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The analysis of the acoustic behavior of flow fields has gained importance in recent years, especially in the automotive industry. The comfort of the driver is heavily influenced by the noise levels and characteristics, especially during long distance drives. Simulation tools can help to analyze the acoustic properties of a car at an early stage of the development process. This work focuses on the low-frequency sound effects, which can be a significant noise component under certain operating conditions. As a first step in the fluid-structure interaction workflow, the flow around a series-production vehicle is simulated, including passenger cabin and underhood flow. The complexity of this model poses extensive demands on the simulation software, concerning meshing, turbulence modeling and level of parallelism. We conducted a transient simulation of the compressible fluid flow, using a hybrid RANS/LES approach.

In many application fields, such as automotive and aerospace, the full FE Biot model has been widely applied to vibro-acoustics problems involving poro-elastic materials in order to predict their structural and acoustic performance. The main drawback of this approach is however the large computational burden and the uncertainty of the input data (Biot parameters) that may lead to less accurate prediction. In order to overcome these disadvantages industry is asking for more efficient techniques. The vibro-acoustic behaviour of structures coupled with poroelastic trims and fluid cavities can be predicted by means of the Patch Transfer Function (PTF) approach. The PTF is a sub-structuring procedure that allows for coupling different sub-systems via impedance relations determined at their common interfaces. The coupling surfaces are discretised into elementary areas called patches.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (> 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying 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 development of a reliable numerical prediction capability. The goal of this paper is to present a computational approach developed to predict the greenhouse windnoise contribution to the interior noise heard by the vehicle passengers. This method is based on coupling an unsteady Computational Fluid Dynamics (CFD) solver for the windnoise excitation to a Statistical Energy Analysis (SEA) solver for the structural acoustic behavior.

Comfort and well-being have always been connected with a flawless interior acoustic, free of any background noise or BSR, (buzz, squeak and rattle). BSR noises dominate the interior acoustic and represent one of the main sources for discomfort often causing considerable warranty costs. Traditionally BSR issues have been identified and rectified through extensive hardware testing, which by its nature intensifies toward the end of the car development process. In the following paper the integration of a virtual BSR validation technique in a modern development process by the use of appropriate CAE methods is presented. The goal is to shift, in compliance with the front loading concept, the development activities into the early phase. The approach is illustrated through the example of an instrument panel, from the early concept draft for single components to an assessment of the complete assembly.

It is shown in how far modal correction techniques can contribute to reduce the CPU effort in the scope of numerical structural-acoustic investigations. Due to this technique a quasi-online interactive acoustic optimization of a basic system configuration can be achieved. In this context special focus is pointed on structural optimization aspects. Finally, the limits of validity as to the accuracy of the results obtained by the modal correction approach in the case of larger modifications are determined.