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Probabilistic dynamic resilience quantification for infrastructure systems in multi-hazard environments

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  • Badr, Ahmed
  • Li, Zoe
  • El-Dakhakhni, Wael

Abstract

Resilience has been evolving as a key criterion for infrastructure systems as it ensures the system's dynamic performance pre-, during, and post-hazard disruptions. However, estimating these performances is challenging due to system and operation complexities, and the probabilistic dynamic nature of infrastructure system. Moreover, infrastructure systems are usually exposed to multi-hazard environments, with their own probabilistic behavior, leading to additional complexity in terms of estimating the system response and, subsequently, the overall system resilience. As such, this study develops a probabilistic resilience-centric system dynamics modeling approach to quantify infrastructure dynamic resilience based on a holistic representation of infrastructure systems under multi-hazard scenarios, whereby the probabilistic natures of both the hazards and system are incorporated. Unlike the traditional resilience quantification approaches that represent system resilience by a single value calculated after the system's full recovery, the developed model focuses on tracking the temporal evolution of system resilience along the entire period of system performance deterioration and recovery. A real-world hydropower dam, as an example for infrastructure systems, in British Columbia, Canada is used as a demonstration application to show model utility in developing resilience-guided assessment plans for infrastructure systems. Overall, the developed approach empowers the decision-makers with insights into critical operational periods, the required time to reach specified resilience targets, and the efficiency of risk mitigation measures in real-time.

Suggested Citation

  • Badr, Ahmed & Li, Zoe & El-Dakhakhni, Wael, 2024. "Probabilistic dynamic resilience quantification for infrastructure systems in multi-hazard environments," International Journal of Critical Infrastructure Protection, Elsevier, vol. 46(C).
    • Handle: RePEc:eee:ijocip:v:46:y:2024:i:c:s1874548224000398
    DOI: 10.1016/j.ijcip.2024.100698
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    References listed on IDEAS

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    1. Erma Suryani & Rully A. Hendrawan & Philip F.E. Adipraja & Arif Wibisono & Basuki Widodo & Rarasmaya Indraswari, 2020. "Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework," Transportation Planning and Technology, Taylor & Francis Journals, vol. 43(7), pages 670-697, October.
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    3. Pant, Raghav & Barker, Kash & Zobel, Christopher W., 2014. "Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 92-102.
    4. Magoua, Joseph Jonathan & Li, Nan, 2023. "The human factor in the disaster resilience modeling of critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
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