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1 ITA - AITES WORLD TUNNEL CONGRESS April 2018 Dubai International Convention & Exhibition Centre, UAE POSTER PAPER PROCEEDINGS

2 Study on the Piston Wind in the Tunnel Generated by a Train with Fire Speeding to a Rescue Station Bai Yun 1, Zeng Yanhua 2 *, Yan Xiaonan 3 1 Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University; Chengdu, China; by165@126.com 2 Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University; Chengdu, China; zengyhua@163.com; The corresponding author 3 Key Laboratory of Transportation Tunnel Engineering, Ministry of Education, Southwest Jiaotong University; Chengdu, China; @qq.com ABSTRACT A 3-D dynamic mesh model of a train with fire speeding to a rescue station was built in FLUENT software of CFD series. This paper has researched the change of the piston wind on cross sections in different positions of the tunnel and rescue station when a train runs and stops in the rescue station with different states (uniform motion, decelerated motion and stationary state). The results show, when the train enters the tunnel, the piston wind in annular space outside the train has the opposite direction with the train; then it has the same direction as the train, and the smoke flows from the head to the rear of the train because the train runs faster than the piston flows. When the train stops in the middle of the rescue station, the piston wind in both ends of rescue station and annular space flows from the head to the rear of the train, and the velocity decelerates to 1.29 m/s after 6 minutes. When the train stops exactly in the rescue station, the smoke flows to transverse alleyways. It is suggested that when the smoke exhaust is designed, special attention should be paid to the influence on smoke flow by the piston wind to make sure the safe evacuation. Key Words: Train with fire; Rescue station; Piston wind; 3-D dynamic mesh model 1. INTRODUCTION With the development of national economy and the continuous improvement of living standards, the railway has become the main transportation in China. Recently, accompanying the construction of high-speed railway, a great deal of super long railway tunnels have been built in the mountainous country. With the length of railway tunnels increasing, the probability of fire and the difficulty of evacuation after the fire have also increased. Because of the closed environment, there is a great limit on the disaster prevention and rescue in railway tunnels. Once the fire happens, a large number of toxic gases with high temperature will spread rapidly in the tunnel. If the personnel are not effectively evacuated, there will be a large number of casualties (Bai, 2014; Cai, 2008; Nakamura, Yamana, Matshushita, Wakamatsu and Wakamatsu, 1992). According to the related specifications in China (Ministry of Railways of the People s Republic of China, 2012), Emergency rescue stations should be set up in tunnels with 20 km length and above, and the fire train should speed to the rescue station to evacuate passengers. In this stage, the air flow changes complexly due to the piston wind induced by the train and the fire-heating air pressure, and therefore influences the smoke movement, which would cause unbearable consequences without effective controlling. Therefore, it seems to be the key to find out the distribution law of the air flow when the fire train speeds to and stops at the rescue station for evacuation. 1

