Numerical investigation of unsteady airflow in subway influenced by piston effect based on dynamic mesh Peng Xue, Shijun You, Jiangyue Chao, Tianzhen Ye ⇑ School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, PR China article info Article history: Received 5 August 2012 Received in revised form 2 September 2013 Accepted 12 October 2013 Available online 6 November 2013 Keywords: Standard k–e RNG k–e Full-scale model Shaft Louver abstract The piston effect has a significant influence on unsteady airflows in subway stations and tunnels. This study uses in situ experimental data and a computational fluid dynamics (CFD) method to analyze the three-dimensional unsteady air flow in a subway station and tunnel. An experimental analysis of train-induced unsteady flow was measured in an actual station with platform bailout doors (PBD), and air velocity variations were recorded at regular time intervals. The unsteady numerical analysis uses a dynamic mesh method for the full-scale model. The results indicate that Standard k–e and RNG k–e equa- tions are both appropriate for simulating the high Reynolds numbers in tunnel and station airflow because these equations coincide with the experimental data. Specific diversion and suction ratios exist in each channel of the airflow for piston wind. The proportions between bypass ducts and platforms are stable no matter in open or close systems. And the draught relief shaft located before station plays more important role for piston wind than the one located after the station. Ó 2013 Elsevier Ltd. All rights reserved. 1. Introduction With the rapid development of the subways, more people are paying attention to subway station environmental conditions, such as air temperature, humidity, air velocity, pressure, air quality and noise. Environmental Control Systems (ECS) in subway stations are responsible for delivering a comfortable and healthy station envi- ronment (Yuan and You, 2007; Wang and Li, 2007), but train-in- duced unsteady airflows in the subway tunnels have a great influence on the subway station environment. Many researchers have focused on the issue of unsteady airflow. A theoretical research method was used by Wang et al. to study the piston effect (Wang et al., 2009). In addition, CFD technology has been widely utilized to analyze the airflow in subways. Haitao had validated the formation of piston wind by using FLUENT (Hai- tao, 2010). Kim and Kim employed PSD (Platform Screen Doors, which gets tunnels and platform apart) to carry out a numerical analysis of the effects of duct location on the ventilation perfor- mance in a subway tunnel (Kim and Kim, 2007, 2009). Lin et al. discovered that the length of the draught relief shaft is an impor- tant parameter for tunnel ventilation. Analysis using SES (Subway Environmental Simulation) produced results that agreed well with the measured values, but the sectional area of the draught relief shaft was not the factor for increasing the piston effects and effec- tive air exchange (Lin et al., 2008). Juraeva et al. used CFX to locate better installation locations for tunnel air-curtains (Juraeva et al., 2011). Huang and Gao conducted a numerical study of the train-in- duced unsteady airflows in a subway tunnel with natural ventila- tion ducts using the dynamic layering method by FLUENT. And the numerical results from the RNG k–e model agree quite well with the experimental results (Huang and Gao, 2010). Then he re- vealed the duct number and duct geometry on duct ventilation performance in a subway tunnel (Huang et al., 2011). In 2012, he investigated numerically the characteristics of train-induced unsteady airflow in a subway tunnel in Seoul by using the Standard k–e model. And the results are closer to experimental results than those from Kim (Huang et al., 2012). However, the experimental data used for validating these numerical results were obtained by performing a 1/20 scale experiment. It is difficult to obtain the same Reynolds and Grashof numbers, which are necessary to achieve flow similarity between a small-scale experimental model and a complex actual subway station (Chen, 2009). Thus, in situ measurement data must also be used to validate the numerical models, especially CFD models. In most cities of northern China, platforms typically have PBD (platform bailout doors) system, which leaves an area 0.5 m in height area where the air can flow between the tunnel and plat- form. When a train moves through the tunnel, a piston effect will form. The increasing pressure becomes a compression wave and the piston wind will propagate down to the next station (Ogawa and Fujii, 1997). Jia et al. performed numerical simulations of the flow characteristics in a subway tunnel and station (Jia et al., 0886-7798/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.tust.2013.10.004 ⇑ Corresponding author. Tel./fax: +86 22 27892626. E-mail addresses: xuepeng@tju.edu.cn (P. Xue), yousj@tju.edu.cn (S. You), chaojiangyue@tju.edu.cn (J. Chao), 408396586@qq.com (T. Ye). Tunnelling and Underground Space Technology 40 (2014) 174–181 Contents lists available at ScienceDirect Tunnelling and Underground Space Technology journal homepage: www.elsevier.com/locate/tust