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Resilience-Based Repair Strategy for Gas Network System and Water Network System in Urban City

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  • Xirong Bi

    (Key Laboratory of Earthquake Engineering and Engineering Vibration, Institute of Engineering Mechanics, China Earthquake Administration, Harbin 150080, China
    Earthquake Administration of Guangxi Zhuang Autonomous Region, Nanning 530022, China)

  • Jingxian Wu

    (Department of Transportation Engineering, Business School, University of Shanghai for Science & Technology, Shanghai 200093, China)

  • Cheng Sun

    (College of Civil Engineering and Architecture, Guangxi University for Nationalities, Nanning 530006, China)

  • Kun Ji

    (College of Civil and Transportation Engineering, Hohai University, Nanjing 211124, China)

Abstract

In resilience-based frameworks, optimizing the repair strategy and approaches is important for the recovery of the function of gas network systems (GNS) and water network systems (WNS). According to the resilience quantification results of GNS and WNS for a real example urban city in China, the potential impact of utilizing different repair sequences and repair/replacement approaches was investigated. First, a Monte Carlo simulation-based method was proposed to search for the optimal repair sequence according to the skew of the recovery trajectory (SRT). Under high seismic intensity conditions, the significant difference between the repair sequence corresponding to maximum SRT and minimum SRT indicates that choosing the optimal repair sequence is important in the enhancement of repair efficiency, especially when the pipelines have experienced serious damage. We also discussed the parallel repair strategy, which is more consistent with the practice, and can greatly improve the recovery efficiency compared with the single pipeline repair strategy under large damage conditions; however, under minor damage levels, the parallel repair strategy may result in a certain degree of redundancy. Next, three different repair approaches were thoroughly compared, including the point-by-point repair approach, whole pipeline replacement, and hybrid repair approach. At the condition of high seismic intensity (e.g., macroseismic intensity IX), the resilience curves for the hybrid repair approach and the pipeline replacement approach are overall similar and take less time and economic cost than the point-by-point repair approach. However, when the seismic intensity is low, the point-by-point repair approach is most efficient and has the shortest recovery time. Therefore, the choice of repair approach should be determined by stakeholders based on the specific pipeline’s damage situation. Finally, we calculated the joint resilience curves by allocating different weight factors to GNS and WNS, to represent the proportion of water and gas supply that contributes to community resilience.

Suggested Citation

  • Xirong Bi & Jingxian Wu & Cheng Sun & Kun Ji, 2022. "Resilience-Based Repair Strategy for Gas Network System and Water Network System in Urban City," Sustainability, MDPI, vol. 14(6), pages 1-15, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:6:p:3344-:d:769816
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    References listed on IDEAS

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    1. Shuang, Qing & Zhang, Mingyuan & Yuan, Yongbo, 2014. "Node vulnerability of water distribution networks under cascading failures," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 132-141.
    2. Stephanie E. Chang & Timothy McDaniels & Jana Fox & Rajan Dhariwal & Holly Longstaff, 2014. "Toward Disaster‐Resilient Cities: Characterizing Resilience of Infrastructure Systems with Expert Judgments," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 416-434, March.
    3. 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.
    4. Ouyang, Min, 2016. "Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 106-116.
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    1. Chen, Xing-lin & Huang, Zong-hou & Ge, Fan-liang & Lin, Wei-dong & Yang, Fu-qiang, 2024. "A probabilistic analysis method for evaluating the safety & resilience of urban gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

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