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The high cost and competitive nature of automotive product development necessitates the search for less expensive and faster methods of predicting vehicle performance. Continual improvements in High Performance Computing (HPC) and new computational schemes allow for the digital evaluation of vehicle comfort parameters including wind noise. Recently, the commercially available Computational Fluid Dynamics (CFD) code PowerFlow, was evaluated for its accuracy in predicting wind noise generated by an external automotive tow mirror. This was accomplished by running simulations of several mirror configurations, choosing the quietest mirror based on the predicted performance, prototyping it, and finally, confirming the prediction with noise measurements taken in an aeroacoustic wind tunnel. Two testing methods, beam-forming and direct noise measurements, were employed to correlate the physical data with itself before correlating with simulation.

This paper presents a simulation of the cooling airflow and surface temperatures of a midsize truck. The simulation uses full detailed geometry of the truck. Performance of the under-hood cooling airflow is analyzed and potential design changes leading to better cooling airflow are highlighted. Surface temperature over certain under-hood part is studied. Possible optimizations using various material and configurations are proposed. It is shown that the presented simulation approach provides valuable information to evaluate cooling system and thermal protection performance. Fast design iterations can be achieved using this approach.

For most car manufacturers, wind noise from the greenhouse region has become the dominant high frequency noise contributor at highway speeds. Addressing this wind noise issue using experimental procedures involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process. Previously, a computational approach that couples an unsteady computational fluid dynamics solver (based on a Lattice Boltzmann method) to a Statistical Energy Analysis (SEA) solver had been validated for predicting the noise contribution from the side mirrors. This paper presents the use of this computational approach to predict the vehicle interior noise from the windshield wipers, so that different wiper placement options can be evaluated early in the design process before the surface is frozen.

Wind noise is a significant source of interior noise in automobiles at cruising conditions, potentially creating dissatisfaction with vehicle quality. While wind noise contributions at higher frequencies usually originate with transmission through greenhouse panels and sealing, the contribution coming from the underbody area often dominates the interior noise spectrum at lower frequencies. Continued pressure to reduce fuel consumption in new designs is causing more emphasis on aerodynamic performance, to reduce drag by careful management of underbody airflow at cruise. Simulation of this airflow by Computational Fluid Dynamics (CFD) tools allows early optimization of underbody shapes before expensive hardware prototypes are feasible. By combining unsteady CFD-predicted loads on the underbody panels with a structural acoustic model of the vehicle, underbody wind noise transmission could be considered in the early design phases.

Since transient vehicle HVAC computational fluids (CFD) simulations take too long to solve in a production environment, the goal of this project is to automatically create a lumped-parameter flow network from a steady-state CFD that solves nearly instantaneously. The data mining algorithm k-means is implemented to automatically discover flow features and form the network (a reduced order model). The lumped-parameter network is implemented in the commercial thermal solver MuSES to then run as a fully transient simulation. Using this network a “localized heat transfer coefficient” is shown to be an improvement over existing techniques. Also, it was found that the use of the clustering created a new flow visualization technique. Finally, fixing clusters near equipment newly demonstrates a capability to track localized temperatures near specific objects (such as equipment in vehicles).

In the development of an FAW SUV, one of the goals is to achieve a state of the art drag level. In order to achieve such an aggressive target, feedback from aerodynamics has to be included in the early stage of the design decision process. The aerodynamic performance evaluation and improvement is mostly based on CFD simulation in combination with some wind tunnel testing for verification of the simulation results. As a first step in this process, a fully detailed simulation model is built. The styling surface is combined with engine room and underbody detailed geometry from a similar size existing vehicle. From a detailed analysis of the flow field potential areas for improvement are identified and five design parameters for modifying overall shape features of the upper body are derived. In a second step, a response surface method involving design of experiments and adaptive sampling techniques are applied for characterizing the effects of the design changes.