3 More recent studies focused on the piston wind and the aerodynamic phenomena induced by high-speed train in a single tunnel. By using numerical method, Woods and Pope (1981) put forward a generalized one-dimensional flow prediction method for calculating the flow generated by a train in a single-track tunnel, and described a full-size experiment to provide validation data. Fujii and Ogawa (1995) represented the basic characteristics of the flow field created when two trains passed by each other. Ogawa and Fujii (1997) investigated the transient flow field induced by tunnel entry with the focus on the compression wave which was the source of the booming noise at the tunnel exit. By using a reduced-scale test method, Bellenoue, Morinière and Kageyama (2002) simulated experimentally the first compression wave generated in a tunnel when a high-speed train entered it, and validated the possibilities by means of well-documented recent data that were obtained during the full-scale tests carried out in the framework of the European Union research project TRANSAERO. Raghunathan, Kim and Setoguchi (2002) studied the state of the art on the aerodynamic and aeroacoustic problems of high-speed railway train and highlighted proper control strategies to alleviate undesirable aerodynamic problems. Luo, Gao, Wang and Zhao (2003) presented the flow characteristics produced by high-speed train passing a tunnel. Shin and Park (2003) analyzed the flow field around the high speed train which entered into a tunnel with the focus on the vortex and the pressure in the nose region. Kim and Kim (2007) studied the pressure and velocity variations with time in the subway tunnel by conducting both experimental and three-dimensional numerical analyses, the predicted numerical results were in good agreement with the experimental data. Suzuki, Ido, Sakuma and Kajiyama (2008) investigated the aerodynamic force causing the vibration of high-speed trains, through the running test and a numerical simulation. Kim and Kim (2009) carried out a computational analysis of a ventilation system in a subway tunnel by solving 3D Reynolds-averaged Navier-Stokes equations for train-induced unsteady flow using the sharp interface method as the model for the moving boundary of an immersed solid, and found the optimum location of the vent shaft. Han and Wang (2012) explored the laws of how the tunnel s length affected the aerodynamic effects of the subway station. Zhong, Tu, Yang and Liang (2015) investigated the influence of piston wind on fire smoke propagation in subway numerically, and obtained the flow field structure in fire platform, temperature contours and velocity profiles at various scenarios respectively. In this study, the Fluent was used to simulate variations of airflow field in the rescue station when the train ran towards the rescue station in different states (uniform motion, decelerated motion and stationary state). The variation rules of airflow field in the rescue station generated by the train running towards the rescue station are revealed and the results provide advice for the design of ventilation and smoke exhausting for evacuation in super-long railway tunnels later on. 2. GOVERNING EQUATIONS 2 When a train runs in a tunnel, the piston wind is generated in the slender space due to the limitation of tunnel walls and the pressure difference caused by the train moving. Under the viscous effect of air, the air flow near walls of the train has the same speed as the train, while that in other regions moves with various speed. Thus there will be three flow states of turbulent, transitional and laminar regimes under the influence of the train. When a fire train moves in a tunnel and stops at the rescue station, the piston wind has the same direction as the train in the regions without the train, while it has various directions in annular space outside the train.

4 In addition, affected by the fire-heating air pressure and the design feature, the piston wind in the tunnel flows more complexly, and it is very difficult to simulate the state of air flow in the tunnel. In order to facilitate the calculation, the following assumptions are made in the paper (Bao, 2005): (1) Under the Maher number of less than 0.3, it is considered that the air flow with low velocity in the tunnel is incompressible. (2) The air flow could be regard as turbulent flow. (3) The heat release rate (HRR) of the fire source is constant. (4) The doors of transverse alleyways in the rescue station are always open. (5) There is no natural wind in the calculation, and all fans are closed. Fire combustion in a tunnel is a process of material and energy transfer, in which the smoke movement belongs to an unsteady turbulent flow. The characteristic of turbulence is that the movement of any point at any time still satisfies the characteristics of continuous medium flow, though all physical quantities of fluid will change with the change of space and time. In view of the above hypothesis and analysis, the three-dimensional (3-D) unsteady turbulent flow in a tunnel containing a rescue station can be simulated, and the four conservation equations are applicable to the airflow in tunnels. The mass conservation equation is expressed as follows: ρ + ρu = 0 (1) t where ρ is the density of air, u is velocity of the fluid, t is the time. The momentum conservation equation (i.e. the N-S equation) is expressed as follows: r ( ρu) + ρuu + p = ρg + f + τ (2) ij t where p is the pressure on a microelement, ρg is the body force, f is the source term caused by pollution sources and heat sources, τ ij is the viscous stress on the microelement. The energy conservation equation is expressed as follows: Dp ( ρhs) + ρhu s = + q& ʹʹʹ q& ʹʹ + Φ (3) t Dt where h S is the sensible enthalpy, qʹʹʹ & is the HRR per unit volume, qʹʹ & is the heat flux, Φ is the energy dissipation function. The component transport conservation equation is expressed as follows: ( ρy i ) + ρyu i = ρd i Y i + m& i ʹʹʹ (4) t where Y i is the mass fraction of the ith kind of gas component, D i is the diffusion coefficient of the ith kind of gas component, mʹʹʹ & is the mass generation rate per unit volume of the ith kind of gas component. 3

