Experimental and numerical studies on aerodynamic ...

Experimental and numerical studies on aerodynamic noise of automotive rear view mirror Qiliang Lia), Zhigang Yangb), Yigang Wangc) and Yinzhi Hed) (Received: 1 June 2011; Revised: 26 September 2011; Accepted: 30 September 2011)

Wind tunnel test and numerical approaches are used to understand the aerodynamic noise characteristics of automotive rear view mirror, and their results are compared to evaluate the similarities and differences. The agreement of the location of sound sources and the sound spectra indicates the mutual validation of the two different approaches, and the numerical simulation approach is feasible to investigate the characteristics of the mirror induced noise. The test sound spectra show that the frequency of noise is mainly in the low and middle frequency range. With increment in the nozzle speed, the frequency of shedding vortex increases linearly and it suggests the existence of a constant Strouhal number for a given mirror. The sound energy of sound sources region and other regions becomes stronger when the nozzle speed increases. In regions of side windows and far field, the sound energy is proportional to the fourth power of nozzle speed and the 5.8th power of nozzle speed respectively. C 2011 Institute of Noise Control Engineering. V Primary subject classification: 21.6.5; Secondary subject classification: 13.2.1

1 INTRODUCTION Due to the required reduction of noise emissions to the environment and the reduction of noise level inside passenger cabin, studies of noise generation and propagation are becoming more and more crucial for the development of vehicles. As noise generated by engine and tires has become quieter, aerodynamic noise has become the dominant noise under high-speed cruising conditions. Among various types of aerodynamic noise, the broadband noise that is generated by fluid passing over rear view mirror is probably the most noticeable. It is caused by fluctuating pressure and velocity of the complex flow field, while the flow and acoustic mechanisms have not yet been fully clarified. Fluid passing over rear view mirror has been studied in the past two decades. Early studies were directed at optimizing mirror housing shapes to reduce their contribution to the total aerodynamic drag of the vehicle, a)

b)

c)

d)

College of Automotive Studies, Jiading Campus of Tongji University, Shanghai CHINA; email: [email protected]. College of Automotive Studies, Jiading Campus of Tongji University, Shanghai CHINA; email: zhigang.yang@ sawtc.com. College of Automotive Studies, Jiading Campus of Tongji University, Shanghai CHINA; email: yigang.wang@ sawtc.com, (Corresponding author). College of Automotive Studies, Jiading Campus of Tongji University, Shanghai CHINA; email: yinzhi.he@sawtc .com.

Noise Control Eng. J. 59 (6), November-December 2011

which is around 3–6% for modern vehicles1. Later studies used experimental methods to determine shape, angle and position of the mirror housing that lead to reduce aerodynamic noise2–4. With the development of computer hardware, numerical algorithms and turbulent models, CFD has emerged to become a viable tool for investigating aerodynamic noise generated by rear view mirror. A generic rear view mirror (a quarter sphere on the top of a half cylinder) has been extensively studied by many research groups, using experimental and computational techniques5–8. Most of those studies were focused on the feasibility of numerical method which was used to simulate aerodynamic noise generated by rear view mirror. A further study was done by Kuo-Huey Chen et al9 to develop a transient CFD procedure to accurately predict aerodynamic noises generated by the actual production rear view mirror. One of few studies10 extends single mirror on a flat plate to mirror mounted on a full vehicle. They did an excellent work of the aerodynamic noise generated by rear view mirror. However, all the numerical and experimental results were focused on the frequency below 1000 Hz, and the agreement between numerical predictions and experimental measurement for the BMW vehicle was not good. It wasn’t clear whether such discrepancies between numerical results and test results were due to the turbulence model and mesh density. The present investigation is a study on the rear view mirror of Rover series which is mainly focused on the aerodynamic noise characteristic generated by rear 613

view mirror, which has not yet been fully studied. Both wind tunnel test and CFD approach were used in the present study, with wind tunnel test being the main tool of study and CFD serving as a tool of validation together. The structure of the paper is as follows: the method of study is firstly described; then, the test result is discussed and the comparison between test results and numerical results is shown; conclusions are presented in the last section of the paper.

