ABSTRACT This study is aimed to investigate the transport of air pollutants and traffic flow in Chungcheng and Cross-Harbor Tunnels in Kaohsiung City. The work includes road measurements and three-dimensional numerical modeling. This article reports the first part of the work concerning measurement results. The items on road-side investigation include traffic flow rate traffic, speed, travel time and vehicle catergory. The air pollutants being sampled and analyzed in the tunnels are carbon monoxide (CO), sulfur dioxide (SO2), nitrogen oxides (NOX) and total hydrocarbon (THC). The road-side investigations show that the major vehicles in Chungcheng Tunnel are passenger cars, the next are small trucks, and the minor are large trucks. The peak hours are at 10:30 ¡V 11:30 in the morning and 15:30 ¡V 17:30 at afternoon with average traffic flow rate in 250 ¡V 350 No./hr. The major vehicles in Cross-Harbor Tunnel are motorcycles, the next are passenger cars, large trucks and small trucks. Traffic flow rate at morning peak hours of 7:00 ¡V 8:00 are 1,800 and 1,000 No./hr for motorcycles and passenger cars, respectively, and are below 800 No./hr for the large and small trucks. Results of air pollutants analysis show that CO in Cross-Harbor Tunnel is about as three times as that of Chungcheng Tunnel due to high motorcycle flow rate in Cross-Harbor Tunnel. The maximum concentration of NOX was about 500 ppb for Cross-Harbor Tunnel and was about 1,000 ppb for Chungcheng Tunnel during the study period, suggesting that cars and trucks are the major emission sources of NOX. The transport of air flow and gaseous pollutants downstream (or to the tunnel exit) is mainly done by tunnel fans and piston effect of moving vehicles in order to decrease pollutants concentrations inside the tunnel. The mechanism is affected by fan number and flow rate, traffic flow rate, traffic speed and net tunnel aspect ratio. Results in two tunnels show that CO and NOX both increase with increasing downstream distance, but are not always so for SO2 and THC. Whether other mechanisms such as absorption of SO2 and THC on tunnel walls or sink and absorption on tunnel floor due to being heavier than air affect distributions of SO2 and THC remains further investigations.

ABSTRACT Three-dimensional modeling on the aerodynamics of airflow and diffusion of air pollutants in a longitudinal-ventilated traffic tunnel was carried out. The model takes ventilation fans, traffic flow rate, speed, emission factor and piston effect of moving vehicles into consideration. Turbulent flow and dispersion of gaseous pollutants in road tunnels were solved numerically using the finite volume method. Traffic emissions were accordingly modeled as banded line sources along the tunnel floor. The effects of fan ventilation, roughness and piston effect of moving vehicles on the air flow and pollutant dilution are examined. Concentrations of gaseous pollutants CO, NOX, SO2 and THC (total hydrocarbons) at three axial locations in the tunnel, together with traffic flow rate, traffic speed and types of vehicle were measured. Case study was conducted on the Cross-Harbor Tunnel and the Chungcheng Tunnel in which on-site measurements of traffic flow were also conducted concurrently to provide traffic emission data to the tunnel environment for numerical simulation and comparisons. The aim of this study was to understand the spatial variation of air pollutants generated by traffic emissions and evaluation of ventilation performance and piston effect of moving vehicles on dilution of air pollutants in these tunnels. The results show that the major emission sources of CO are passenger cars and motorcycles, while major emission sources of NOx are trucks. Pollutants convect downstream with the wind generated either by longitudinal ventilation fans and/or moving vehicles, thus causing increasing pollutants concentrations with increasing downstream distance. The piston effect of moving vehicle alone can provide 64% ~ 85% increase of wind speed in Chungchen Tunnel and 13% ~ 20% in Cross-Harbor Tunnel. When all fans are on, showing 185% ~ 328% and 120% ~ 182% increases in Chungchen Tunnel and Cross-Harbor Tunnel, respectively. The piston effect of moving vehicle alone can provide 14% ~ 32% dilution of air pollutants in the Chungcheng Tunnel. The piston effect of moving vehicles is compounded with ventilation fans, showing a 47% ~ 66% dilution effect when all fans are on. For the Cross-Harbor Tunnel, the piston effect of moving vehicle alone can provide 9% ~ 23% dilution of air pollutants and 36% ~ 74% dilution effect when all fans are on. The results reveal that cross-sectional concentrations are non-uniformly distributed and that concentrations rise with downstream distance. When all fans were turned off, wind speed in tunnels would be considered as constant, and gaseous pollutants concentration agree with linearly alone the tunnel.

