Traffic noise is a major noise source in the study of environmental noise. Various noise generation mechanisms depict different spectral features. Some are wide-band noise, such as engine knocks; some have signature frequencies, such as gear transmissions; and some are in a certain frequency region, such as tire/road noise. These spectral features affect the façade design of a building in order to achieve sufficient exterior noise insulation and satisfactory interior noise due to the traffic noise. ISO standard 11819-1 specifies the measurement procedure of statistical pass-by tests. There are three ranges of vehicle speed: slow, medium, and fast. However, it requires that the vehicle must maintain constant speed when passing by the test point. Unfortunately, a vehicle tends to generate higher noise when accelerating, especially at low frequencies. Therefore, it is necessary to distinguish the noise levels at an intersection versus middle-points of the road between two intersections. Presumably, the traffic noise levels at an intersection would be higher. This research measured the traffic noise at various locations of different speed limits. Statistical analyses were conducted to compare the spectra at these locations. This is also an effort to refine the noise map.

Random excitations can result from various types of non-deterministic loads such as wind loads, terrain loads, and other types of white noise loads. In this paper, an overview is presented of the modal method to obtain the random response of a coupled structural-acoustic system subjected to random excitations. When the structural system is coupled with an enclosed cavity, the structural-acoustic frequency response functions (FRFs) can be obtained using the uncoupled structural modes and the uncoupled acoustic modes, with structural-acoustic coupling as well as modal damping included in the formulation. The random response of the coupled structural-acoustic system is then obtained by summation of the structural-acoustic FRFs with the applied auto- and cross-spectral random loadings at the excitation locations. The theoretical formulation of the coupled structural-acoustic system is described. An example of a rectangular cavity coupled with flexible panels exposed to external random white noise load is presented. The methodology is then applied to an automotive vehicle travelling over a randomly rough road to predict the interior sound pressure response in the vehicle.

Goods and products transported by road are subjected to vehicle vibration which, without proper protective packaging, can suffer damage. To reduce shipment costs, protection has to be optimised to limit product damage occurrence while keeping packaging weight and size to a minimum. Optimisation is realized by simulating the vibration of transport vehicles. To achieve an accurate simulation, each vehicle vibration mode has to be modelled. These include: the nonstationary random vibration induced by road roughness and speed variations, the transient vibration created by road surface aberrations and the harmonic vibration created by the vehicle engine and drive train. Identifying and indexing these mixed-modes within complex road vehicle vibration signals is essential to define the severity and occurrence of the different modes in order to develop an accurate model. This paper shows that indexing can be performed using the orthogonal wavelet transform such as Daubechies 10. Assuming that each mode is preponderant in different analysis scales, the wavelet coefficients can be used to perform the indexing. This allows more sensitive mode detection and a more precise time indexing thanks to the multi-resolution nature of the wavelet transform compared to other time-frequency analysis methods.

Reducing tire noise has been a topic of increased focus in the recent years in industrial countries in order to decrease road traffic noise. Computational fluid dynamics (CFD) simulations conducted using ANSYS FLUENT are presented here to provide a better understanding of the small-scale noise generation mechanisms due to air-pumping at the tire-road interface. The CFD model employs a large eddy simulation (LES) turbulence modeling approach, where the filtered compressible Navier-Stokes equations are solved for simple groove geometries with a moving bottom wall that represents the deformation due to the tire movement along the road surface. A horizontally moving wall is used to represent the motion of the tire groove in and out of the contact patch while the deformation of the groove is prescribed. Temporal and spatially accurate pressure fluctuations are utilized to determine sound pressure levels and dominant frequencies. In addition to an understanding of noise generation mechanisms in such grooves, the CFD model developed here can potentially provide a series of control parameters that can help optimize the tire performance in terms of tire acoustics.

Balcony acoustic treatments can be demonstrated to provide important benefits in reducing road traffic noise within the balcony space and consequently internally for any adjacent room. The actual effect on road traffic noise is derived from a multitude of variables that can be broadly categorized into (a) acoustical and (b) geometrical for two distinct propagation volumes being (i) the street space, and (ii) the balcony space. A series of recent research activities in this area has incorporated the use of a combined image and diffuse source model, which can be used to predict the effect of balconies on road traffic noise for large number of scenarios. This paper investigates and presents a method and capability to summarize predictive data into user friendly guidelines aimed for use by acoustical professionals and architects and possible implementation in building design policies for environmental noise. The paper concludes with a presentation of the likely format of a potential design guide.