2 METHOD OF STUDY 2.1 Experimental Method In order to improve the understanding of aerodynamic noise phenomena, a development project has been established to study the aerodynamic noise generated by automotive rear view mirror using wind tunnel test and numerical simulation. A style of production vehicle was chosen to do an aerodynamic noise experiment at Shanghai Automotive Wind Tunnel Center11, as shown in Fig. 1, which is the first full scale automotive wind tunnel in China. The background noise level of aero-acoustic wind tunnel is lower than 61 dBA at the nozzle speed of 160 km=h, with the help of a special low-noise ventilator and comprehensive acoustic treatment. The test was conducted at three nozzle speeds of 120 km=h, 140 km=h and 160 km=h when the vehicle yaw angle is 0 . In each test condition, five types of acoustic equipment including surface microphone, microphone with nose cone, free field microphone, artificial head and microphone array with 120 channels were used. Nine 13.2 mm diameter G.R.A.S high sensitivity surface microphones were mounted to the surface of the side windows and the rear view mirror to record sound sources, which was shown in Fig. 2(a). Figure 2(b) shows the positions of free field microphone and microphone array. Artificial head was located at the position of driver to reflect his or her subjective impression.

Fig. 2—Test points position. In order to locate the position of the test points accurately and conveniently, coordinate origin “O” is located at the left front side windows near the B-pillar, and then the coordinate positions of all test points are illustrated in Table 1. Before the test was done, all the test equipments were calibrated by following the production instruction. The gap of the car body was covered by the seal and some safeguards were done. Then the sampling frequency and sampling time of data processing were set to 48k and 30s, respectively. Sound pressure signals of the test points at three nozzle speeds were collected. We did the same measurement with and without the mirror, so that we could understand aerodynamic noise of the mirror clearly.

2.2 Numerical Method

Fig. 1—Schematic of wind tunnel test. 614


A CAD model of entire vehicle without engine cabin, passenger cabin and tires etc, was created by using ATOS I high-speed 3D digitizer, as shown in Fig. 3. The vehicle model has a length of 4865 mm, a width of 1765 mm and a height of 1422 mm. To make the vehicle body form a closed volume, four simplified tires based on main tire parameters were installed at the position of tire. The vehicle is placed in a computational domain which was five times the vehicle length, seven times the vehicle width and four times the

Table 1—Geometric position of test points. Number x (mm) y (mm) z (mm) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

498 298 298 498 498 398 298 498 660 689 751 2498 998 73 2356 552

13 13 63 86 35 96 127 127 127 127 27 5788 5788 5788 5788 6288

47 46 172 221 110 240 79 79 48 149 29 79 79 79 79 108

Equipment type Surface microphone Surface microphone Surface microphone Surface microphone Surface microphone Surface microphone Microphone þnose cone Microphone þnose cone Surface microphone Surface microphone Surface microphone Free field microphone Free field microphone Free field microphone Free field microphone Microphone array

vehicle height. There was almost one times the vehicle length between the computational domain inlet and bump of vehicle, as shown in Fig. 4. The CAD model as STL format was imported into the commercial software HYPERMESH. Before the surface mesh was generated, geometry cleanup which includes deleting short edges and merging faces was done. In the present numerical study, the vehicle component surfaces were discretized with triangle mesh elements. The smallest surface element has a size around 2.55.0 mm, which is located at the surfaces of mirror, as depicted in Fig. 5(a). A bigger surface element has a size around 7.510.0 mm, which is located at the surfaces of side windows, as shown in Fig. 5(b). The typical surface mesh element of other surfaces has a size around 10–15 mm. The surfaces of virtual wind tunnel were discretized with mainly rectangular mesh

Fig. 3—CAD model. Noise Control Eng. J. 59 (6), November-December 2011

Fig. 4—Computational domain. elements. Cells of prismatic layers were created just off the vehicle surfaces and the wind tunnel floor in order to satisfy the required near-wall resolution with yþ5 and better resolve the boundary layer over those surfaces. Next to these prismatic cells, tetra cells were generated in the computational domain within a Cartesian box enclosing the vehicle model, which is about two times of vehicle length distance in length, two times the vehicle length, two times the vehicle width and two times the vehicle height. Hex cells were used to discretize the fluid in the remaining part of the computation domain, because it is more accurate and more economic in mesh amounts. Cells of mixed cell type were generated using commercial software TGRID. The number of the resulting cells is strongly dependent on the size of the surface mesh representing the boundary of the computational domain, and the size of the computational domain itself. In the present study, nearly 9.9 million cells were created in the initial solution. Hybrid approach was used to predict aerodynamic noise generated by rear view mirror. First, a spatial and temporal aerodynamic simulation is done to obtain velocity and pressure fluctuations from the sound sources terms. Then, an acoustic analogy is used to calculate sound at the receivers from the velocity and pressure fluctuations recorded in the simulation at the sources. In the current analysis, large eddy simulation (LES)12 of the commercial software Fluent 6.3.26 was used to obtain pressure fluctuations on the surfaces of vehicle. The sound pressure at all test points is calculated using FW-H formulation13, which adopts the most general form of Lighthill’s acoustic analogy14,15. One of the test nozzle speeds which corresponds to the Mach numbers for the incoming flow of 0.11 is chosen. Due to low Mach number, an incompressible pressure based solver is used with an implicit SIMPLE pressure-velocity coupling algorithm. A Bounded Central Difference scheme is chosen for the present case and the discretization in time follows an implicit second-order scheme to obtain a converged solution. Smagorinsky-Lilly subgrid model is used to solve eddy viscosity in LES approach. At the inlet to the computational domain, a constant velocity with no 615

