Weight Minimization of Sound Packages by Balancing Absorption and Transmission Performance
Abstract
Generally, heavier noise control treatments are favored over lighter ones since heavier acoustical materials tend to insulate (block) noise sources more effectively than do lighter materials. In automotive applications, however, heavier materials cannot always be adopted because of concerns over the total weight of the vehicle. Thus, it would be useful to identify lightweight acoustical treatments that can mitigate vehicle interior noise. Automotive sound packages have both absorption and barrier characteristics, and there is inevitably a trade-off between these two. Therefore, it is important to study the exchange between the absorption and transmission of acoustical materials particularly as it pertains to weight. Here, a procedure based on plane wave analysis is described that can be used to identify weight reduction opportunities by adjusting the acoustical properties of a generic sound package, consisting of a fibrous layer and a flexible microperforated panel surface treatment, so that it meets a target sound pressure level in a downstream interior space. It has been found, for the configuration studied here, that there are lightweight sound package configurations that can maintain acoustical performance equivalent to that of heavier noise treatments, and further, it has been found that the lightest treatments tend to favor barrier performance rather than absorption. Further, the impact of acoustical leaks has been considered, and it has been found that even very small leaks can result in a very substantial weight penalty if a specified level of acoustical performance is to be ensured. Further, the impact of changing the underlying panel mass and altering the frequency weighting used in the optimization process has also been considered.The optimizer used in the proposed procedure requires considerable calculation time; hence, the acoustic pressure calculation time needs to be minimized to enhance the efficiency of the solution process. Thus, the transfer matrix method (TMM) for a two-dimensional case was used to calculate the interior acoustic pressure for a simple geometry as a starting point in the process of identifying the minimum-weight sound packages. The TMM is a widely used analytical approach to predicting the sound pressure (and particle velocity) for a system that can be represented as a series of subsystems. Although the TMM can offer fast and simple calculations for the acoustic system, its application is limited to a plane-wave-based model. Thus, the TMM is not the best option for the acoustic pressure prediction in a complex geometry such as a vehicle interior, that involves non-planar wave propagation. Therefore, a hybrid TMM-FEA method is proposed in this research to evaluate the acoustical performance of the sound package in more complex geometries (here, a vehicle-like cavity). So, in this research, the TMM was introduced to obtain the initial solutions that can be used in conjunction with the FEA tool to calculate the sound pressure field in the complex geometry case. The correlation between the results of these two approaches was then analyzed to develop a space-averaged pressure prediction model for various absorptive cases in the interior space. Finally, this SAP prediction model was used to generate an acoustic map that can be used to graphically estimate the SAPs in the complex geometry case.In order to validate the usage of the developed equation for different sets of boundary conditions, several case studies were performed to study the effects of the surface impedance arrangements, geometrical shapes, and, lastly, the presence of extra features in the interior space. Finally, the SAP difference between the area near the driver’s right ear and the total interior cavity was studied to show that the SAP of the total cavity can be adjusted to evaluate the acoustic performance of the sound packages along the lines of conventional industry practice.
Degree
Ph.D.
Advisors
Bolton, Purdue University.
Subject Area
Acoustics|Artificial intelligence|Design|Energy|Materials science|Packaging
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