Although tire/road noise and tire vibration phenomena have been studied for decades, there are still some missing links in the process of accurately predicting and controlling the overall tire/road noise and vibration. An important missing link is represented by the effect of rolling on the dynamic behavior of a tire. Consequently, inside the European seventh framework program, an industry-academia partnership project, named TIRE-DYN, has been founded between KU Leuven, Goodyear and LMS International. By means of experimental and numerical analyses, the effects of rolling on the tire dynamic behavior are quantified. This paper presents the results of vibration measurements on a rotating tire with an embedded accelerometer. Modal parameters of the rolling tire are estimated from an operational modal analysis. In addition, the dispersion curves, which give detailed insight in the wave propagation behavior of a structure, are analyzed for the rolling tire. The goal of these analyses is to deepen the understanding on the influence of rolling on the tire dynamic behavior.

This research examined the influence “quiet” (e.g., hybrid and electric) vehicles may have on the ability of blind pedestrians to perform common orientation and mobility tasks under low vehicle speed conditions. The research involved blind participants detecting forward approaching vehicles and approaching backing vehicles, deciding whether a vehicle coming from behind or from the front but across an intersection would continue to go straight or turn across the intended path of travel of a pedestrian seeking to cross a street (i.e., a pathway discrimination task), and taking parallel and perpendicular alignment from passing traffic. Participants included some with normal hearing and some with impaired hearing. Testing was conducted on a public roadway and a parking lot in Kalamazoo, Michigan under ambient sound conditions consistent with a typical urban travel environment. Conditions involved evaluating internal combustion engine (ICE) Chevrolet Malibu and a set of hybrid Chevrolet Volts capable of operating in a “quiet” mode (referred to as Electric Mode or EM) or operating in EM but augmented with one of five different artificially-generated sounds emanating out of a front-bumper mounted speaker. All of the artificial sounds generally performed better against the baseline the Chevrolet Volt EM than the Chevrolet Malibu. This suggests that, to some extent, putting any one of these artificial sounds on a hybrid or electric vehicle may improve pedestrian performance on the measures examined relative to not adding any sound at all. One sound (sound 5) did not outperform against the Chevrolet Malibu in any measure and had the fewest instances of outperforming the Chevrolet Volt EM. Of the remaining 4 sounds, two sounds outperformed both the Chevrolet Malibu and the Chevrolet Volt EM on several measures. Against the Chevrolet Malibu, sound 2 was slightly better in detection distance and crossing margin while sound 4 was better in the path discrimination tasks. The two sounds were equivalent on the alignment tasks. The pathway discrimination task reflects one of the more potentially threatening situations in which a blind pedestrian might encounter a quiet vehicle (e.g., turning to cross the pedestrian’s path). Sound 4 performed much better than sound 2 on this measure, making it the most effective of all the artificial sounds examined. While these two sounds were equitable in the right-straight task, sound 4 showed almost half as many missed vehicle surges (i.e., forward movement from a stop) and 1/4 the rate of missed paths and incorrect judgments. Vehicle sound condition did not impact participants’ alignment. Normal hearing participants performed significantly better than hearing impaired participants on this task, but not as well as would be expected based on previous data [1]. These results support the potential for artificially-generated sounds to improve the ability of blind pedestrians to detect approaching vehicles relative to what is being achieved with ICE vehicles. Regression analysis of the detection data supports previous results that sound energy in the 500 to 1000 Hz range is important for detection. However, the analysis indicates it is not that energy in this region that makes the signal more noticeable, but that energy in this region in the ambient environment hinders detection. Previous findings in low ambient conditions showing a predictive value for the amplitude modulation of an artificial sound were not supported in these data.

