带出口匝道城市隧道通风特性比尺模型试验
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摘要
通风特性是影响城市隧道内外环境的关键,为深入研究带出口匝道城市隧道风量及风量分配的变化规律,获得隧道总风量及分流比的高效控制策略,基于相似理论,设计并搭建总长为38 m的1/20带匝道隧道通风比尺模型,研制可实现8台模型风机联动的变频控制系统、16个断面的速度及压力数据的实时测量与自动采集系统(该系统在风速u≥2.5 m·s~(-1)时,比尺模型同步满足阻力、惯性力和压力相似准则),进行各通风段射流升压力变化对隧道内风量及风量分配的影响试验。结果表明:隧道主线通风段与匝道通风段风量存在联动耦合效应,当调节某通风段射流升压力时,该通风段及与之串联的通风段风量均随着射流升压力的增大而增大,与之并联的通风段,风量随射流升压力的增大而减小;总风量和分流比分别是影响城市隧道内、外环境的关键因素,调节分流前主线段射流升压力不改变分流比,但对控制隧道总风量变化最为高效,单位射流升压力作用下的总风量变化幅度达1.43%·(N·m~(-2))~(-1);调节分流后主线段或匝道段射流升压力对隧道总风量的影响有限,但能有效控制分流比,单位射流升压力作用下的分流比增幅分别为(-4.43,4.16)%·(N·m~(-2))~(-1);利用分流前主线段的射流风机控制隧道内环境,利用分流后主线段或匝道段的射流风机控制隧道外环境,是最为高效的通风控制方法。
Ventilation characteristics are key factors that affect the inside and outside environment of urban tunnels. The objective of this study was to determine the changing trends of air flux and air flux distribution in tunnels with off-ramps, thus formulating an effective control strategy for the total air flux and diversion ratio. A 38 m-long, 1/20-scale model of a tunnel with a ramp was designed and built on the basis of similarity theory. A frequency-conversion control system and real-time automatic measurement and acquisition system were developed to carry out the synchronous control of eight model fans and automatic acquisition of velocity and pressure data of sixteen tunnel sections. When the wind speed in the model tunnel was greater than 2.5 m·s~(-1), it could synchronously satisfy the similarity criterion for resistance, inertial force, and pressure. The test system of the tunnel ventilation scale model was used to analyze the influence of the changing jet-flow pressurization in a single or multiple ventilation section on the air flux and diversion ratio inside the tunnel. According to the test results, an interactional coupling effect of air flux exists between the ramp and the main tunnel. As the jet-flow pressurization in a certain ventilation section increases, the air flux of the ventilation sections connected to it in series increases as well, whereas that of the ventilation sections connected to it in parallel decreases. The total air flux and diversion ratio are both key factors affecting the inside and outside environment of urban tunnels. The adjustment of the jet-flow pressurization at the main line before the diversion does not change the diversion ratio, however it is highly efficient in controlling the total air flux, with the change in total air flux being 1.43 %·(N·m~(-2))~(-1) per unit rise in pressure. The adjustment of the jet-flow pressurization at the main line after the diversion or ramp has limited influence on the total air flux, yet it is effective in controlling the diversion ratio, with the change in the diversion ratio being-4.43%·(N·m~(-2))~(-1) by adjusting the jet-flow pressurization at the main line after the diversion and 4.16%·(N·m~(-2))~(-1) by adjusting the jet-flow pressurization at the ramp, per unit rise in pressure. For urban tunnels with an off-ramp, the most efficient method for ventilation control is to control the inside environment of urban tunnels by a jet fan at the main line before the diversion, and the outside environment by a jet fan at the main line after the diversion or ramp.
Ventilation characteristics are key factors that affect the inside and outside environment of urban tunnels. The objective of this study was to determine the changing trends of air flux and air flux distribution in tunnels with off-ramps, thus formulating an effective control strategy for the total air flux and diversion ratio. A 38 m-long, 1/20-scale model of a tunnel with a ramp was designed and built on the basis of similarity theory. A frequency-conversion control system and real-time automatic measurement and acquisition system were developed to carry out the synchronous control of eight model fans and automatic acquisition of velocity and pressure data of sixteen tunnel sections. When the wind speed in the model tunnel was greater than 2.5 m·s~(-1), it could synchronously satisfy the similarity criterion for resistance, inertial force, and pressure. The test system of the tunnel ventilation scale model was used to analyze the influence of the changing jet-flow pressurization in a single or multiple ventilation section on the air flux and diversion ratio inside the tunnel. According to the test results, an interactional coupling effect of air flux exists between the ramp and the main tunnel. As the jet-flow pressurization in a certain ventilation section increases, the air flux of the ventilation sections connected to it in series increases as well, whereas that of the ventilation sections connected to it in parallel decreases. The total air flux and diversion ratio are both key factors affecting the inside and outside environment of urban tunnels. The adjustment of the jet-flow pressurization at the main line before the diversion does not change the diversion ratio, however it is highly efficient in controlling the total air flux, with the change in total air flux being 1.43 %·(N·m~(-2))~(-1) per unit rise in pressure. The adjustment of the jet-flow pressurization at the main line after the diversion or ramp has limited influence on the total air flux, yet it is effective in controlling the diversion ratio, with the change in the diversion ratio being-4.43%·(N·m~(-2))~(-1) by adjusting the jet-flow pressurization at the main line after the diversion and 4.16%·(N·m~(-2))~(-1) by adjusting the jet-flow pressurization at the ramp, per unit rise in pressure. For urban tunnels with an off-ramp, the most efficient method for ventilation control is to control the inside environment of urban tunnels by a jet fan at the main line before the diversion, and the outside environment by a jet fan at the main line after the diversion or ramp.
