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1、CFD simulation and optimization ofthe ventilation for subway side-platform Feng-Dong Yuan *, Shi-Jun YouAbstractTo obtain the velocity and temperature field of subway station and the optimized ventilation mode of subway side-platform station, this paper takes the evaluation and optimization of the v
2、entilation for subway side-platform station as main line, builds three dimensional models of original and optimization design of the existed and rebuilt station. And using the two-equation turbulence model as its physics model, the thesis makes computational fluid dynamics (CFD) simulation to subway
3、 side-platform station with the boundary conditions collected for simulation computation through field measurement. It is found that the two-equation turbulence model can be used to predict velocity field and temperature field at the station under some reasonable presumptions in the investigation an
4、d study. At last, an optimization ventilation mode of subway side-platform station was put forward.1. Introduction Computational fluid dynamics (CFD) software is commonly used to simulate fluid flows, particularly in complex environments (Chow and Li, 1999; Zhang et al., 2006; Moureh and Flick, 2003
5、). CFD is capable of simulating a wide variety of fluid problems (Gan and Riffat, 2004; Somarathne et al., 2005; Papakonstantinou et al., 2000; Karimipanah and Awbi, 2002). CFD models can be realistically modeled without investing in more costly experimental method (Betta et al., 2004; Allocca et al
6、., 2003; Moureh and Flick, 2003). So CFD is now a popular design tool for engineers from different disciplines for pursuing an optimum design due to the high cost, complexity, and limited information obtained from experimental methods (Li and Chow, 2003; Vardy et al., 2003; Katolidoy and Jicha, 2003
7、). Tunnel ventilation system design can be developed in depth from the predictions of various parameters, such as vehicle emission dispersion, visibility, air velocity, etc. (Li and Chow, 2003; Yau et al., 2003; Gehrke et al., 2003). Earlier CFD simulations of tunnel ventilation system mainly focus
8、on emergency situation as fire condition (Modic, 2003; Carvel et al., 2001; Casale, 2003). Many scientists and research workers (Waterson and Lavedrine, 2003; Sigl and Rieker, 2000; Gao et al., 2004; Tajadura et al., 2006) have done much work on this. This paper studied the performance of CFD simula
9、tion on subway environment control system which has not been studied by other paper or research report. It is essential to calculate and simulate the different designs before the construction begins, since the investment in subways construction is huge and the subway should run up for a few decade y
10、ears. The ventilation of subway is crucial that the passengers should have fresh and high quality air (Lowndes et al., 2004; Luo and Roux, 2004). Then if emergency occurred that the well-designed ventilation system can save many peoples life and belongings (Chow and Li, 1999; Modic, 2003; Carvel et
11、al., 2001). The characteristics of emergency situation have been well investigated, but there have been few studies in air distribution of side-platform in normal conditions. The development of large capacity and high speed computer and computational fluid dynamics technology makes it possible to us
12、e CFD technology to predict the air distribution and optimize the design project of subway ventilation system. Based on the human-oriented design intention in subway ventilation system, this study simulated and analyzed the ventilation system of existent station and original design of rebuilt statio
