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An overview of the theory and applications of the Lattice-Boltzmann Method (LBM) is presented in this paper. LBM has gained a reputation over the past decade as a viable alternative to traditional Reynolds-averaged Navier-Stokes (RANS) based methods for the solution of computational fluid dynamics (CFD) applications in the aerospace and automotive industries. The theoretical background of the method is presented and the key differentiators to traditional RANS methods are summarized. We then look at current and potential future applications of CFD in the aerospace industry and identify a number of areas where the limitations of RANS tools, in particular with regard to unsteady flows and the handling of complex geometries, prevent a deeper penetration of CFD into product development processes in the aerospace industry.

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.

Presented are simulations of cooling airflow and external aerodynamics over Land Rover LR3 and Ford Mondeo cars under several driving conditions. The simulations include details of the external flow field together with the flow in the under-hood and underbody areas. Shown is the comparison between the predicted and measured coolant inlet temperature in the radiator, drag and lift coefficients, temperature distribution on the radiator front face, and wake total pressure distribution. Very good agreement is observed. In addition, shown is the complex evolution of the temperature field in the idle case with strong under-hood recirculation. It is shown that the presented Lattice-Boltzmann Method based approach can provide accurate predictions of both cooling airflow and external aerodynamics.

Nowadays vehicle quality is rated for noise and vibration and the interior sound levels have become a major target of automotive companies. Strides have been made in reducing power train, tire and external wind noise over the years. However, HVAC and blower fan flow-induced noise reaches the interior cabin without any sound isolation and can strongly impact customer comfort. In the early stage of vehicle design, it is experimentally difficult to get an estimate of the flow pattern and sound levels. The goal of this study is to develop and validate a numerical noise prediction tool for complete HVAC systems noise, defined as the arrangement of sub-systems such as air intake duct, thermal mixing unit, blower, ducts and outlet vents. This tool can then be used during the development of vehicles to evaluate and optimize the aeroacoustics performances of the system without additional or belated experiments.

Charge air temperature needs to be kept low for optimum engine operation. If charge air temperature is too high, engine performance reduction strategies are invoked to protect engines by limiting torque available to drivers. A 1D-3D coupling simulation methodology is developed to accurately predict internal air temperature after charge air cooler (CAC) during a racing drive cycle. The 3D flow simulation is used to characterize external air flow before CAC in steady-state cases. Then, interpolated 3D simulation results between steady operating points are used as transient external air boundary conditions in front of CAC in a 1D system model. 3D flow simulation is also used to predict internal flow rate ratio between CAC tubes. Finally, an 1D system model is used to predict time-trace of charge air temperature at CAC internal outlet during the racing drive cycle. The simulation results show that prediction errors are within 5 degrees for charge air temperature at internal outlets.

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.

A new approach is proposed and demonstrated for investigation of the spatial structure of fluctuations in unsteady aerodynamics results obtained using CFD. This approach is used in this study to isolate unsteadiness in the flow field due to coherent structures at relatively high frequency from the dominant organized motion, as well as from the computational noise, in unsteady data obtained from CFD simulations. These simulations are performed using the commercial CFD software, PowerFLOW, which employs a Lattice Boltzmann method and a very large-eddy simulation (VLES) model for small-scale turbulence. Spectral analysis is performed on the simulation data to compare with experimental results obtained in a wake plane for a simplified vehicle shape. A new frequency band filtering approach is used to visualize pressure fluctuations in the dominant frequency range responsible for aerodynamic noise.

A newly developed simulation methodology for a long term, transient tractor cabin cool-down is presented in this paper. The air flow was simulated using a Lattice-Boltzmann Equation (LBE) based 3-dimensional flow solver. The conduction and radiation effects on the solid parts as well as the average cabin air temperature evolution were solved by the thermal solver, which also includes a human comfort model. The simulation results were compared with the measured experimental test data and good agreement was observed validating the developed simulation approach. The developed methodology can be applied to all other ground vehicles cabin comfort applications.

The efficiency of a gap-type of deflector for suppressing vehicle sunroof buffeting is studied in this work. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using a CFD/CAA numerical method based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution. In this study the same gap-type deflector configuration is installed on two different types of vehicles, a SUV and a sedan.

A decade of industrial experience with Exa's CFD software, PowerFLOW, has matured the simulation software to the point where the geometric modeling process is now the bottleneck to efficiency and effectiveness. Simply put, the actual CAE simulation event is now fast enough and accurate enough to drive design intent; however, the geometric design process that supplies alternative models to the software is not fast enough to keep up with the critical path of the design cycle. If CAE tools in general are to play in important role in creating design intent rather than simply verifying completed design work, then the modeling process which drives them will have to improve. In the context of this paper, geometric design involves both Class A exteriors and under-hood geometries. Two pieces of software have been developed to help in this area: PowerWRAP and PowerCLAY.