On-highway tractor-trailer vehicles operate in a complex aerodynamic environment that includes influences of surrounding vehicles. Typical aerodynamic analyses and testing of single vehicles on test track, in wind tunnel or in computational fluid dynamics (CFD) do not account for these real world effects. However, it is possible with simulation and on-road testing to evaluate these aerodynamic interactions. CFD and physical testing of multiple vehicle interactions show that traffic interactions can impact the overall drag of leading and trailing vehicles. This paper will discuss results found in evaluating the effects of separation distances on tractor-trailer aerodynamics in on-road and CFD evaluations using a time-accurate Lattice Boltzmann Method based approach and the ramifications for improving real world prediction versus controlled single vehicle testing.

This paper presents a combined numerical and experimental investigation of the characteristics of spark discharge in a spark-ignition engine. The main objective of this work is to gain insights into the spark discharge process and early flame kernel development. Experiments were conducted in an inert medium within an optically accessible constant-volume combustion vessel. The cross-flow motion in the vessel was generated using a previously developed shrouded fan. Numerical modeling was based on an existing discharge model in the literature developed by Kim and Anderson. However, this model is applicable to a limited range of gas pressures and flow fields. Therefore, the original model was evaluated and improved to predict the behavior of spark discharge at pressurized conditions up to 45 bar and high-speed cross-flows up to 32 m/s. To accomplish this goal, a parametric study on the spark channel resistance was conducted.

For the automotive industry, the quality and level of the wind noise contribution has a growing importance and therefore should be addressed as early as possible in the development process. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof broadband noise is generated by the turbulent flow developed over the roof opening. A strong shear layer and vortices impacting on the trailing edge of the sunroof are typical mechanisms related to the noise production. Sunroof designs are tested to meet broadband noise targets. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions and potentially late design changes.

The object of the validation study presented in this paper is a generic vehicle, the so-called SAE body, developed by a consortium of German car manufacturers (Audi, Daimler, Porsche, Volkswagen). Many experiments have been performed by the abovementioned consortium on this object in the past to investigate its behavior when exposed to fluid flow. Some of these experiments were used to validate the simulation results discussed in the present paper. It is demonstrated that the simulation of the exterior flow is able to represent the transient hydrodynamic structures and at the same time both the generation of the acoustic sources and the propagation of the acoustic waves. Performing wave number filtering allows to identify the acoustic phenomena and separate them from the hydrodynamic effects. In a next step, the noise transferred to the interior of the cabin through the glass panel was calculated, using a Statistical Energy Analysis approach.

Exhaust and muffler noise is a challenging problem in the transport industry. While the main purpose of the system is to reduce the intensity of the acoustic pulses originating from the engine exhaust valves, the back pressure induced by these systems must be kept to a minimum to guarantee maximum performance of the engine. Emitted noise levels have to ensure comfort of the passengers and must respect community noise regulations. In addition, the exhaust noise plays an important role in the brand image of vehicles, especially with sports car where it must be tuned to be “musical”. However, to achieve such performances, muffler and exhaust designs have become quite complex, often leading to the rise of undesired self-induced noise. Traditional purely acoustic solvers, like Boundary Element Methods (BEM), have been applied quite successfully to achieve the required acoustic tuning.

Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.

One of the remaining challenges in the simulation of the aerodynamics of ground vehicles is the modeling of the airflows around the spinning tires and wheels of the vehicle. As in most advances in the development of simulation capabilities, it is the lack of appropriately detailed and accurate experimental data with which to correlate that holds back the advance of the technology. The flow around the wheels and tires and their interfaces with the vehicle body and the ground is a critical area for the development of automobiles and trucks, not just for aerodynamic forces and moments, and their result on fuel economy and vehicle handling and performance, but also for the airflows and pressures that affect brake cooling, engine cooling airflows, water spray management etc.

