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Sustainable Urban Planning Technique of Fire Disaster Prevention for Subway

Author

Listed:
  • Dongho Rie

    (Fire Disaster Prevention Research Center, National Incheon University, Incheon 22012, Korea)

  • Jioh Ryu

    (Department of Mechanical & Automotive Eng., Shinhan University, Uijeongbu 11644, Korea)

Abstract

Subway infrastructure is a representative urban infrastructure for sustainable urban development as part of its policy to harmonize with economic growth. As the transportation infrastructure of large cities develops with high speed and intelligence, more attention will be paid to its safety. The main cause of death in subway fires is asphyxiation, due to the closed specificity of the underground space. Therefore, smoke exhaust facilities should be capable of minimizing the effects of smoke to ensure the safe evacuation of passengers in the event of fire. In this study, three kinds of fire locations are adopted to analyze the distribution of platform temperature, CO, and visibility in connection with the smoke exhaust system operation method. We evaluate the performance of the applicable smoke exhaust system from ASET-based untenable area analysis. Fatality evaluation by escape analysis according to the smoke exhaust system estimates the fatality based on the tenability performance evaluation. Moreover, the FED method was used to evaluate tenability performance. Therefore, the result of this study suggests a solution for sustainable subway Disaster response from the performance evaluation of the subway platform smoke exhaust system for safe evacuation of passengers, which is essential for subway construction or remodeling.

Suggested Citation

  • Dongho Rie & Jioh Ryu, 2020. "Sustainable Urban Planning Technique of Fire Disaster Prevention for Subway," Sustainability, MDPI, vol. 12(1), pages 1-26, January.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:1:p:372-:d:304516
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    References listed on IDEAS

    as
    1. Jiansong Wu & Zhuqiang Hu & Jinyue Chen & Zheng Li, 2018. "Risk Assessment of Underground Subway Stations to Fire Disasters Using Bayesian Network," Sustainability, MDPI, vol. 10(10), pages 1-21, October.
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