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Presented in this paper is a procedure to develop a high fidelity quasi steady state aerodynamic model for use in race car vehicle dynamic simulations and its application in a race vehicle multi-body full lap simulation. Developed to fit quasi steady state (QSS) wind tunnel data, the aerodynamic model is regressed against three independent variables: front ground clearance, rear ride height, and yaw angle. An initial dual range model is presented and then further refined to reduce the model complexity while maintaining a high level of predictive accuracy. The model complexity reduction decreases the required amount of wind tunnel data thereby reducing wind tunnel testing time and cost. The quasi steady state aerodynamic model for the pitch moment degree of freedom is systematically developed in this paper. This procedure is extended to the other five aerodynamic degrees of freedom to develop a complete, high fidelity, six degree of freedom quasi steady state aerodynamic model.

Tire aerodynamics has long been viewed as a critical area in the ongoing research on vehicle drag reduction as it is a significant contributor to the overall automotive parasitic drag. Previous wind-tunnel experiments have revealed that the flow over a rotating wheel is a very complex phenomenon. This complexity arises from the tire-ground contact patch, various points of flow separation due to the wheel geometry, and the effects of wheel rotation. These aspects make the numerical simulation of this type of flow rather challenging. Existing literature shows a number of ways, like sliding mesh, by which to simulate the flow over an isolated wheel, but the problem of finding an accurate yet cost-effective solution still remains elusive. The current paper attempts to investigate the different methodologies to emulate the wheel motion. In addition, the paper will address the influence of mesh parameters and solver setting dependency of the solution.

Cost benefit and teraflop restrictions imposed by racing sanctioning bodies make steady-state RANS CFD simulation a widely accepted first approximation tool for aerodynamics evaluations in motorsports, in spite of its limitations. Research involving generic and simplified vehicle bodies has shown that the veracity of aerodynamic CFD predictions strongly depends on the turbulence model being used. Also, the ability of a turbulence model to accurately predict aerodynamic characteristics can be vehicle shape dependent as well. Modifications to the turbulence model coefficients in some of the models have the potential to improve the predictive capability for a particular vehicle shape. This paper presents a systematic study of turbulence modeling effects on the prediction of aerodynamic characteristics of a NASCAR Gen-6 Cup racecar. Steady-state RANS simulations are completed using a commercial CFD package, STAR-CCM+, from CD-Adapco.

There have been claims that the rear wing on the NASCAR Car of Tomorrow (COT) race car causes lift in the condition where the car spins during a crash and is traveling backwards down the track at high speed [1,2]. When enough lift is generated, the race car can lose control and even become airborne. At least in part, to address this concern, a new rear spoiler was designed by NASCAR to replace the wing and prevent this dangerous condition. This paper looks at the flow characteristics of both the rear wing and the new spoiler using particle image velocimetry (PIV) to provide qualitative analysis as well as flow visualization. In particular, the interaction of these downforce devices with "roof flaps" (which are designed to prevent lift) is explored. These experiments are done in a continuous flow water tunnel having a cross section of 1.0 m2 using a simplified 10% scale model COT body with either a wing or spoiler attached.

For flows around a tire rotating over a ground plane, the Reynolds number is probably the most important parameter influencing the transition mechanism leading to flow separation from the tire surface, as it determines the viscous response of the boundary layer in the vortex-wall interaction. The present work investigates the effects of Reynolds number on an isolated tire model using a commercial Computational Fluid Dynamics (CFD) code. It validates the baseline simulation for this purpose against the Particle Image Velocimetry (PIV) data from Stanford University got using a Toyota Formula 1 race car tire model. Time-resolved velocity fields and vortex structures from the PIV data are used to correlate local and global flow phenomena to identify unsteady boundary-layer separation and the subsequent flow structures. The study will highlight the pre to post critical flow regimes where the aero coefficients and vortex structure will be studied.

When Computational Fluid Dynamics (CFD) is used in the development of road vehicles for passenger and performance use, the fidelity and numerical accuracy of the simulation are paramount as manufacturers strive to optimize the vehicle down to the single aerodynamic count. While much research has been performed on how the choices of simulation model or grid size affects the simulation results, very little has been done to investigate how the spatial decomposition of the domain amongst different nodes of a high-performance computing unit (HPC) influences the results of the simulation. As simulations grow larger, more nodes are required to reduce the simulation time, however in most commercial software this introduces a new form of error due to the accumulation of round-off errors created in the intra-node communication schemes used during iterations.