引文
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[2] 李俊梅,许鹏,李炎锋,等.坡度对隧道拱顶烟气最高温度影响的数值模拟与实验研究[J].北京工业大学学报,2014,40(5):707-713.LI Jun-mei,XU Peng,LI Yan-feng,et al.Numerical Simulation and Experimental Studies on the Effect of Slope on the Maximum Smoke Temperature Under the Ceiling in Tunnel Fires [J].Journal of Beijing University of Technology,2014,40 (5):707-713.
[3] DU T,YANG D,PENG S,et al.A Method for Design of Smoke Control of Urban Traffic Link Tunnel (UTLT) Using Longitudinal Ventilation [J].Tunnelling and Underground Space Technology,2015,48:35-42.
[4] LI J,LIU S,LU Y,et al.Experimental Study of Smoke Spread in Titled Urban Traffic Tunnels Fires [J].Procedia Engineering,2012,45 (7):690-694.
[5] El-FADEL M,HASHISHO Z.Vehicular Emissions and Air Quality Assessment in Roadway Tunnels:The Salim Slam Tunnel [J].Transportation Research Part D,2000,5 (5):355-372.
[6] HOEK G,KRISHNAN R M,BEELEN R,et al.Long-term Air Pollution Exposure and Cardio-respiratory Mortality:A Review [J].Environmental Health a Global Access Science Source,2013,12 (1):43-57.
[7] RAASCHOUNIELSEN O,ANDERSEN Z J,JENSEN S S,et al.Traffic Air Pollution and Mortality from Cardiovascular Disease and All Causes:A Danish Cohort Study [J].Environmental Health a Global Access Science Source,2012,11 (1):60-67.
[8] VEGA M G.Numerical 3D Simulation of a Longitudinal Ventilation System:Memorial Tunnel Case [J].Tunnelling & Underground Space Technology Incorporating Trenchless Technology Research,2008,23 (5):539-551.
[9] MAELE K V,MERCI B.Application of RANS and LES Field Simulations to Predict the Critical Ventilation Velocity in Longitudinally Ventilated Horizontal Tunnels [J].Fire Safety Journal,2008,43 (8):598-609.
[10] 阳东,赵成梅.热压与风机动力共同作用下多分支隧道内排烟气流的多解性[J].土木建筑与环境工程,2015,37(1):1-6.YAND Dong,ZHAO Cheng-mei.Multiple Steady States of Exhaust Airflow in a Multi-branch Tunnel with the Combined Effects of Buoyancy and Fan Power [J].Journal of Civil,Architectural & Environmental Engineering,2015,37 (1):1-6.
[11] MENG Q,QU X,WANG X,et al.Quantitative Risk Assessment Modeling for Nonhomogeneous Urban Road Tunnels [J].Risk Analysis,2011,31 (3):382-403.
[12] 李炎锋,付成云,李俊梅,等.城市交通隧道坡度对火灾烟气扩散影响研究[J].中国安全生产科学技术,2011,7(5):10-15.LI Yan-feng,FU Cheng-yun,LI Jun-mei,et al.Study on the Slope Effect on Smoke Propagation in Urban Traffic Tunnel [J].Journal of Safety Science and Technology,2011,7 (5):10-15.
[13] 李术才,王汉鹏,郑学芬.分岔隧道稳定性分析及施工优化研究[J].岩石力学与工程学报,2008,27(3):447-457.LI Shu-cai,WANG Han-peng,ZHENG Xue-fen.Forked Tunnel Stability Analysis and Its Construction Optimization Research [J].Chinese Journal of Rock Mechanics and Engineering,2008,27 (3):447-457.
[14] 周栋梁,邹金锋.岩溶区分岔隧道底板的安全厚度[J].中南大学学报:自然科学版,2015,46(5):1886-1892.ZHOU Dong-liang,ZOU Jin-feng.Safe Thickness of Floor of Forked Tunnel in Karst Areas [J].Journal of Central South University:Science and Technology,2015,46 (5):1886-1892.