Air velocities induced by underground vehicles in complex metro systems are obtained using artificial neural networks. Complex tunnel shaft-systems with any number of tunnels and shafts and with most of the practically possible geometries encountered in underground structures can be simulated with the proposed method. A single neural network, of type feed-forward back propagation, with a single hidden layer is trained for modelling a single tunnel segment. Train and tunnel parameters that have influence on the vehicle induced flow characteristics are used together to obtain non-dimensional input and target parameters. First input parameter is the major head loss coefficient of tunnel, (L/D)_Tunnel. Blockage ratio A_Train/A_Tunnel and train aspect ratio (D/L)_Train are selected to be non-dimensional input parameters to represent the system geometry. As the final input parameter, skin friction coefficient of the train, f_Train drag coefficient of the train, C_D / frontal area of the train, A_Train and lateral area of the train, A_Lateral are combined into a single overall drag coefficient based on the train frontal area. Non-dimensional V_Air/V_Train speed ratio is selected to be the target parameter. Using maximum air velocity predicted by the trained neural network together with non dimensional system parameters and time, an additional neural network is trained for predicting the deceleration of air in case of train stoppage within the tunnel system and departure of the train from the system. A simulation tool for predicting time dependent velocity profile of air in metro systems is developed with the trained neural networks.

This study separated two parts: PART ¢¹ Meteorologically adjusted trends of ozone Since meteorological changes strongly affect ambient ozone concentrations, trends in concentrations of ozone upon the adjustment of meteorological variations are important of evaluating emission reduction efforts. This work is to study meteorological effects on the long-term trends of ozone concentration using a multi-variable additive model in Kaohsiung. The long-term trends of ozone concentration were analyzed using the Holland model (without meteorological-adjusted) and the robust MM Regression model (with meteorological-adjusted) based on the data of eight EPA air quality stations from 1997 to 2006 in Kaohsiung area. According to the result of the simulation, the simulated value of the robust MM-Regression model present more valid than the Holland model.The simulated results show that the long-term ozone concentration increases at 13.84% (or 13.06%) monthly (or annually) after meteorological adjustments, less than at 26.10% (or 23.80%) without meteorological adjustments in Kaohsiung county. The simulated results show that the long-term ozone concentration increases at 9.01% (or 6.88%) monthly (or annually) after meteorological adjustments, less than at 22.01% (or 19.67%) without meteorological adjustments in Kaohsiung city. Wind speed, duration of sunshine and pressure are the three dominant factors that influence the ground-level ozone levels in Kaohsiung area. PART ¢º Dispersion of air pollutants in the Hsuehshan Tunnel Concentrations of carbon monoxide (CO) and nitrogen oxides (NOx) were measured from November 14 ¡V 17 2008 in a cross-mountain Hsuehshan traffic tunnel stretching 12.9 km and containing eastward and westward channels. Air pollutants of CO (carbon monoxide) and NOx (nitrogen oxides) will be monitored at the inlet, outlet and vertical shafts of the tunnel. Meanwhile, numerical simulation of three-dimensional turbulent flow will be performed using STAR-CD software. Traffic and pollutant concentrations during the weekends exceeded those during the weekdays. Measured concentrations of CO at the two tunnel outlets (14.5 ¡V 22.8 ppm) were approximately three times higher than those at the two tunnel inlets (3.2 ¡V 7.3 ppm), while concentrations of NOx at the two tunnel outlets (1.9 ¡V 2.9 ppm) were approximately four to five times higher than those at the two tunnel inlets (0.3 ¡V 0.8 ppm). The outlet of vertical draft 2 had the highest pollutant concentrations (CO = 12.3 ppm; NOx = 1.9 ppm), followed by vertical drafts 1 and 3. Three-dimensional turbulence modeling results indicate that airflow in the tunnel was primarily driven by the combined effects of axial fans and vehicles. Results of this study demonstrate that simulated pollutant concentrations increase downstream and are vertically stratified, due to tailpipe exhausts close to tunnel floor. Simulations agreed fairly well with measurements.