13、ns of Tianjin subway in China with the professional software AIRPAK, and then found the optimum ventilation project for the ventilation and structure of rebuilt stations.2. Ventilation systemTianjin Metro, the secondly-built subway in China, will be rebuilt to meet the demand of urban development an
14、d expected to be available for Beijing 2008 Olympic Games. The existent subway has eight stations, with a total length of 7.335 km and a 0.972 km average interval. For sake of saving the cost of engineering, the existent subway will continue to run and the stations will be rebuilt in the rebuilding
15、Line 1 of Tianjin subway. Although different existent stations of Tianjin Metro have different structures and geometries, the Southwest Station is the most typical one. So the Southwest Station model was used to simulate and analyze in the study. Its geometry model is shown in Fig. 1.2.1. The struct
16、ure and original ventilation mode of existent station The subway has two run-lines. The structure of Southwest Station is, length width height = 74.4 m(L) 18.7 m(W) 4.4 m(H), which is a typical side-platform station. Each side has only one passageway (length height = 6.4 m(L) 2.9 m(H). The middle of
17、 station is the space for passengers to wait for the vehicle. The platform mechanical ventilation is realized with two jet openings located at each end of station and the supply air jets towards train and track. There is no mechanical exhaust system at the station and air is removed mechanically by
18、tunnel fans and naturally by the exits of the station.2.2. The design structure and ventilation of rebuilt station The predicted passenger flow volume increase greatly and the dimension of the original station is too small, so in the rebuilding design, the structure of subway station is changed to,
19、(length width height = 132 m(L) 17.438 m(W) 4.65 m(H), and each side has two passageways. The design volume flow of Southwest Station is 400000 m3/h. For most existent stations, the platform height is only 2.9 m, which is too low to set ceiling ducts.So in the original design, there are two grille v
20、ents at each end of the platform to supply fresh air along the platform length direction and two grille vents to jet air breadthways towards trains. The design velocity of each lengthways grille vent is 5.54 m/s. For each breadthways vent, it is 5.28 m/s. Under the platform, 80 grille vents of the s
21、ame velocity (4.62 m/s, 40 for each platform of the station) are responsible for exhaust.3. CFD simulation and optimization The application of CFD simulation in the indoor environment is based on conversation equations of energy, mass and momentum of incompressible air. The study adopted a turbulenc
22、e energy model that is the two-equation turbulence model advanced by Launder and Spalding. And it integrated the governing equation on the capital control volumes and discretized in the definite grids, at last simulated and computed with the AIRPAK software.3.1. Preceding simplifications and presump
23、tions Because of mechanical ventilation and the existence of train-driven piston wind, the turbulence on platform is transient and complex. Unless some simplifications and presumptions are made, the mathematics model of three-dimensional flow is not expressed and the result is divergent. While ensur
