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Worst-case vulnerability assessment and mitigation model of urban utility tunnels

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  • Ouyang, Min
  • Liu, Chuang
  • Wu, Shengyu

Abstract

Constructing utility tunnels would bring new threats, among which the terrorist threat has been identified as the most serious one. Because utility tunnels increase geographical interdependencies among urban infrastructure systems (UISs), and attacking a tunnel segment could cause simultaneous failure of all its carried systems. This paper models the terrorist threat as worst-case failure, and formulates a tri-level mathematical model to assess and mitigate the worst-case vulnerability of urban utility tunnels that carry interdependent UISs. Exact solution of the model is obtained by a column-and-constraint generation based decomposition algorithm. Real utility tunnels that carry interdependent power and water systems in Tianjin Eco-city, China, are used to demonstrate the proposed approach. Results show that there exists a threshold value of the defense budget BD. If BD is less than that threshold, the utility tunnels greatly benefit the attacker and increase the power and water systems’ worst-case vulnerability. If BD is equal to that threshold, the utility tunnels almost do not affect the worst-case vulnerability. If BD is larger than that threshold, the utility tunnels benefit the defender and reduce the worst-case vulnerability.

Suggested Citation

  • Ouyang, Min & Liu, Chuang & Wu, Shengyu, 2020. "Worst-case vulnerability assessment and mitigation model of urban utility tunnels," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:reensy:v:197:y:2020:i:c:s0951832019303060
    DOI: 10.1016/j.ress.2020.106856
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    References listed on IDEAS

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    Cited by:

    1. Chang, Leilei & Zhang, Limao & Xu, Xiaobin, 2023. "Causality-based multi-model ensemble learning for safety assessment in metro tunnel construction," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    2. Hai, Nan & Gong, Daqing & Liu, Shifeng & Dai, Zixuan, 2022. "Dynamic coupling risk assessment model of utility tunnels based on multimethod fusion," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    3. Li, Qing & Li, Mingchu & Gong, Zhongqiang & Tian, Yuan & Zhang, Runfa, 2022. "Locating and protecting interdependent facilities to hedge against multiple non-cooperative limited choice attackers," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    4. Wang, Ying & Zhang, Limao, 2021. "Simulation-based optimization for modeling and mitigating tunnel-induced damages," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    5. Wu, Jiansong & Bai, Yiping & Fang, Weipeng & Zhou, Rui & Reniers, Genserik & Khakzad, Nima, 2021. "An Integrated Quantitative Risk Assessment Method for Urban Underground Utility Tunnels," Reliability Engineering and System Safety, Elsevier, vol. 213(C).

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