5 3. NUMERICAL SIMULATION 3.1. CFD model Based on a super-long railway tunnel in Southwestern China which is approximately 34.5 km long and contains a rescue station in the middle of it, the calculation model, made up of a main tunnel, a pilot tunnel, a rescue station and an air region, was built using Gambit2.4.6 (Fluent Company, 2004). Through previous researches, the flow field in the tunnel tends to be stable as the train runs into the tunnel at a certain distance, and it will not change until the train starts to slow down. By shortening the tunnel model, both the tunnel and pilot tunnel are built as 3550 m long. The rescue station in the middle of the tunnel (containing the main tunnel, the pilot tunnel and 11 transverse alleyways) is 550 m long. The air region linked with the tunnel inlet is 450 m long, 100 m wide and 45 m high. The train is 300 m long, 3.1 m wide and 4 m high, its original position is in the middle of the air region, and the distance between the head of the train and the tunnel inlet is 100 m. The cross sections of the tunnel are shown in Figure 1, and the schematic diagram of the computational analysis model is shown in Fig. 2. Figure 1. Cross sections of the tunnel: (a) normal section; (b) widening section in the rescue station. Figure 2. Schematic diagram of the computational analysis model. 4

6 3.2. Dynamic grid settings The objective of the paper is to investigate numerically the variation of the piston wind in induced by fire train s moving towards the rescue station, and the dynamic mesh technique was used to model the train s moving in the tunnel. Numerical domain was divided into two categories: static region and motion region, and two regions were linked by sliding grid interfaces. The motion region belonged to rigidbody motion, and its motions were defined using user-defined function (hereafter UDF ) (Bai, Zeng, Zhang, Yan, Ruan and Zhou, 2016). The diagrammatic representation for dynamic grid settings is shown in Figure 3. Figure 3. Diagrammatic representation for dynamic grid settings. In the numerical simulation, the influence of the natural wind is ignored. The fire source, with the HRR of 20 MW, is located in the middle of the train, which with the distance of 100 m far outside the tunnel inlet begins to run at a constant speed of m/s. After the train runs at the constant speed for 36 seconds, it is decelerated to stop at the rate of m/s2. Then the train stops in the middle of the rescue station after 48 seconds. The schedule of the numerical train run is shown in Figure Numerical train speed (m/s) Numerical train speed (m/s) Time (s) Running distance (m) (a) (b) Figure 4. Schedule of the numerical train run: (a) variation with time; (b) variation with running distance. 5

7 4. RESULT AND DISCUSSION 4.1. Analysis of the speed field in annular space When a train runs in a tunnel, the air flow in the annular space, surrounded by walls of tunnel and train, is different from that in the no train space due to the friction of walls and the effect of the train ends. Here the cross section in the annular space 100 m away from the train rear is focused on, and the following analyses of the flow field in the annular section are carried out in the stages of uniform motion and decelerated motion The speed field in the uniform motion stage Figure 5 shows the speed distribution in the annular section when it enters the tunnel for 100 meters and 900 meters. As can be seen from the figure, the flow field changes with the constant speed of the train. When the section is 100 m far away from the entrance in the tunnel, the air flow has the opposite direction with the train, and the velocity in the bottom part is larger than that in the top part, and the maximum velocity is about 14.5 m/s. When the section is 900 m far away from the entrance, it still has the opposite direction with the train, and the maximum velocity in the bottom part is about 9.0 m/s. (a) (b) Figure 5. Velocity vector in the annular section: (a) 100 m and (b) 900 m far away from the entrance in the tunnel. Set the direction of the train running as the positive direction, figure 6 shows the variations of average velocity with uniform motion time in the annular section. As is shown in Figure 6, in the period of 0 9 s, the train moves in the air region, and the average velocity is nil. Then the train enters the tunnel, and the airflow has the opposite direction to the train running. When the annular section has just entered the tunnel (t=9 s ), the airflow has maximum average velocity with m/s. Then it approximately linearly decreases with time, and the value is m/s as the train begins to decelerate (t=36 s ). 6

