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Hybrid Hidden Markov Models for resilience metrics in a dynamic infrastructure system

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  • Zhao, S.
  • Liu, X.
  • Zhuo, Y.

Abstract

Disruptive events triggered by natural disasters, man-made accidents, or violent attacks can lead to significant consequences and losses for networked infrastructure systems. A critical consideration for a disrupted system is enhancing its resilience to rapidly recover to the desired performance level. The nature of the resilience measurement problem can be summarized as the following: (1) system capacities are dependent/interdependent and time-varying; (2) the severity of consequences and potential losses caused by disruptions are associated with uncertainties; (3) system performances depend on resources input/dispatch strategies and system-design attributes; and (4) historical information in major disaster prevention is incomplete. In this study, we propose a resilience analysis framework and a metric for measuring resilience that combines resilience capacities, disruption scenarios, and dispatch strategies. Non-homogeneous Hidden Markov Models (HMM) are designed to evaluate resilience capacities, including adaptive capacity, absorptive capacity, and recovery capacity under different disruption scenarios. Subsequently, an optimized dispatch strategy is proposed to maximize system resilience and ensure the continuity of system functionality. Finally, a case study of a water supply system taken from Shanghai City demonstrates that the proposed approaches are effective for system-resilience assessment.

Suggested Citation

  • Zhao, S. & Liu, X. & Zhuo, Y., 2017. "Hybrid Hidden Markov Models for resilience metrics in a dynamic infrastructure system," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 84-97.
    • Handle: RePEc:eee:reensy:v:164:y:2017:i:c:p:84-97
    DOI: 10.1016/j.ress.2017.02.009
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    8. Mingyuan Zhang & Juan Zhang & Gang Li & Yuan Zhao, 2020. "A Framework for Identifying the Critical Region in Water Distribution Network for Reinforcement Strategy from Preparation Resilience," Sustainability, MDPI, vol. 12(21), pages 1-17, November.
    9. Hu, Jinqiu & Khan, Faisal & Zhang, Laibin, 2021. "Dynamic resilience assessment of the Marine LNG offloading system," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
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    12. Cai, Baoping & Xie, Min & Liu, Yonghong & Liu, Yiliu & Feng, Qiang, 2018. "Availability-based engineering resilience metric and its corresponding evaluation methodology," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 216-224.
    13. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    14. Cheng, Yao & Elsayed, E.A. & Chen, Xi, 2021. "Random Multi Hazard Resilience Modeling of Engineered Systems and Critical Infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    15. Márcio das Chagas Moura & Helder Henrique Lima Diniz & Enrique López Droguett & Beatriz Sales da Cunha & Isis Didier Lins & Vicente Ribeiro Simoni, 2017. "Embedding resilience in the design of the electricity supply for industrial clients," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-33, November.
    16. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    17. Dhulipala, Somayajulu L.N. & Flint, Madeleine M., 2020. "Series of semi-Markov processes to model infrastructure resilience under multihazards," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    18. Jiang, J. & Liu, X., 2018. "Multi-objective Stackelberg game model for water supply networks against interdictions with incomplete information," European Journal of Operational Research, Elsevier, vol. 266(3), pages 920-933.
    19. Suo, Weilan & Wang, Lin & Li, Jianping, 2021. "Probabilistic risk assessment for interdependent critical infrastructures: A scenario-driven dynamic stochastic model," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    20. Dui, Hongyan & Lu, Yaohui & Wu, Shaomin, 2024. "Competing risks-based resilience approach for multi-state systems under multiple shocks," Reliability Engineering and System Safety, Elsevier, vol. 242(C).

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