CFD simulation and assessment of life safety in a subway train fire
Introduction
In case of subway train fire large quantities of smoke are likely to spread rapidly to entire subway station due to stack effect and confinement of the tunnel wall. Especially, because smoke spread path usually coincide with passenger’s evacuation path it will reduce visibility and can cause fatalities by asphyxiation. On 18 February 2003, as an example, a subway train was set on fire with gasoline by a mentally ill patient at Jungangno Station in Daegu, South Korea. The fire quickly spread to all six coaches of the train within 2 min due to the highly flammable interior of the train, destroying two trains and causing large casualties of 192 deaths and 148 injuries. The reasons for many casualties are as follows (National Emergency Management Agency, 2004, Tsujimoto, 2003);
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The interior materials include the seats, flooring and advertisement boards were not made of fire proof materials but composed of flammable fiberglass, carbonated vinyl and polyethylene.
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No adequate smoke control system was operated although much poisonous smoke products due to fire spread to another train.
This fire accident underscored the importance of fire safety engineering in underground space and the need to enhance smoke control system in order to maintain a safe evacuation path that is free of smoke and toxic gases. After this tragedy, the Korean Government determined to improve on the fire safety measures in all subway systems. As part of an effort to improve the life safety in subway train fire, platform screen door (PSD) systems are planned to install in main subway stations in order to prevent smoke spread and achieve safe boarding subway train. For these reasons, the PSD systems are being more and more installed in Seoul Subway. However, even though many researches have been carried out to predict smoke behavior or movement and related topics in underground space such as tunnel (Oka and Atkinson, 1995, Wu and Bakar, 2000, Roh et al., 2007a, Roh et al., 2007b) and subway systems (Cha and Kim, 1999, Gabay, 2004, Lee and Ryou, 2004, Kang, 2007, Yuan and You, 2007), the effect of PSD and ventilation on passenger’s life safety in the event of a subway train fire had rarely been conducted. Therefore, the investigation of effect of PSD and ventilation on life safety is needed since the PSD and ventilation systems will be installed or improved in most subway stations for fire safety. In this study, fire simulation and evacuation simulation are performed to estimates the effect of PSD and ventilation on passenger’s life safety in a subway train fire. The Fire Dynamics Simulator (FDS V406) code is used to predict smoke spread and the available safe egress time. The evacuation of a subway station due to a train fire is simulated to predict the time required for evacuation using self-developed evacuation code, which treats evacuation path such as platform, stairway and other path as 1-D unidirectional line. The characteristics of this evacuation code are such movement model and individual model that it calculates travel speed as a function of passengers’ density by treatment of the movement of each passenger as the motion of individuals. The present evacuation code is key in showing congestion areas, queuing, or bottlenecks within the simulated station.
Section snippets
Subway platform geometry and fire scenario
The subway station chosen for present study is assumed to represent a typical subway station with three stories below the ground, 220 m long × 15 m high × 24 m wide as shown in Fig. 1. The subway station is modeled for simplicity but is representing a type of subway station. For simplicity, no vertical gradient along a platform is assumed. There are six exits to ground (safe region), 5 m wide × 3 m high in Basement 1 and subway turnstiles (ticket gate) in Basement 2, which are mechanical barrier and have
Fire simulation
In order to estimate the effects of PSD and ventilation systems on the passenger’s life safety, simulations of smoke spread in subway station are carried out using Fire Dynamics Simulator (FDS V406) code, developed by National Institute of Standards and Technology (NIST). The FDS code describes fire-driven flows using LES (Large Eddy Simulation) turbulence model, the mixture fraction combustion model, finite volume method of radiation transport for a non-scattering gray gas, and conjugate heat
Evacuation simulation
Passengers’ life safety depends on whether passengers can evacuate safely before untenable conditions occur. Generally, the time required to egress called RSET consists of detection time, response time and movement time. Detection time is the time from fire ignition to fire detection. The response time is defined as the time from the alarm sounding until the passenger initiates movement to evacuate the subway station, a measurement on how long it takes passengers to react and begin to evacuate
Prediction of smoke spread
The smoke spread in modeled subway station is investigated by using transient visibility contour because visibility is the most important factor in estimating the time to reach untenable condition. This may cause passengers to panic and interfere with evacuation and lead to disorientation and death of the passengers. The most useful quantity for assessing visibility in a space is the light extinction coefficient which is a product of the density of smoke particulate and a mass specific
Conclusions
In this study, fire and evacuation simulation is carried out to estimate the effect of PSD and ventilation on passenger’s life safety in the event of a subway station fire.
The conclusions are as follows:
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The passengers in platform with PSD and ventilation have much available time of about 400 s than in case without PSD and ventilation in modeled subway station.
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The time required for evacuation in the modeled subway station is about 6 min and passage times through stairway in Basement 2 and 3 and
Acknowledgments
The authors gratefully acknowledge the financial and other support received for this project from “Development of Railway vehicle Fire Simulation and Ultra Long Rail Tunnelfire Safety Design (T305C1000005-05C010000512)” and partially supported by the Chung Ang University Excellent Grant in 2008.
References (18)
A smoke model and its application for smoke management in an underground mass transit station
Fire safety Journal
(2007)- et al.
Control of smoke flow in tunnel fires
Fire Safety Journal
(1995) - et al.
Critical velocity and burning rate in pool fire during longitudinal ventilation
Tunnelling and underground space technology
(2007) - et al.
Control of smoke flow in tunnel fires using longitudinal ventilation systems – a study of the critical velocity
Fire Safety Journal
(2000) - et al.
CFD simulation and optimization of the ventilation for subway side-platform
Tunnelling and Underground Space Technology
(2007) - et al.
Smoke control in subway tunnels
Korean Journal of Air-Conditioning and Refrigeration Engineering
(1999) - Gabay, Daniel, 2004. Compared fire safety features for metro tunnels, Safe and Reliable Tunnels. In: Innovative...
- Ingason, H., 1994. Heat release rate measurement in tunnel fires. In: Proceedings of the International Conference on...
- et al.
Generation and transport of smoke components
Fire Technology
(2004)