CFD Studies

CFD provides numerical solutions to the governing equations of fluid dynamics throughout the desired flow region. It allows for complex problems to be solved without losing the integrity of the problem due to over-simplification. It is this ability to solve large problems that makes CFD an excellent tool for the automotive industry. CFD allows engineers to examine the airflow over an automobile or a particular part such as a wing or hood, and see the aerodynamic effect of changing the geometry of any particular area of the vehicle. Not only does the automotive industry use CFD to study the airflow external to the car, but now also employs CFD in mapping airflow through the engine, and even within the car to predict the behavior of thermal comfort systems and the efficiency of cooling systems (Chandra et. al., 2011).

CFD can be used to even Simulate the Flow over a Golf Ball (Smith, 2011) or to eliminate/ reduce snow accumulation on rear warning lights to improve visibility of the truck by motoring public. (Dinc, 2011). 3D simulation of the through-thickness permeability of knitted fabrics can also be predicted by using FLUENT software package (Mezarcıöz et al, 2014).

Özdemir and Onbaşıoğlu 2004, investigated the flow around a F-4 Phantom II aircraft by means of CFD with Fluent Code by employing Spallart Almaras and Standard k-ε turbulence models. And the results obtained from CFD analyses were compared with the experimental results.

Computational fluid dynamics (CFD) is extensively used in the racing industry to predict the down force and drag racecars would experience at high velocities (Tu et. al., 2008).

Mezarcioz (2006), investigated the 3D turbulent flow around a bus by means of CFD.

Sardar (2010), investigated in his study three-dimensional simulation analysis of a diesel engine using moving dynamic mesh with different turbulence and combustion models, which were k-ε, k-Ω.

Chandra et. al. (2011), conducted a study to improve the shell design of a Formula 1 racecar. 3D CAD model was generated and analyzed with standard and realizable k-ε turbulence models. Some Computational Fluid Dynamic analysis and simulation were done to maximize down force and minimize drag during high speed maneuvers of the race car.

Bayraktar (2012), implemented 1-D and 3-D unsteady CFD based simulation tools in a military ground vehicle design process. Both powertrain cooling and HVAC systems were simulated in various operating conditions on a Computer Cluster using multiple fidelity tools. HVAC system variables are optimized and the simulation results were compared and validated with experimental tests. At the end of the study, it was concluded that, Although 1-D simulation tools provide valuable first prediction about a proposed system, it is observed that analyzing transient behavior of a vehicle thermal system requires input from higher fidelity 3-D CFD computations and sometimes climate tests. Using such input straightens the accuracy

of the computational modeling and create valuable database for future vehicle developments.

Huang and Han (2002), demonstrated the capability of CFD analysis of a passenger compartment soak and cool down simulations. The predictions of accurate airflow velocity and temperature distributions were crucial to the success of the Virtual Thermal Comfort Engineering. The full 3-D CFD analysis of soak and cool down simulations demonstrated an excellent agreement with the available experiment data for a simplified passenger compartment. In comparison with thermocouple measurements, the current transient simulation can accurately predict air temperatures at most locations around an occupant in the passenger compartment.

The project aiming numerically modeling of the flow and thermal processes occurring in a passenger car’s underhood using computational fluid dynamics (CFD) was conducted by Zyl (2006).

A computational study was conducted by Xiao et. al. (2008), in order to characterize the heat transfers in a sedan vehicle underbody and the exhaust system.

Kulkarni et. al. (2012), conducted a study on under hood flow management of heavy commercial vehicle to improve thermal performance. In the study under hood flow management for 25T truck has been carried out by flow analysis by CFD method using commercial software. As a result of that study they improved velocity and mass flow rate of the air passing through the radiator, and engine room of a truck. Since the airflow around the engine was improved, at the end of modifications, heat amount transferred to the driver cabin was decreased and heat rejection on radiator and exhaust manifold increased.

Jalil and Alwan (2007), presented a numerical study of a two-dimensional, turbulent, re-circulating flow within a passenger car cabin with k-ε turbulence model.