24、ing the reliability of the computation results, some preceding simplifications and presumptions have to be taken.(1) The period of maximum air velocity is paid attention to in the transient process. Apparently the maximum air velocity is reached at the period when train stops at or starts away from
25、the station (Yau et al., 2003; Gehrke et al., 2003), so the period the simulation concerns about the best period of time for simulation is from the point when at the section of x = 0.0 m (Fig. 1) and the air velocity begin to change under piston-effect to the point when train totally stops at the st
26、ation (defined as a pulling-in cycle).(2) Though the pulling-in cycle is a transient process, it is simplified to a steady process.(3) Because the process is presumed to a steady process, the transient velocity of test sections, which was tested in Southwest Station in pulling-in cycle, is presumed
27、to the time-averaged velocity of test sections.(4) The volume flow driven into the station by pulling-in train is determined by such factors as BR (blocking ratio, the ratio of train cross-section area to tunnel cross-section area), the length of the train and the resistance of station etc. For exis
28、tent and new stations, BRs are almost the same. Although the length of the latter train doubles that of the former which may increase the piston flow volume, the resistance of latter is greater than that of the former which may counteract this increase. So it is presumed that the piston flow volume
29、is same for both existent and new station and that the volume flow through the passenger exits is also same. Based on this presumption, the results of the field measurements at the existent station can be used as velocity boundary conditions to predict velocity filed of new station.3.2. Original con
30、ditions To obtain the boundary conditions for computation and simulation, such as the air velocity and temperature of enclosure, measures were done by times at Southwest Station.All data are recorded during a complete pulling-in cycle. The air velocities were measured by the multichannel anemone-mas
31、ter hotwire anemoscope and infrared thermometer is used to measure the temperature of the walls of the station which are taken as the constant temperature thermal conditions in the simulation.3.2.1. Temperatures of enclosure Divide the platform into five segments and select some typical test positio
32、ns. The distributing temperature of enclosure is shown in Table 1. It can be seen from Table 1 that all temperatures of enclosure are between 23 _C and 25 _C, there is little difference in all test positions, and the average temperature is 24 _C. So all temperatures of subway stations walls is 24 _C
33、 in CFD computation and simulation.3.2.2. Time-averaged air velocity above the platformFig. 1 is the location of test section and the layout of measuring points. The data measured include 12 transient velocities in each section (AH in Fig. 1), which were deal with sections time-averaged velocities i
34、n the period, 12 points velocities of passageway, which is used to acquire the average flow, and the velocities of each end of station, which is used to acquire the average piston flow volume.Fig. 2 is the lengthways velocities measured of platform sections, is the maximum air velocity, is the minim
35、um air velocity and is the average air velocity. Fig. 2 shows that the maximum air velocity is at the passageway. At the passageway the change of air velocity is about 2.25 m/s, which is the maximum and indicates that the passageway is the position effected most by the piston wind effect, and the ai