8 0-2 Average velocity (m/s) Uniform motion time (s) Figure 6. Average velocity variations in the annular section with uniform motion time The speed field in the decelerated motion stage Figure 7 shows the speed distribution in the annular section when the train has decelerated for 24 seconds and 48 seconds. As can be seen from the figure, the air flow gradually reverses its direction which becomes the same as the train running direction. When the train has decelerated for 24 seconds, the air flow in most part of the section has the same direction as the train running except that in the bottom part, and the maximum value of the velocity is about 3.5 m/s. When the train has decelerated for 48 seconds, the air flow direction in all part of the annular section is the same as the train running, and the maximum value is about 4.5 m/s. (a) (b) Figure 7. Velocity vector in the annular section: (a) td = 24 s; (b) td = 48 s. Figure 8 shows the variations of average velocity with decelerated motion time in the annular section. It can be observed clearly from Figure 8 that in the early period of decelerated motion, the airflow has the opposite direction to the train running, and the value approximately linearly decreases with time. When the train has decelerated for 20 seconds (td=20 s), the average velocity becomes zero. Then the air flow has the same direction as the train running, and the average velocity increases gradually. When td=27 s, the annular section just enters the rescue station, its value is about 2.2 m/s. When the train just stops (td=48 s), the average velocity reaches 3.89 m/s. 7

9 4 2 Average velocity (m/s) Decelerated motion time (s) Figure 8. Average velocity variations in the annular section with decelerated motion time Analysis of the piston wind in the rescue station Here the cross sections on both ends of the rescue station are focused on, and Figure 9 shows the variation of average velocity with time in the two sections. As can been seen from Figure 9, before the train enters the tunnel (t=0 3 s), there is no piston wind in the rescue station. After the train enters the tunnel with constant speed, the piston wind in the entrance of the rescue station has the same direction as the train running, and the velocity increases gradually. The piston wind reaches its peak with the value of 7.06 m/s at 48 s. When the head of the train begins to enter the rescue station (t=51 s), the entrance becomes an annular section, and the piston wind reduces sharply to 0.76 m/s, then it gradually increases again. When the rear enters the rescue station, the entrance reverts to a full section, and the piston wind begins to decrease. When t=84 s, the train has just stopped, and the average velocity in the entrance of the rescue station is 4.58 m/s. When the train has stopped for 6 minutes (t = 444 s), the average velocity is down to 1.29 m/s Average Velocity (m/s) Average Velocity (m/s) Time (s) Time (s) Figure 9. Average velocity variations in the sections on both ends of the rescue station: (a) the entrance; and (b) the exit. The variation of the piston wind in the exit section of the rescue station is relatively stable because of the absence of train passing. When t=48 s, the average velocity reaches the maximum of 2.26 m/s, then it decreases gradually. The piston wind is down to 1.96 m/s when t=84 s, and 1.14 m/s when t=444 s. 8

10 5. CONCLUSIONS The numerical simulation on variations of the piston wind generated by the fire train running towards the rescue station in different states (uniform motion, decelerated motion and stationary state) was conducted using dynamic mesh technique. The following conclusions were drawn. (1) When the fire train enters the tunnel, the air flow in annular space has the opposite direction to the train running. With the train running in the tunnel, the direction of air flow becomes the same as the traffic direction, and the velocity approximately linearly increases. When the train just stops in the rescue station, the velocity reaches the value of 3.89 m/s. (2) As the train stops, the piston wind in the entrance, middle and exit of the rescue station flows from the rear to the head of the train, the values are 4.58 m/s, 3.89 m/s and 1.96 m/s respectively. They would decrease to about 1 m/s after the train stopping for 6 minutes. Therefore, in the earlier stage of train s stopping, it will take about 1 minute for the fire smoke to flow rapidly from the rear to the head of the train without effective control measures, and this is bound to have a significant impact on the passengers evacuation. It is suggested that when the smoke exhaust is designed, special attention should be paid to the influence on smoke flow by the piston wind to make sure the safe evacuation. (3) In the stages of uniform motion, decelerated motion and earlier stationary state, the piston wind in the entrance of the rescue station is obviously larger than that in the exit section of the rescue station, and thus a large amount of smoke will flow to the transverse passages, which is unfavorable for evacuation. So when the ventilation and smoke exhaust design is designed, it should take full account of the influence, and the fresh wind system should be started before the train braking to prevent the fire smoke from flowing into the transverse passages. (4) The length of a tunnel is one of the important factors which influence the piston wind, and the railway, in which the rescue station is generally set up, is above 20 km. Because of the inconvenience of numerical calculation, the simulation of a tunnel with 4000 m length was conducted. Although the value of the piston wind is different from that in the actual super-long railway tunnel, the change trend is consistent. So, the conclusions of this paper can provide references for the design of disaster prevention and evacuation in the long railway tunnel. 6. ACKNOWLEDGEMENTS This paper was supported by the National Natural Science Foundation of China (No: ). REFERENCES Bai, Y., Zeng, Y., Zhang, X., Yan, X., Ruan, L., & Zhou, X. (2016). Numerical and experimental study on the flow field induced by a train urgently speeding to the rescue station. Tunnelling and Underground Space Technology, 58, Bai, Y. (2014). Study on Fire Characteristics and Smoke Control of Rescue Station Test in Railway Tunnel. Southwest Jiaotong University, Chengdu. Bao, H. (2005). Numerical Simulation on Piston Wind Produced by Train in a Subway. Nanjing University of Science and Tech, Nanjing. 9