Fig. 5—Surfaces mesh of vehicle. perturbations condition was used. At the exit of the virtue wind tunnel, the pressure outflow condition was specified. Inviscid wall conditions were applied at the virtue wind tunnel side and top walls. No-slip wall condition was applied at the surfaces of the vehicle and the wind tunnel floor. A steady state solution was first obtained using Realizable k-e turbulence model16 and second order upwind discretization schemes. The steady state data was then used to initialize the transient LES run. The transient simulation was started with an initial time step of 0.0005s and twenty five iterations per time step. Two thousand time steps later, the time step was reduced to 0.00025s, but the iteration numbers of each time step weren’t changed. It should be pointed out that twenty five iterations were conducted within each time step to ensure that the continuity and momentum equations were converged till the residuals dropped more than 4 orders of magnitude at each time step. Some monitor points were created to discern whether the solution reached dynamic stability. According to the amplitude and frequency of pressure and velocity fluctuations at the monitor points, the solution has reached dynamic stability after next two thousand time steps. After achieving dynamic stability, pressure fluctuations on the surfaces were extracted for the aerodynamic noise post-processing. More than two thousand pressure fluctuations of sound sources data were collected. As for HP xw8400 workstation made up of eight processors, our case spent more than forty days.

characteristics at the nozzle speed of 140 km=h was analyzed.

3 ANALYSIS OF TEST RESULTS

3.2 Side Windows

We analyzed the aerodynamic noise characteristics inside and outside the flow field using wind tunnel test results. Due to the similarity of acoustic characteristic at different nozzle speeds, only the aerodynamic noise

The sound pressure of side windows is influenced by mirror and A-pillar. Two test points are chosen to understand its effects through installing and detaching the mirror on the side windows, and their frequency

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3.1 Location of Sound Sources The microphone array measurement technique is a good tool to investigate sound sources qualitatively, and a lot of efforts have been put into the development of this technique for aero-acoustical application to investigate sound sources of vehicle in the past few years. For microphone array measurement in an open test section of aero-acoustic wind tunnel, it is usually placed outside the flow field, where the sound emitted from sources in the flow has to propagate through a turbulent shear layer to reach the microphones. Fluid passing over A-pillar region has a complex three dimensional structure. Fluid separates near the A-pillar and the separation rolls into a vertical structure and reattaches downstream due to the weep back, which becomes a big separation region and a reattachment region, as shown in Fig. 6. Aerodynamic noise is generated and propagated because of severe flow fluctuations resulted from these regions. Boundary layer is formed and developed at the housing of mirror, and it separates when adverse pressure gradient occurs. A lot of vortices with a wide range of length and time scales occur at the wake of mirror and they flap the side windows which lead to high strong intensity of pressure fluctuations and form a sound source. This is indeed found to be the case, as illustrated by Fig. 7(a), which shows a big sound source at the location of the side windows region.

3.3 Wake of Mirror

Fig. 6—Flow field characteristic of A-pillar and mirror regions. spectrum of sound pressure level is shown in Fig. 8. We can see from the results for point 1 there is an obvious discrepancy in the frequency below 1000 Hz and above 5000 Hz, and little difference in the frequency spectrum from 1000 to 5000 Hz. The sound pressure level of the test point with mirror is far higher than that without mirror at the low and middle frequencies. When the frequency increases, the discrepancy becomes small. As for high frequency, the discrepancy of sound pressure level is about 1.5 dB. Based on these findings, we can conclude that for the side window near the mirror, the effects on sound pressure focus on low and middle frequency that is due to large scale eddies generated by separation at the mirror. The intensity of the A-pillar vortex can be influenced by the root of mirror because it hinders A-pillar vortex to form and develop, which is the reason why the sound pressure level of point 6 without mirror is higher than that with mirror for the frequency below 1000 Hz.

