Surrogate-based decision-making for post-earthquake recovery scheduling and resilience assessment of subway systems considering the effect of infrastructure interdependency

This study proposes a method for post-earthquake recovery and seismic resilience assessment of subway systems considering the effect of infrastructure interdependency. A two-stage recovery decision-making model is established. In the pre-earthquake stage, reserved restoration resources are determined by balancing recovery speed and recovery efficiency. In the post-earthquake stage, the optimal restoration schedules are obtained by solving the established functional recovery optimization model using the NSGA-II. A deep learning-based surrogate model for functionality computation is developed to significantly reduce the computational costs in the recovery decision-making and optimization process. A seismic resilience assessment and recovery decision-making process is conducted for a real, large-scale subway system. The results indicate that the subway system exhibits high recovery efficiency in its early-stage recovery and a high level of seismic resilience. The study highlights the significant impact of the municipal power supply system (MPSS) as a critical infrastructure system. The recovery time affected by the MPSS accounts for more than 33% of the total recovery time of the subway system. Ignoring the impact of the MPSS led to an average 12.13% underestimation of the center of resilience. These results underscore the substantial influence of the MPSS on the recovery and seismic resilience of subway systems.

• Record URL:
  • https://doi.org/10.1016/j.ress.2024.110781
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0951832024008524
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09518320
• Supplemental Notes:
  • © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies. Abstract reprinted with permission of Elsevier.
• Authors:
  • Hu, Jie
  • Wen, Weiping
  • Zhai, Changhai
  • Pei, Shunshun
  • 0000-0002-2792-441X
• Publication Date: 2025-4

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 110781
• Serial:
  • Reliability Engineering & System Safety
  • Volume: 256
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0951-8320
  • Serial URL: https://www.sciencedirect.com/journal/reliability-engineering-and-system-safety

Subject/Index Terms

• TRT Terms: Decision making; Disaster preparedness; Disaster resilience; Earthquake resistant design; Earthquakes; Subways
• Geographic Terms: China
• Subject Areas: Environment; Geotechnology; Operations and Traffic Management; Planning and Forecasting; Railroads; Security and Emergencies;

Filing Info

• Accession Number: 01942946
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 22 2025 9:33AM