11 Bellenoue, M., Morinière, V., & Kageyama, T. (2002). Experimental 3-D simulation of the compression wave, due to train-tunnel entry. Journal of Fluids and Structures, 16(5), Cai, J. (2008). The study on the fire analysis and the fire rescue preplan of highway tunnel. Chongqing Jiaotong University, Chongqing. Fluent Company GAMBIT 2.2 Tutorial Guide. Fujii, K., & Ogawa, T. (1995). Aerodynamics of High Speed Trains Passing by Each Other. Computers & Fluids, 24(8), Han H., & Wang Y. (2012). Research on the Influence of the Length of the Tunnel on the Aerodynamic Effects of High-speed Railway Tunnels with Underground Stations. Traffic Engineering and Technology for National Defence, (2), Kim J.Y., & Kim, K.Y. (2007). Experimental and Numerical Analyses of Trainintroduced Unsteady Tunnel Flow in Subway. Tunnel and Underground Space Technology, 22, Kim, J.Y., & Kim, K.Y. (2009). Effects of vent shaft location on the ventilation performance in a subway tunnel. Journal of Wind Engineering and Industrial Aerodynamics, 97, Luo, J., Gao B., Wang Y., & Zhao, W. (2003). Numerical Simulation on an Unsteady Two-dimension Flow Produced by High-Speed Train Passing a Tunnel. Journal of the China Railway Society, 25(2): Ministry of Railways of the People s Republic of China. (2012). TB Code for Design on Evacuation Engineering for Disaster Prevention and Rescue of Railway Tunnel. Beijing: China Railway Press. Nakamura, H., Yamana, T., Matshushita, T., Wakamatsu, T., & Wakamatsu, T. (1992). Research on smoke control in underground structures. Tunnelling and Underground Space Technology, 7(4), Ogawa, T., & Fujii, K. (1997). Numerical Investigation of Three-dimensional Compressible Flows Induced by a Train Moving into a Tunnel. Computers & Fluids, 26(6), Raghunathan, R.S., Kim H.D., & Setoguchi T. (2002). Aerodynamics of High-speed Railway Train. Progress in Aerospace Sciences, 38, Shin, C.H., & Park, W.G. (2003). Numerical Study of Flow Characteristics of the High Speed Train Entering into a Tunnel. Mechanics Research Communications, 30: Suzuki, M., Ido, A., Sakuma, Y., & Kajiyama, H. (2008). Full-Scale Measurement and Numerical Simulation of Flow around High-Speed Train in Tunnel. Journal of Mechanical Systems for Transportation and Logistics, 1(3), Woods, W.A., & Pope, C.W. (1981). A generalised flow prediction method for the unsteady flow generated by a train in a single-track tunnel. Journal of Wind Engineering and Industrial Aerodynamics, 7, Zhong, W., Tu, R., Yang, J.P., & Liang, T.S. (2015). A study of the fire smoke propagation in subway station under the effect of piston wind. Journal of Civil Engineering and Management, 21(4),

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