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Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models

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  • Guo, Qingjun
  • Amin, Shohel
  • Hao, Qianwen
  • Haas, Olivier

Abstract

This paper applies resilience theory in safety management to three subway construction sites: the Shuangzhai, the Sports Centre and the Sanyizhuang stations on the Xi'an Metro Line 14. It analyses the resilience connotation and evaluates the system resilience using the resilience index. The Delphi method determined the resilience indices. The ANP extension cloud synthesis was constructed combining the cloud and matter-element extension theories to address the randomness and ambiguity of the resilience assessment process for subway construction sites. This study reveals that the resilience level was consistent with actual engineering project assessment at all stations. The resilience assessment of the Shuangzhai Station project ranks first followed by that of Sanyizhuang and then the Sports Centre station. The findings of this study argue for strengthening the resilience management, taking measures to optimise and improve the security system, enhancing the defence ability and anti-risk mechanism at the construction sites of the sports centre and the Sanyizhuang stations.

Suggested Citation

  • Guo, Qingjun & Amin, Shohel & Hao, Qianwen & Haas, Olivier, 2020. "Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    • Handle: RePEc:eee:reensy:v:201:y:2020:i:c:s0951832019308816
    DOI: 10.1016/j.ress.2020.106956
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    References listed on IDEAS

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    Cited by:

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    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. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system based on multi-dimensional continuous-time Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 246(C).
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