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

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...

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Main Authors: Zaman Sajid, Yaqi Yang, Peilei You, Hao Deng, Xin Cheng, Syed Nasir Danial
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Fire
Subjects:
Online Access:https://www.mdpi.com/2571-6255/5/3/69
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author Zaman Sajid
Yaqi Yang
Peilei You
Hao Deng
Xin Cheng
Syed Nasir Danial
author_facet Zaman Sajid
Yaqi Yang
Peilei You
Hao Deng
Xin Cheng
Syed Nasir Danial
author_sort Zaman Sajid
collection DOAJ
description 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.
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spelling doaj.art-bc58eb8f22de4cff879fc862b005ac8e2023-11-23T16:35:41ZengMDPI AGFire2571-62552022-05-01536910.3390/fire5030069An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)Zaman Sajid0Yaqi Yang1Peilei You2Hao Deng3Xin Cheng4Syed Nasir Danial5Department of Process Engineering, Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaDepartment of Process Engineering, Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaDepartment of Process Engineering, Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaDepartment of Process Engineering, Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaDepartment of Process Engineering, Faculty of Engineering & Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, CanadaCentre for Earth Observation Science, University of Manitoba, Winnipeg, MB R3T 2N2, CanadaSubway 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.https://www.mdpi.com/2571-6255/5/3/69fire risk assessmentfatality evaluationsubway stationfault tree analysisfuzzy analysisFDS software
spellingShingle Zaman Sajid
Yaqi Yang
Peilei You
Hao Deng
Xin Cheng
Syed Nasir Danial
An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
Fire
fire risk assessment
fatality evaluation
subway station
fault tree analysis
fuzzy analysis
FDS software
title An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
title_full An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
title_fullStr An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
title_full_unstemmed An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
title_short An Explorative Methodology to Assess the Risk of Fire and Human Fatalities in a Subway Station Using Fire Dynamics Simulator (FDS)
title_sort explorative methodology to assess the risk of fire and human fatalities in a subway station using fire dynamics simulator fds
topic fire risk assessment
fatality evaluation
subway station
fault tree analysis
fuzzy analysis
FDS software
url https://www.mdpi.com/2571-6255/5/3/69
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