Tire modeling has been an area of major research in automotive industries as the tires cause approximately 25% of vehicle drag. With the fast-paced growth of computational resources, Computational Fluid Dynamics (CFD) has evolved as an effective tool for aerodynamic design and development in the automotive industry. One of the main challenges in the simulation of the aerodynamics of tires is the lack of a detailed and accurate experimental setup with which to correlate. In this study, the focus is on the prediction of the aerodynamics associated with an isolated rotating Formula 1 tire and brake assembly. Literature has indicated differing mechanisms explaining the dominant features such as the wake structures and unsteadiness. Limited work has been published on the aerodynamics of a realistic tire geometry with specific emphasis on advanced turbulence closures such as the Detached Eddy Simulation (DES).

A multi-position 4-stroke piston engine utilizing a novel rotary valve system was developed for handheld outdoor power equipment applications such as chainsaws, brush cutters, and string trimmers. The purpose of the project was to create a low-emission 4-stroke engine with 2-stroke performance levels including high RPM limits and power output. This was accomplished using a rotary valve system in lieu of the typical poppet valves of traditional 4-stroke engines. The prototype was then incorporated into a functional product for overall performance evaluation. Three prototype 45cc rotary valve engines were developed and tested in both real-world usage and on laboratory engine dynamometers to measure power output and emissions levels.

Turbulence modeling and the specific boundary conditions are among the two major simulation physics setup variables that affect the prediction veracity of a CFD simulation. The existing literature is rich with studies investigating the effect of the inlet boundary conditions on the predictability of a CFD simulation, and it is recognized that the turbulence characteristics of the freestream flow, viz. the turbulence intensity and length scale, can impact the simulation results significantly, even with the same turbulence model. However, none of these studies encompasses the significance of these two boundary specifications on the CFD analysis of a realistic racecar model. Against this backdrop, the purpose of this study is to systematically investigate the effect of different freestream turbulence specifications on the CFD predictions of the aerodynamic characteristics of a latest generation NASCAR Cup racecar model.

This paper discusses a realistic approach of simulating a generic idealized car model (Ahmed body) moving in close proximity to a Side-wall using transient CFD. This phenomenon is very important in motorsports where racing very close to the safety barrier is very common. Driving in close proximity to a Side-wall alters the aerodynamic characteristics of the vehicle significantly, however, only a handful of published work exists in this area. Additionally, the experimental studies conducted in the past suffer from certain inadequacies especially in properly emulating the Side-wall, which cast some uncertainty as to their applicability to the real world. As such, the present study attempted to imitate the real world flow phenomenon by taking a non-traditional CFD approach in which the body is translated relative to the stationary surrounding fluid and Side-wall instead of the classical method of flowing air over a stationary object.

Computational Fluid Dynamics (CFD) tools play an important role in the early stages of vehicle aerothermal development. Arguably, the RANS (Reynolds Averaged Navier-Stokes) approaches are most widely used in industry due to their acceptable accuracy with affordable computational cost and faster turnaround time. In many automotive flows, RANS models cannot very accurately capture the absolute flow features or even the integral force coefficients. In spite of this, the RANS based CFD prediction results can conveniently be used to assess the magnitude and direction of a trend. However, even for such purposes, notable disagreements often exist between the flow features predicted by different RANS turbulence models. Whilst comparisons of different RANS models for various applications are abundant in literature, such evaluations on full-car models are limited, especially the evaluations of the cooling airflow inside the underhood compartment.

The radiator is the key component of a vehicle’s cooling system. The cooling effectiveness of a radiator largely depends on the flow of fresh air through it. Thus, at high vehicle speeds, the mass flow rate and flow-distribution or flow-uniformity over the radiator surface are the major operating parameters influencing the performance of a radiator. Additionally, the mass of air coming from the front grille plays an important role on the total drag of the vehicle. This paper presents computational studies aiming at improving simultaneously the efficiency of a radiator and reducing the total drag of the vehicle; this is achieved using passive aerodynamic devices that alter the flow pattern approaching the radiator. The vehicle model considered is a Hyundai Veloster and all analyses were carried out using a commercial CFD code Star-CCM+ version 10.04 by CD-adapco.