Wind noise has become an important indicator for passenger automobile quality. Several transmission paths can be related to different parts of the vehicle exterior. While the greenhouse (side glasses, windshield, seals & others) often dominates the interior noise level above 500 Hz, the contribution coming from the underbody area usually dominates the interior noise spectrum at lower frequencies. This paper describes a framework of numerical tools which is capable of determining realistic underbody turbulent and acoustic loads being generated for typical driving conditions, as well as performing the noise transmission through underbody panels and the propagation of sound to the drivers ear location.

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.

Exhaust systems are a necessary solution to reduce combustion engine noise originating from flow fluctuations released at each firing cycle. However, exhaust systems also generate a back pressure detrimental for the engine efficiency. This back pressure must be controlled to guarantee optimal operating conditions for the engine. To satisfy both optimal operating conditions and optimal noise levels, the internal design of exhaust systems has become complex, often leading to the emergence of undesired noise generated by turbulent flow circulating inside a muffler. Associated details needed for the manufacturing process, such as brackets for the connection between parts, can interact with the flow, generating additional flow noise or whistles. To minimize the risks of undesirable noise, multiple exhaust designs must be assessed early to prevent the late detection of issues, when design and manufacturing process are frozen. However, designing via an experimental approach is challenging.

The engineering process in the development of commercial vehicles is facing more and more stringent emission regulations while at the same time the market demands for better performance but with lower fuel consumption. The optimization of aerodynamic performance for reduced drag is a key element for achieving related performance targets. Closely related to aerodynamics are wind noise and cabin soiling and both of them are becoming more and more important as a quality criterion in many markets. This paper describes the aerodynamic and aero-acoustic performance evaluation of a Dongfeng heavy truck using digital simulation based on a LBM approach. It includes a study for improving drag within the design of a facelift of the truck. A soiling analysis is performed for each aerodynamic result by calculating the accumulation of particles emitted form the wheels on the cabin. One of the challenges in the development process of trucks is that different cabin types have to be designed.

At SAIC-GM-Wuling (SGMW) the greenhouse wind noise performance of their vehicles has gained a lot of attention in the development process. In order to evaluate and improve the noise quality of a newly developed SUV a digital simulation based process has been employed during the early stage of the design. CFD simulation was used for obtaining the flow induced exterior noise sources. Performance metrics for the quality were based on interior noise levels which were calculated from the exterior sources using a SEA approach for the noise transmission through the glass panels and propagation to the driver’s or passenger’s head space. Detailed analysis of the CFD results allowed to identify noise sources and related flow structures. Based on this analysis, design modifications were then applied and tested in a sequential iterative process. As a result an improvement of more than 2 dB in overall sound pressure level could be achieved.

The demand for low noise level in vehicle cabin continues to rise lately. In particular, noise generated by eco-friendly cars such as hybrid and electric ones tends to become lower and lower. In this market environment, the noise contributions caused by HVAC systems are also increasing. Therefore, it becomes increasingly important to accurately predict noise generated by HVAC systems and analyze the noise sources and resolve the noise issue. In this study, direct acoustics prediction approach based on Lattice Boltzmann Method is applied to predict the flow-induced noise from HVAC systems including blower and ducts and find noise sources. In order to validate the simulation result, acoustics measurements are performed on HVAC systems in an anechoic room and the results are compared to each other. A new technique is applied to finding a noise source for a specific frequency and shows improved noise level through modifying the geometry related to noise sources detected by the simulation.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

A computational design study, performed in conjunction with experiments, to reduce the howl noise caused by the roof rack crossbars of a production automobile is presented. This goals were to obtain insight into the flow phenomenon causing the noise, and to do a design iteration study that would lead to a small number of cross-section recommendations for crossbars that would be tested in the wind tunnel. The flow condition for this study is 0 yaw at 30 mph inlet speed, which experimentally gives the strongest roof rack howl for the vehicle considered for this study. The numerical results have been obtained using the commercial CFD/CAA software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice Boltzmann Method (LBM), combined with a two-equation RNG turbulence model.

A numerical investigation of automobile sunroof buffeting on a prototype sport utility vehicle (SUV) is presented, including experimental validation. Buffeting is an unpleasant low frequency booming caused by flow-excited Helmholtz resonance of the interior cabin. Accurate prediction of this phenomenon requires accounting for the bi-directional coupling between the transient shear layer aerodynamics (vortex shedding) and the acoustic response of the cabin. Numerical simulations were performed using the PowerFLOW code, a CFD/CAA software package from Exa Corporation based on the Lattice Boltzmann Method (LBM). The well established LBM approach provides the time-dependent solution to the compressible Navier-Stokes equations, and directly captures both turbulent and acoustic pressure fluctuations over a wide range of scales given adequate computational grid resolution.