An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)

Sajid, Zaman and Yang, Yaqi and You, Peilei and Deng, Hao and Cheng, Xin and Danial, Syed Nasir (2022) An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS). Fire, 5 (3). ISSN 2571-6255

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Abstract

Subway transportation is one of the most prevalent urban transportation methods globally. Millions of people around the globe use this medium as their mode of transportation daily. However, subway stations may be highly prone to fire, smoke, or explosion accidents. The safety of people using subway stations demands a robust and practical framework to assess fire hazards and risks. This study provides a methodology to assess fire risk at a subway station. This study integrates fault tree analysis (FTA) and fuzzy analysis to conduct a comprehensive fire risk assessment. An integrated numerical model of fire temperature and fatality rate was developed using probit correlations for various fire exposure scenarios. The fire dynamics simulator (FDS) provides the probability distribution of casualties caused by fire. To demonstrate the operationalization of the model, Line 1 of the Harbin Metro, located in China, is used as a case study. Results show a probability of 42% of having fire risk in the subway station. Results reveal the highest fatality rate is 6.2% when evacuation time exceeds 200 s. The research helps us to understand the spread of smoke and temperature distribution due to a fire in a subway station. This study is helpful for fire protection engineers, safety managers, and local fire departments to develop a contingency plan to deal with fire in a subway station

Item Type: Article
URI: http://research.library.mun.ca/id/eprint/15515
Item ID: 15515
Additional Information: Memorial University Open Access Author's Fund
Keywords: fire risk assessment, fatality evaluation, subway station, fault tree analysis, fuzzy analysis, FDS software, safety
Department(s): Engineering and Applied Science, Faculty of
Date: 25 May 2022
Date Type: Publication
Digital Object Identifier (DOI): https://doi.org/10.3390/fire5030069
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