The wake of the mirror is very complex due to flow separation. Two test points are chosen to record the sound pressure coming from the dipole generated by pressure fluctuations of the surfaces and quanrupole generated by Lightlill stress of the flow field. The frequency spectrum of sound pressure level for point 7 in Fig. 9 has a weak peak apparently due to the largescale vortical motion. However, the peak is not intense enough to alter the overall level of the sound radiated from the mirror. As for the wake of mirror, we know that large scale eddies become smaller and smaller due to vortex interaction as fluid keeps away from the mirror. Large scale eddies such as shedding vortices have more energy and a longer life from formation to being dissipated, which contribute to acoustic characteristic of low frequency. But small scale eddies has less energy and a shorter life, which produces the frequency characteristic. Frequencies that corresponds to the vortex shedding can be found at three nozzle speeds. When the vortex shedding frequency at three nozzle speeds is extracted and plotted into Fig. 10, we can see that the vortex shedding frequency increases as the nozzle speed increases. For example, when the nozzle speed ranges from 120 to 160 km=h, the vortex shedding frequency changes from 58 to 77 Hz. A Strouhal number based on nozzle speed and equivalent diameter coming from the vertical midsection of mirror is calculated, and its value is 0.25, which suggests that vortex shedding frequency linearly increases as the nozzle speed increases.

Fig. 7—Location of sound sources. Noise Control Eng. J. 59 (6), November-December 2011

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Fig. 10—Vortex shedding frequency vs. nozzle speed for two test points.

Fig. 8—Frequency spectrum of sound pressure level for test points. 3.4 Inside the Vehicle Sound quality inside the vehicle plays a major role in providing quiet and comfortable rides, and it becomes one of the important factors used to evaluate automotive comfortable performance. Aerodynamic noise generated by vehicle influences the sound quality inside passenger cabin by two transfer paths. One path by which aerodynamic noise can get inside the vehicle is directly through openings or leaks in the basic structure of the vehicle. The other path by which aerodynamic noise can get inside the vehicle is through

panels, windows and seals, because their transmission losses are less than 100%. Because most of openings are covered by seals, most of aerodynamic noise energy reaches the driver by the second path. As for the sound pressure level at the driver’s ear measured by artificial head, we can see that the sound pressure level of left ear is higher than that of right ear because left ear is near the sound sources. The sound pressure level in the low and middle frequency is far more than it is at high frequency, which can draw a conclusion that aerodynamic noise energy transferred into the passenger is focused on low and middle frequencies. From the noise control point of view, it is not good news because high frequencies are easy to absorb with carpeting and upholstery, and low frequencies are difficult to absorb with them. Due to person’s ears aren’t sensitive to too low and high frequency sound, A-weighted sound pressure level is used to evaluate the sound pressure of driver’s ears, as shown in Fig. 11. It is seen that the A-weighted sound pressure level in the frequency ranging from 100 to 1000 Hz is higher than at other frequencies. Based on the calculations, we get the total sound pressure level and A-weighted sound pressure level of the tested vehicle of 86 dB and 70 dBA respectively. According to previous experience, its noise level is a bit higher than B-class vehicle. Thus, optimization work on aerodynamic noise should be done to improve acoustic performances of the tested vehicle.

3.5 Outside the Vehicle

Fig. 9—Frequency spectrum of sound pressure. 618


The generated aerodynamic noise caused by the fluctuating pressure-induced structural oscillations of the vehicle body plays a significant role in the sound radiated into the far field, and it pollutes the acoustic environment of far field. Figure 12 shows the frequency spectrum of sound pressure level for point 14 which is located outside the flow field. From the figure we can see that the sound pressure level of test point

Fig. 11—Frequency spectrum of sound pressure level for driver’s ears. reduces when the frequency increases, and the rate of decrease becomes faster when the frequency goes higher. As for the A-weighted sound pressure level, the value in the frequency from 100 to 2000 Hz is also higher than at other frequencies.

3.6 The Relation between Sound Energy and Nozzle Speed According to the aero-acoustic theory, aerodynamic noise sources are composed of monopole, dipole and quadrupole. Monopole source effects from an unsteady introduction of volume into the surrounding fluid, and its strength is proportional to M4 (here M is the Mach number). Dipole source will be produced if time varying forces act on the fluid, and quadrupole source will be generated if time dependent stresses including momentum, viscosity and turbulence acting on the fluid. The strength of dipole and quadrupole is proportional to M6 and M8 respectively. To understand the sound sources component and the relation between sound energy and nozzle speed, we have calculated the total sound pressure level of two test points under three nozzle speeds, and their results are illustrated in Table 2. We can clearly see that total sound pressure level of test point increases when the

Table 2—Total sound pressure level. Nozzle speed (km=h) Total sound pressure level (dB)