Different parameters were considered to illustrate their influences on the flow filed and temperature distribution inside car cabin. These parameters included number and location of the air conditioning system’s inlets inside car cabin, different air temperatures at the inlets, different air velocities at the inlets, different solar intensity during day-time for a certain day of the year, different diffuse solar radiation (variation in the kind of car glass). It was found that the number of inlets inside car

cabin play an important role in determining car air conditioning system efficiency.

Moreover, the air temperature and velocity at inlets played an important role in determining cabin climate. The results were used to enhance the understating of the airflow fields within a road vehicle passenger cabin.

CFD analysis to increase the efficiency of the air-handling unit used at the heating ventilating air conditioning systems were carried out by Bulut et. al. (2011).

Air handling unit consist of chambers. All chambers were modeled using CFD code Fluent. The velocity and static pressure distribution in the chambers were investigated and the parts of the chambers were determined which disturbed the fluid flow and caused higher pressure drop.

Moujaes and Gundavelli (2012), used a three-dimensional computational fluid dynamics model to simulate fluid flow in a duct and its simulated leaks with six different air leak geometries placed respectively on its periphery. The k–ε turbulence model for high Reynolds numbers flows was used for that purpose and the Reynolds numbers were varied to simulate a variety of flow conditions. The computer code was used to produce pressure drop data and leak flow rates across the holes necessary to compute the pressure loss coefficients, as well as to produce flow field and static pressure plots that offer insight into the physics of the flow field. The flow coefficient and pressure exponent were found for different leak geometries by curve fitting the pressure and leak flow data derived from CFD simulations and were compared to available data in the literature.

Corgnati and Perino (2013), tested and evaluated In the their study, the potentialities of advanced computational tools applied to the theoretical analysis of museum indoor environments. In particular, CFD techniques were used to examine and predict the microclimatic characteristics of a case study exhibition hall, located inside an historical building in Turin. The use of CFD software revealed to be particularly suited for the concept phase of the design of an exhibition space and it’s setting, when alternative air distribution strategies have to be evaluated in order to identify the one, which ensures the best microclimate quality.

One of the most widely used turbulence models is the two-equation model of kinetic energy, k, and its dissipation rate ε. This model has been applied by most

investigators, who studied the numerical solution of airflow in rooms (Awbi and Setrak, 1986), (Patankar, 1980).

Kaya and Karagoz (2007), investigated the suitability of various turbulence models in highly complex swirling flows, which occur in tangential inlet cyclones.

Three-dimensional steady governing equations for the incompressible, turbulent flow inside the cyclone were solved numerically by using Fluent CFD code, under certain boundary conditions. Different turbulence models and wall functions were tested to get axial and tangential velocity profiles, pressure drop and turbulent quantities.

Predicted results were compared with the experimental and numerical values given in the literature. Results obtained from the numerical tests have demonstrated that the key to the success of CFD lies with the accurate description of the turbulent behavior of the flow.

The airflow in a cold-region tunnel using standard k-ε turbulence model was studied by Tan et. al. (2013). Comparisons of experimental data and CFD results using standard k-ε turbulence model were presented. Comparison of the results indicated that the proposed model and simulation method are efficient and Standard k-ε turbulence model can be used to simulate in tunnel flows.

Salvador (2013), investigated the internal flow and cavitations phenomenon in diesel injector nozzles by means of CFD. Due to high Reynolds numbers, turbulence effects have been taken into account by RANS methods by employing k-ε RNG turbulence model. Its validation against experimental data has demonstrated a great accuracy of the code in terms of mass flow, momentum flux and effective velocity at typical operating conditions of diesel engines.

With the current study, temperature distribution underneath a coach under different working conditions, which is the first study in the literature, would be determined. The gap of cooling load calculation for moving media will be filled with the detail cooling load calculations. Design of a closed cross-section, distinct air channel is the first study to be conducted, applied and experimented in a full size of a coach. As can be seen from the mentioned studies, the number of study conducted to determine the temperature distribution inside of a coach in cooling mode is nearly

zero. At the end of this study temperature distribution with and with out the distinct air channel will be determined for a 12-m coach.

3. MATERIAL AND METHODS