36、r velocity of section D and E after the passageway is almost the same, which indicates that the piston wind can hardly effect the air velocity after the passageway.CFD模拟和地铁站台的优化通风 Feng-Dong Yuan *, Shi-Jun You摘要获得车站的速度和温度领域同时地铁站台的最优方式。这篇文章验证和在主要线路上的地铁通风的最优化。建造三个空间最初的模型和现存物的优化设计和重建车站。并且用两个二平衡空气紊乱模型同样
37、与它的物理模型。这篇论文计算流体动力学（CFD）模拟地铁边台站，它的边界条件通过收集测量数据进行模拟计算。发现这两个流体公式模型可以被用于预知速度和温度在车站下的一些合理的假设下进行学习。最后这一个地铁车站站台的最优化通风方案被提出来了。1介 绍CFD（Computational fluid dynamics）软件通常是模拟流动性流程图。特别是在复杂的环境计量中（Chow and Li, 1999; Zhang et al., 2006; Moureh and Flick, 2003）。CFD还可以模拟流动性问题的多种情况(Gan and Riffat, 2004; Somarathne et
38、 al., 2005; Papakonstantinou et al., 2000; Karimipanah and Awbi, 2002).CFD模型是逼真的模型不需要昂贵的试验方法(Betta et al., 2004; Allocca et al., 2003; Moureh and Flick, 2003)。因而CFD是现在通俗的设计工具为了工程师从不同的规范寻找最优的设计方案,由于高成本的复杂性和条件的限制而通过模拟试验获得的方法(Li and Chow, 2003; Vardy et al., 2003; Katolidoy and Jicha, 2003)。隧道通风系统设计是能深
39、度发展从不同的参数预测，例如车辆光的散射，离子，可见度，空气速度等。(Li and Chow, 2003; Yau et al., 2003; Gehrke et al., 2003).早期的CFD隧道通风系统的模拟大体上集中在紧急情况如着火的情况下(Modic, 2003; Carvel et al., 2001; Casale, 2003)。多数科学家和研究者(Waterson and Lavedrine, 2003; Sigl and Rieker, 2000; Gao et al., 2004; Tajadura et al., 2006)已经做了许多这方面的工作。这篇文章是学习CFD
40、模拟在地铁环境的控制是不能从其他文章或报告研究中得到的。它的本质是计算和模拟在结构成型以前，因为地铁投资建设是巨大的而且建设是要经过上十年的时间。地铁通风是至关重要的因为乘客需要新鲜和高质量的空气(Lowndes et al., 2004; Luo and Roux, 2004)。然后如果有紧急情况出现有计划的通风设计系统可以拯救生命和财产(Chow and Li, 1999; Modic, 2003; Carvel et al., 2001)。紧急情况的特征已经很好的研究，但是已经有一些研究关于在通常的情况下站台的空气分布状态。大的发展和高速的电脑和计算的流动性动力学技术它有可能运用到CFD
41、技术和预言空气的分布状态和优化的地铁通风系统设计的项目。基于在地铁通风系统的人工向导意图，这种研究模拟和分析已经存在的通风系统同时通过专业软件AIRPAK得出天津地铁原先的车站位置需要重建，然后为重建车站找到最佳的通风的项目和结构。2通风系统天津地铁是中国第二个建造的地铁，重建将会适应城市的发展并且希望用于2008年的北京奥运会。现存的车站有八个车站，其总长为7.335km和平均0.932km的间距。由于工程的存款成本，那现存的地铁将继续运营并且车站的重建主要在天津地铁的一号线。尽管天津地铁现存的各种车站有着不同结构和几何结构，西南车站就是最典型的一个。几何模型展示在图符1中。2.1现存的车站
42、结构和早期的通风模型地铁有两条运营线路。西南车站的结构为长宽高74.4m18.7m4.4m一个典型的边台车站。每边只有仅有一个通道（长宽6.4m2.9m）。中间留出的空间是留给乘客等待机车。站台的机械通风是通过两个位于车站末端的喷射的敞口提供空气给火车和车轨。在车站没有机械排气系统，空气的流动是通过隧道的机械扇子和车站的自然通风。2.2. 设计结构和重建车站的通风预计旅客大规模的增加和原先车站体积太小，所以重建设计的地铁结构体系将被设计为，长宽高132m17.438m4.65m并且每边有两个乘客通道。西南车站的设计体积流量为400000 m3/h。其他大多数的现存车站站台高度仅有2.9m那对于
43、设置小导管太矮了。因此早期的设计里，有两个在每边平台末端的网格的通风口提供给站台纵向的新鲜空气和这两个通风口还向火车横向的喷射空气。横向网格通风口纵向设计风速为5.54m/s。每边的横向速度为5.28m/s.在站台下,80个相同风速的网格式通风口(4.62m/s,站台两边个40个)被用于排气是可靠的.3. CFD模拟和优化设计CFD模拟在户内环境的应用是基于能量,质量和动力的不可压缩空气守恒公式,研究采用二平衡空气紊乱能量模型被Launder和Spalding升级后的二平衡紊乱模型.它综合了governing equation在控制体积的重要性和使离散明确的表示在格子上,最后模拟并完成了AIR
44、PAK软件.3.1 前述的简化和假定由于机械通风和火车行驶所带来的风,所以站台上的空气紊乱是短暂和复杂的.除非一些简化和假设能成立,否则那个三维的数学模型就不能表述从而使得结果有分歧.然而为了确保计算结果的可靠性,一些限制的简化和假设不得不被提出来.(1) 最大风速的周期在短暂的过程中是值得注意的.很显然最大风速是在火车停或行驶离开车站这个周期中达到的(Yau et al., 2003; Gehrke et al., 2003),所以周期模拟的最好时间从x=0.0m(见图1)的地方开始并且空气速度正在活塞效应下向另一个点,当火车完全在车站停下来后结束.(定义为一个“拉力-周期”)图1:(2)
45、尽管“拉力-周期”是一个短暂的过程,但是他被简化为一个稳定的过程.(3) 因为那过程被假定为一个稳定的过程,在西南车站“拉力-周期”测试区的瞬时速度被假定为这个测试区的时间平均速度.(4) 体积流动通过“拉力-周期”打入车站决定于这些因素BR(阻碍率,火车穿越面积和隧道穿越面积之比),火车的长度和车站的阻力等等.对于原来的还是新的车站,BR都几乎是一样的.尽管后来的火车长度是原先火车长度的两倍,用于提高活塞活动的体积,同样由于体积的增大使得后来的比原先的火车所受到的阻力也更大了.所以假设原来和新的车站活塞活动体积是一样的,乘客出来是的活动体积也是相等的.基于上述假设,用于现存车站的测量结果可作
46、为预算新的车站的速度边界条件.3.2 原始条件获得了计算的边界条件和模拟,例如空气流动速度和站内温度,按时对西南测量得出的.所有的数据的收集都在一个完全的“拉力-周期”过程中.空气速度的测量是通过多波段的海葵大师热线风速仪,红外线温度计测量车站墙的温度,车站的温度在模拟中被视为恒定不变的.3.2.1 站内温度将站台分为5段并且选择一些典型的位置作为测点.站内温度的分布如表1.我们可以从表1中看到站内所有的温度都在23-25度之间,所有测点有一点点不同,平均温度为24度.所以在CFD计算和模拟中地铁站内墙的温度均为24度.3.2.2 站台上的平均时间风速图1是 测试区的位置和测量点的布局图.数据测量的是包括每个站的瞬时速度(在图1中A-H点),在一个周期中处理为区内的时间平均速度,过道12点的速度用于获得平均流速,车站末端的每个速度用于获得平均活塞活动体积.图2是测量站台区域的纵向风速, 为最大空气流动速度, 为最小空气流动速度, 为空气平均流动速度.图2显示了过道中的最大空气流动速度.在过道中空气流动速度的变化量大约是2.25m/s,最大值标志着过道是最受活塞风效应影响的位置,并且空气流速在D区和E区之后几乎是相等的,这标志着在过道之后活塞风效应已经很难影响空气的平均流速了.表1:表2