mehmet Baran Ulak & Grzegorz Kakareko & Eren Erman Ozguven & Sungmoon Jung & Reza Arghandeh, 2019. "Measuring the accessibility of critical facilities in the presence of hurricane-related roadway closures and an approach for predicting future roadway disruptions," 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. 95(3), pages 615-635, February.
    2. Kang, Won-Hee & Song, Junho & Gardoni, Paolo, 2008. "Matrix-based system reliability method and applications to bridge networks," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1584-1593.
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    Cited by:

    1. Hou, Guangyang & Muraleetharan, Kanthasamy K. & Panchalogaranjan, Vinushika & Moses, Paul & Javid, Amir & Al-Dakheeli, Hussein & Bulut, Rifat & Campos, Richard & Harvey, P. Scott & Miller, Gerald & Bo, 2023. "Resilience assessment and enhancement evaluation of power distribution systems subjected to ice storms," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Flávio Henrique Mendes & Felipe Coelho de Souza Petean & Ezequiel Luís Tavares Correia & António Manuel Saraiva Lopes, 2024. "A Proximity-Based Approach for the Identification of Fallen Species of Street Trees during Strong Wind Events in Lisbon," Land, MDPI, vol. 13(5), pages 1-11, May.

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