This study contrasts two modeling techniques proposed to accurately predict the influence of sintered fibrous metal (a non-woven structure of metallic fibers attached to one another by sintering processes), as a liner substitute, on sound attenuation performance and resulting noise emission for conventional aftermarket dissipative mufflers. Predicted values are compared to sound measurement data from stationary engine exhaust tests of a commercially available single-cylinder 450cc off-road motorcycle. The performance prediction techniques rely on the appropriate application and combination of pre-existing silencer design, engine exhaust and gas flow performance models as an economic alternative to more complex and expensive modeling programs that are typically beyond the reach of most small to medium-sized businesses in the motorcycle aftermarket industry. With respect to test results that showed approximate acoustical parity between mufflers containing the two different liner types, application limitations on the most suitable prediction technique are presented along with suggestions for further model refinement or additional physical testing. Further research is also invited to explore the impact of this liner substitution on muffler backpressure and its consequential impact on realized engine power.

The consumer today places greater demands upon the vehicle acoustical engineer than in the past. Product quality has always been associated with a quiet ride. Automotive engineers recognize that the predominant sources of vehicle interior noise are wind, tire-road or rolling noise, and the powertrain. This paper suggests a test protocol for measuring wind and rolling noise using a chassis rolls dynamometer and road tests. Automotive engineers are frequently confronted by customer complaints concerning wind noise. Usually, engineers resort to using wind tunnels to address these concerns and to conduct diagnostic studies to remedy wind noise problems. Unfortunately, wind tunnels are expensive to rent and difficult to schedule. As an alternative, the engineer can learn a great deal about the wind noise of a vehicle by using a chassis rolls dynamometer along with road tests [1,2]. If the chassis rolls surface texture closely matches that of the road surface, the tire-road or rolling noise signal in both situations can be assumed to be equivalent. The powertrain noise source can be minimized by shifting the vehicle into neutral and coasting. Wind noise is a source for the road measurements, but not for the chassis rolls. Hence, the wind noise can be calculated by measuring the cab interior noise for both operating conditions, and subtracting the rolling noise measured on the chassis rolls. The two vehicles tested in this study included a pickup truck and a sport utility vehicle. The acoustical data revealed significantly different rolling and wind noise characteristics. The pickup truck had significantly louder rolling noise, and the wind noise was dominated by low frequency sound. The sport utility vehicle was much quieter overall and was significantly quieter for rolling noise than the pickup. The wind noise of the sport utility vehicle also was dominated by high frequency components. Both vehicles showed that rolling and wind noise trends increase linearly with speed. However, the slope of wind noise data for the sport utility vehicle was much steeper than the pickup, which suggested that it was more sensitive to wind noise as speed increased. Exterior noise data from both vehicles showed that the tire-road signal from the road differed significantly from that of the chassis rolls dynamometer. Rolling & wind noises will become even more critical as the motor vehicle industry adopts hybrid electric and, in the future electric fuel cell vehicles, because powertrain noise sources in the vehicle will likely be reduced. The procedure suggested here provides an inexpensive simple approach to assessing rolling and wind noise in the vehicle.

This paper describes the development of a new method for measuring pass-by sound from trucks and other vehicles using 2-dimensional arrays. The approach provides 2-dimensional quantitative maps “images” of the cross-range and elevation distribution in the vehicle side view. The method is an application and extension of an array technology that was originally used for the characterization of static aeroacoustic sources in wind tunnels. The focus of this work is on identifying and rank-ordering the important contributing sources of passby noise. This development includes two phases: developmental testing at a test track site, and road-side testing at two California State highway sites. The acquisition post-processing allows the “observer” to track the vehicle cross-range in order to create a time sequence of source maps that may be interpreted as both level relationships and directivity patterns. The processing applies both range and approximate Doppler adjustments to spectra as a function of time during pass-by or, equivalently, to vehicle position relative to the array’s center. An image demodulation scheme is shown to clarify the images. The initial phase of this work occurred at a test track using known “cooperative” truck sources. This experience permitted the verification of the method and the definition of a final measurement approach that was viable at a highway site. Subjects were all trucks that varied in model, vehicle speed, tread, and the presence of a trailer. The array beamformer’s ability to localize and the measurement system’s ability to track were validated using both stationary and moving sources. Following validation at the test track site, the instrumentation was transferred to two California highway sites. There, acoustic calibration was used to align the array with the road track and to provide a spatial reference for mapping the “images”. Both light and heavy vehicles at these sites were “uncooperative” with arrivals and speeds randomly determined by traffic flow. This work was funded by the California Department of Transportation.