[15] 丁文其,郑康成,金威.某深埋分岔隧道空间荷载结构计算方法[J].中国公路学报,2016,29(2):90-97.DING Wen-qi,ZHENG Kang-cheng,JIN Wei.Spatial Load-structure Calculation Method for a Deep Forked Tunnel [J].China Journal of Highway and Transport,2016,29 (2):90-97.
[16] FERKL L,MEINSMA G.Finding Optimal Ventilation Control for Highway Tunnels [J].Tunnelling and Underground Space Technology,2007,22 (2):222-229.
[17] 吴珂,朱凯,谭真,等.城市隧道纵向通风延迟效应的机理研究及影响因素分析[J].现代隧道技术,2014,51(5):139-144.WU Ke,ZHU Kai,TAN Zhen,et al.On the Mechanism and Influence of the Delayed Effect of Longitudinal Ventilation in Urban Tunnels [J].Modern Tunnelling Technology,2014,51 (5):139-144.
[18] MA C,JIANG D,YUE X.Intelligent Model of Urban Road Tunnel Ventilation System Based on Multi-Level Neural Network [C] // IEEE.Pacific-Asia Conference on Circuits,Communications & Systems.New York:IEEE,2009:636-639.
[19] HRBCEK J,SPALEK J,SIMAK V.Process Model and Implementation the Multivariable Model Predictive Control to Ventilation System [C] // IEEE.2010 IEEE 8th International Symposium on Applied Machine Intelligence and Informatics (SAMI).New York:IEEE,2010:211-214.
[20] LI Y,LING L,CHEN J.Combined Grey Prediction Fuzzy Control Law with Application to Road Tunnel Ventilation System [J].Journal of Applied Research & Technology,2015,13 (2):313-320.
[21] KARAKAS E.The Control of Highway Tunnel Ventilation Using Fuzzy Logic [J].Engineering Applications of Artificial Intelligence,2003,16 (7/8):717-721.
[22] DU P,LUO X,DU P,et al.The Research of Urban Road Tunnel Longitudinal Ventilation Control Based on RBF Neural Network [C] // IEEE.2010 Second IITA International Conference on Geoscience and Remote Sensing.New York:IEEE,2010:85-87.
[23] WU K,YANG Q,KANG C,et al.Adaptive Critic Design Based Control of Tunnel Ventilation System with Variable Jet Speed [J].Journal of Signal Processing Systems,2016,53:1-10.
[24] CHUNG C,CHUNG P.A Numerical and Experimental Study of Pollutant Dispersion in a Traffic Tunnel [J].Environmental Monitoring and Assessment,2007,130 (1/2/3):289-299.
[25] SAMBOLEK M.Model Testing of Road Tunnel Ventilation in Normal Traffic Conditions [J].Engineering Structures,2004,26 (12):1705-1711.
[26] WANG F,WANG M,He S,et al.Computational Study of Effects of Jet Fans on the Ventilation of a Highway Curved Tunnel [J].Tunnelling and Underground Space Technology,2010,25 (4):382-390.
[27] WANG F,WANG M,HE S,et al.Computational Study of Effects of Traffic Force on the Ventilation in Highway Curved Tunnels [J].Tunnelling and Underground Space Technology,2011,26 (3):481-489.
[28] TAN X,CHEN W,DAI Y,et al.Experimental Research on the Mixture Mechanism of Polluted and Fresh Air at the Portal of Small-space Road Tunnels [J].Tunnelling and Underground Space Technology,2015,50:118-128.
[29] 方磊,谢永利,杨晓华.公路隧道竖井送排式通风送风口角度优化模型[J].长安大学学报:自然科学版,2009,29(4):69-72.FANG Lei,XIE Yong-li,YANG Xiao-hua.Optimized Model of Air Supply Outlet Angle in Highway Tunnel Blowing and Exhausting Longitudinal Ventilation System [J].Journal of Chang'an University:Natural Science Edition,2009,29 (4):69-72.
[30] LI Q,CHEN C,DENG Y,et al.Influence of Traffic Force on Pollutant Dispersion of CO,NO and Particle Matter (PM 2.5) Measured in an Urban Tunnel in Changsha,China [J].Tunnelling and Underground Space Technology,2015,49:400-407.
[31] 陈玉远.城市公路隧道多匝道通风系统计算方法的探讨[J].现代隧道技术,2011,48(5):97-100.CHEN Yu-yuan.Discussion of Calculation Method for Multiple-ramp Ventilation Systems in Urban Highway Tunnels [J].Modern Tunnelling Technology,2011,48 (5):97-100.
[32] CASCETTA F,MUSTO M,ROTONDO G.Innovative Experimental Reduced Scale Model of Road Tunnel Equipped with Realistic Longitudinal Ventilation System [J].Tunnelling and Underground Space Technology,2016,52:85-98.
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