Un fluide porté à une température et pression supérieures à celles du point critique est communément appelé fluide supercritique. Ce fluide possède des propriétés particulièrement intéressantes à cheval entre celles des gaz et celle des liquides. En effet, la masse volumique d’un fluide supercritique est proche de celle d’un liquide tandis que sa viscosité est proche de celle d’un gaz. Une des caractéristiques particulières de ces fluides quand ils s’approchent du point critique est que plusieurs des propriétés thermo-physiques montrent un comportement singulier (compressibilité divergente, diffusivité thermique évanescente etc). Dans ce travail, un modèle mathématique basé sur les équations de Navier-Stokes couplées à celle de l’énergie est proposé afin d’étudier les écoulements de ces fluides très proches de leur point critique. La validation du modèle a été effectuée sur un problème de propagation d’onde acoustique dans l'eau. Nous avons ainsi observé que des solutions précises avec des schémas implicites pour des systèmes non linéaires sont possibles avec des nombres de Courant élevés. L’étude des écoulements dans des fluides supercritiques, lorsqu'ils sont assujettis à une trempe thermique et à une vibration simultanées ont montré que de telles conditions pouvaient conduire à la formation d’instabilités thermo-vibrationnelles, en particulier les instabilités de Rayleigh-vibrationnelles et paramétriques. Les simulations numériques nous ont permis de relever deux phénomènes particulièrement surprenants : (i) la température du fluide à l’intérieur du domaine devient inférieure à la trempe de température imposée à la frontière et (ii) une oscillation des doigts d’instabilité apparaît dans la couche limite thermique dans la direction de la vibration. Dans le cas des fluides sous le point critique (cas diphasique), le modèle compressible développé est couplé à un de champ de phase (“phase field”) dans les conditions isothermes. Des cas tests élémentaires ont été considérés avec succès. Une discussion est proposée afin d’étendre le modèle dans le cas d’une transition continue du régime supercritique au régime sous-critique et vice-versa. / A fluid, in addition to its liquid and gas phase, is known to exist in another phase, wherein the fluid inherits some properties of both the phases. Such a fluid is called a supercritical fluid and the conditions (pressure and temperature) beyond which the fluid exists in this state is called the critical point. One of the peculiar feature of the fluids near the critical point is that the various thermo-physical properties show a singular behavior, such as diverging compressibility, vanishing thermal diffusivity etc. The flow behavior near the critical point leads to intriguing flow features ascribed to the strong thermo-mechanical coupling whose in-depth investigation can be limited by experimental constraints especially during a continuous transition from supercritical to subcritical regime. The current work focuses on analyzing the flow behavior in near-critical fluids with prime focus on supercritical fluids. This is achieved by developing a mathematical and numerical model which is followed by the validation study and error analysis of the numerical scheme wherein unusual behavior of the Courant number is observed. Subsequently, the flow behavior of supercritical fluid is studied when simultaneously subjected to thermal quench and vibration, mainly Rayleigh-vibrational and parametric instabilities, their physical mechanism and various parameters affecting them. In addition, two captivating phenomena, firstly where the temperature of the fluid region drops below the imposed boundary condition and secondly, the see-saw motion of the thermal boundary layer are observed and physical explanations are provided. In order to investigate the flow dynamics in subcritical regime, phase-field modelling approach is explored for isothermal conditions. The model is examined for elementary test cases illustrating the feasibility to extend the model for a continuous transition from supercritical to subcritical regime.