Faster turn-around times and cost-effectiveness make the Reynolds Averaged Navier-Stokes (RANS) simulation approach still a widely utilized tool in racecar aerodynamic development, an industry where a large volume of simulations and short development cycles are constantly demanded. However, a well-known flaw of the RANS methodology is its inability to properly characterize the separated and wake flow associated with complex automotive geometries using the existing turbulence models. Experience suggests that this limitation cannot be overcome by simply refining the meshing schemes alone. Some earlier researches have shown that the closure coefficients involved in the RANS turbulence modeling transport equations most times influence the simulation prediction results.

The aerodynamic design optimization of a ground vehicle highly depends on the wake region behind it. Vehicle's wake and its instability have a major contribution to the drag, lift, and side forces experienced by the vehicle. In this paper, we investigate numerically the dynamic characteristics of the wake downstream of a realistic generic car model, DrivAer Fastback, at a Reynolds number of 4.8 million based on the free stream velocity and wheel-base as the characteristic velocity and length scales, respectively. Two methods, Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) are applied to symmetric the 2D plane, taken at the centerline of the geometry, to decompose the unsteady wake to its major dynamic modes. We simulated the flow field using a validated IDDES approach and then applied POD and DMD on the streamwise velocity field.

Racecar aerodynamic development demands rapid and incremental development cycles using extensive and well-correlated simulation data. The successful implementation of such a process is a major performance differentiator between race teams. Reynolds Averaged Navier-Stokes (RANS) simulations are an industry-wide tool of choice for their relatively quick turn-around times and cost-effectiveness. A limitation of RANS simulation is an inability to fully resolve flow separation and wake structures of the racecar geometry thereby reducing the accuracy of simulation and the confidence in incremental development work. However, race organizers of both Formula1 and NASCAR are placing increasing limits on aerodynamic development such as number of runs in a wind tunnel and CPU hours for CFD simulation. This prevents widespread use of LES or DES methodologies that require 5-10 times more computational resources.

In spite of growing popularity of scale resolved transient simulations, like the Detached Eddy Simulation (DES), among the mainstream automotive OEMs for the aerodynamic optimization of the production vehicles, Reynolds Averaged Navier-Stokes (RANS) simulations is still the most widely used Computational Fluid Dynamics (CFD) approach in motorsports. This is partially due to the usage-limitations imposed by the sanctioning bodies like, the FIA and NASCAR, restricting not only the hours of wind tunnel operation but also limiting the amount of CFD compute resource. This, coupled with speed requirements for aerodynamic development prevent the widespread use of scale-resolved modeling, such as Large Eddy Simulation (LES) or Detached Eddy Simulation (DES) methodologies that require an order of magnitude more computational resources.

Autonomous takeoff and landing maneuvers of an unmanned aerial vehicle (UAV) from/on a moving ground vehicle (GV) have been an area of active research for the past several years. For military missions requiring repeated flight operations of the UAV, precise landing ability is important for autonomous docking into a recharging station, since such stations are often mounted on a ground vehicle. The development of precise and efficient control algorithms for this autonomous maneuvering has two key challenges; one is related to flight aerodynamics and the other is related to a precise detection of the landing zone. The aerodynamic challenges include understanding the complex interaction of the flows over the UAV and GV, potential ground effects at the proximity of the landing surface, and the impact of the variations in the surrounding wind flow and ambient conditions.

Although, the implementation of lift-off prevention devices such as the NASCAR roof flaps have greatly reduced the frequency and severity of race vehicle aerodynamic lift-off incidents, airborne incidents still occur occasionally in motorsports. The effectiveness of existing lift-off prevention measures and future trends in lift-off prevention are addressed in this paper. The results and analysis presented in this paper will be of paramount interest to race vehicle designers and sanctioning bodies because the effects of aerodynamics on vehicle lift-off need to be comprehended, but there exists a scarcity of reliable data in this area.