Test point 4 Test point 14

120

140

160

125.8 82.9

128.6 86.6

130.9 90.3

nozzle speed increases. For the test point of side windows, about 5.1 dB increase in amplitude can be found when the nozzle speed increases from 120 km=h to 160 km=h. However, higher increase amplitude can be found for the test point outside the flow field. Many studies point out that aerodynamic noise energy generated by vehicle is proportional to vehicle speed raised to a power a, as shown in Eqn. (1). In order to find out the speed exponent, we make a deduction from the original format. Based on the test results of Table 2, two lines are shown in the Fig. 13. According to the slope of line one, we can see that for sound sources of side windows, the sound energy is nearly proportional to the fourth power of nozzle speed, which indicates that dipole source generated by static pressure fluctuation is the main type sound sources at that region. Based on the slope of line two, we can find that sound energy radiated from vehicle to the receiver outside the flow field is proportional to

Fig. 12—Frequency spectrum of sound pressure level for test point 14. Noise Control Eng. J. 59 (6), November-December 2011

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Fig. 13—Sound energy vs. nozzle speed. the 5.8th power of nozzle speed, which suggests that dipole source is still the main type sound sources for the far field. I / ua ) DSPL ¼ 10 lg ¼

Ii ui ¼ a 10 lg ) a I1 u1

DSPL 10 lg uu1i

(1)

4 COMPARISON OF NUMERICAL RESULTS AND TEST RESULTS In order to evaluate the feasibility of CFD to simulate aerodynamic noise of mirror, we spent more than forty days to get numerical results for the location of sound sources and the frequency spectrum of tested points.

4.1 Location of Sound Sources Figure 7(b) also shows a big sound source at the location of the side windows region. From the sound source point of view, both CFD results and test results are consistent. As for the exact location of sound source, the difference between test result and CFD result is due to the refraction effect that leads to the sound source drift downstream the flow.

4.2 Frequency Spectrum of Sound Pressure Level Figure 14 shows a comparison between CFD and test frequency spectrum. Three test points which are located at the side windows, A-pillar and mirror respectively are chosen to understand aerodynamic noise characteristic of sound sources, and one test point that is located outside the flow field is chosen to determine the propagation of aerodynamic noise generated by vehicle. The comparison frequency between measured and simulated sound pressure level is limited to 20 to 2000 Hz, which is due to the limited 620


Fig. 14—Frequency spectrum of sound pressure level for some points. computer resources and the background noise of the wind tunnel. The frequency spectrum of sound pressure level measured and computed shows a trend of monotonous

decay over a wide range of frequency from 20–2000 Hz. The numerical results agree with the test results up to about 1000 Hz for the three surface microphones. The discrepancy between test results and numerical results in the high frequency range from 1000 to 2000 Hz is solely attributed to the numerical error that may be caused by inadequate accurate turbulent model, coarse mesh density and low-accuracy scheme. Due to these reasons, eddies with small length and time scales are not resolved so that the turbulent energy of high frequency is underestimated. As for test point 14, sound pressure level measured and computed for all the compared frequencies except the frequency from 100 to 300 Hz is consistent. The reason for underestimating the sound pressure level computed at the frequency from 100 to 300 Hz is mainly because the flow field of tire regions can’t be simulated accurately by using simplified tires.

5 CONCLUSION The aerodynamic noise characteristic of automotive rear view mirror is presented. The wind tunnel test results, including the location of sound sources and the frequency spectrum at test points were taken into consideration, and the relation between sound energy and nozzle speed was pointed out. Numerical simulation of aerodynamic noise generated by mirror was also carried out to evaluate its feasibility. Vortex shedding frequency based on the weak peak due to the large-scale vortical motion can be found in the wake of mirror at different nozzle speeds. It increases linearly as nozzle speed increases, which demonstrates that the Strouhal number is a constant at all test nozzle speeds. The sound energy distributions of side windows and the wake of mirror are found to be concentrated in low and middle frequencies. It is shown that for sound sources of side windows, the sound energy is nearly proportional to the fourth power of nozzle speed, which indicates that dipole source generated by static pressure fluctuation is the main sound sources at that region. Sound energy radiated from vehicle to the receiver outside the flow field is proportional to the 5.8th power of nozzle speed, which suggests that dipole source is still the main type sound sources for far field. The numerical predictions using hybrid method based on Fluent LES and FW-H formulations agrees basically with the wind tunnel test in terms of the loca-


tion of sound sources and the noise spectra. Due to the mesh resolution, low-accuracy scheme and sub-grid modeling of the current LES, the spectra in the frequency above 1000 Hz isn’t good.

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