Version 1
: Received: 19 August 2024 / Approved: 19 August 2024 / Online: 20 August 2024 (10:56:20 CEST)
How to cite:
Li, D.; Zhou, F.; Hou, Y.; Du, S. Cascading Failure and Resilience of Urban Rail Transit Stations Under Flood Conditions: A Case Study of Shanghai Metro. Preprints2024, 2024081386. https://doi.org/10.20944/preprints202408.1386.v1
Li, D.; Zhou, F.; Hou, Y.; Du, S. Cascading Failure and Resilience of Urban Rail Transit Stations Under Flood Conditions: A Case Study of Shanghai Metro. Preprints 2024, 2024081386. https://doi.org/10.20944/preprints202408.1386.v1
Li, D.; Zhou, F.; Hou, Y.; Du, S. Cascading Failure and Resilience of Urban Rail Transit Stations Under Flood Conditions: A Case Study of Shanghai Metro. Preprints2024, 2024081386. https://doi.org/10.20944/preprints202408.1386.v1
APA Style
Li, D., Zhou, F., Hou, Y., & Du, S. (2024). Cascading Failure and Resilience of Urban Rail Transit Stations Under Flood Conditions: A Case Study of Shanghai Metro. Preprints. https://doi.org/10.20944/preprints202408.1386.v1
Chicago/Turabian Style
Li, D., Yuru Hou and Shubo Du. 2024 "Cascading Failure and Resilience of Urban Rail Transit Stations Under Flood Conditions: A Case Study of Shanghai Metro" Preprints. https://doi.org/10.20944/preprints202408.1386.v1
Abstract
The increasing frequency of urban flooding, driven by global climate change, poses significant threats to the safety and resilience of urban rail transit systems. This study systematically examines the cascading failure processes and resilience of these networks under flood conditions, with a specific focus on the Shanghai Metro. A comprehensive resilience evaluation model was developed by integrating geographic information, static network characteristics, and dynamic passenger flow indicators. This study employs an improved Coupled Map Lattice (CML) model to simulate cascading failures, considering the coupling effects of station centrality, geographic elevation, and passenger flow dynamics. Results indicate that stations with higher degree centrality are more likely to trigger rapid cascading failures across the network. However, incorporating dynamic passenger flow and geographic elevation data helps mitigate these effects, emphasizing the need for multi-dimensional resilience strategies. The findings provide valuable insights for urban transit management, offering a scientific foundation for developing targeted disaster response strategies to enhance network resilience against floods. This study advances the understanding of the vulnerability of urban rail transit systems and offers practical guidance for improving disaster preparedness in urban transportation infrastructure.
Environmental and Earth Sciences, Water Science and Technology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