Modern aerodynamic Class 8 freight tractors can improve vehicle freight efficiency and fuel economy versus older traditional style tractors when pulling Canadian style A- or B-Train double trailer long combination vehicles (LCV's) at highway speeds. This paper compares the aerodynamic performance of a current generation aerodynamic tractor with several freight hauling configurations through computational fluid dynamics evaluations using the Lattice-Boltzmann methodology. The configurations investigated include the tractor hauling a standard 53′ trailer, a platooning configuration with a 30′ separation distance, and an A-Train configuration including two 48′ trailers connected with a dolly converter. The study demonstrates CFD's capability of evaluating extremely long vehicle combinations that might be difficult to accomplish in traditional wind tunnels due to size limitations.

The interaction of fuel sprays and in-cylinder flow in direct-injection engines is expected to alter kinetic energy and integral length scales at least during some portions of the engine cycle. High-speed particle image velocimetry was implemented in an optical four-valve, pent-roof spark-ignition direct-injection single-cylinder engine to quantify this effect. Non-firing motored engine tests were performed at 1300 RPM with and without fuel injection. Two fuel injection timings were investigated: injection in early intake stroke represents quasi-homogenous engine condition; and injection in mid compression stroke mimics the stratified combustion strategy. Two-dimensional crank angle resolved velocity fields were measured to examine the kinetic energy and integral length scale through critical portions of the engine cycle. Reynolds decomposition was applied on the obtained engine flow fields to extract the fluctuations as an indicator for the turbulent flow.

The primary purpose of this paper is to correlate the CFD simulations performed using PowerFLOW, a Lattice Boltzmann based method, and wind tunnel tests performed at a wind tunnel facility on 1/8th scaled tractor-trailer models. The correlations include results using an aerodynamic-type tractor paired with several trailer configurations, including a baseline trailer without any aerodynamic devices as well as combinations of trailer side skirts and a tractor-trailer gap flow management device. CFD simulations were performed in a low blockage open road environment at full scale Reynolds number to understand how the different test environments impact total aerodynamic drag values and performance deltas between trailer aerodynamic devices. There are very limited studies with the Class-8 sleeper tractor and 53ft long trailer comparing wind tunnel test and CFD simulation with and without trailer aerodynamic device. This paper is to fill this gap.

Trailer positioning plays a significant role in the overall aerodynamics of a tractor-trailer combination and varies widely depending on configuration and intended use. In order to minimize aerodynamic drag over a range of trailer positions, adjustable aerodynamic devices may be utilized. For maximum benefit, it is necessary to determine the optimal position of the aerodynamic device for each trailer position. This may be achieved by characterizing a two-dimensional design space consisting of trailer height and tractor-trailer gap length, with aerodynamic drag as the response. CFD simulations carried out using a Lattice-Boltzmann based method were coupled with modeFRONTIER for the creation of multiple Kriging Response Surfaces. Simulations were carried out in multiple phases, allowing for the generation of intermediate response surfaces to estimate predictive error and track response surface convergence.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

The ultimate goal for vehicle aerodynamicists is to develop vehicles that perform well on the road under real-world conditions. One of the most important metrics to evaluate vehicle performance is the drag coefficient. However, vehicle development today is performed mostly under controlled settings using wind tunnels and computational fluid dynamics (CFD) with artificially uniform upstream conditions, neglecting real-world effects due to road turbulence from wind and other vehicles. Thus, the drag coefficients computed with these methods might not be representative of the real performance of the car on the road. This might ultimately lead engineers to develop design solutions and aerodynamic devices which, while performing well in idealized conditions, do not perform well on the road. For this reason, it is important to assess the vehicle’s drag as seen in real-world environments. An effort in this direction is represented by using the wind-averaged drag.

Exhaust systems including mufflers are commonly mounted on engines to reduce the firing cycle noise originating from the combustion process. However, mufflers also produce flow-induced self-noise, originating from the complex flow path throughout the muffler. As an engine prototype is not available in the early stages of a development program, it is challenging to assess the acoustic performance of the full system when only experiment is available. It is also difficult to pinpoint the design features of a muffler generating noise, as a portion of the noise is generated internally. Numerical approaches are a possible alternative. However, capturing non-linear dissipation mechanisms and thermal fluctuations of exhaust flows is challenging, while necessary to accurately predict flow noise.