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In the automotive industry, the use of beading is widely spread. Beads are primarily used to stiffen the floor and dash panels. The aim is to reduce vibration levels and hopefully at the same time reduce radiated noise. Beading has a positive effect close to the first panel mode's natural frequency however it can have a negative effect at all other frequencies. Typically, engineers assume a radiation efficiency of “1” (one) over the whole frequency range for simplicity or lack of available implemented formulation in their simulation tools. This assumption directs the investigation at reducing the vibration levels only. This approach can be misleading because even though radiation efficiency tends to “1” (one) above coincident frequency it is not the case below coincidence. While increasing stiffness reduces vibration levels, it also increases radiation efficiency. This can yield to higher levels of radiated noise.

Integration of acoustic material concepts into vehicle design process is an important part of full vehicle design. The ability to assess the acoustic performance of a particular sound package component early in the design process allows designers to test various design concepts before selecting a final solution and long before a design freeze. This paper describes an innovative acoustic material concept which is easily integrated in a design process through the use of vibro-acoustic simulation and a database of intrinsic properties of acoustic materials: The Biot Parameters. Biot parameters are widely used in simulation in many industries (and used the most in the automotive industry) to describe the physical interactions between the acoustic waves travelling through foams, fibers or homogeneous metamaterials and the solid and fluid phase of these poro-elastic materials.

There are many software tools in use today that are implementing the Biot, or complementary, method for the evaluation of foam and fiber materials. The justification of this process is to understand which mechanisms of the noise control material are contributing to the noise reduction and to optimize the material based on its acoustic properties. The disadvantage of this method is that it is quite complex and time consuming to test a material in order to extract the underlying properties that govern the acoustic performance. An alternative inverse method for material characterization based on simple impedance tube measurements has been developed lately. This paper recalls the physics and mathematics behind the method and concentrates on its validation.

This paper presents new advances in predicting wind noise contribution to interior SPL in the framework of the Wind Noise German Working Group composed of Audi, Daimler, Porsche and VW. In particular, a new approach was developed that allows to fully describe the wind noise source using CFD generated surface pressure distribution and its cross-correlation function and apply this source on an SEA side glass. This new method removes the need to use a diffuse acoustic field or several plane waves with various incidence angle to approximate the correct acoustics source character to apply on the SEA side glass. This new approach results are compared with results previously published which use more deterministic methods to represent the side glass and the interior of a vehicle.

There are many applications in which exterior flow over a structure is an important source for interior noise. In order to predict interior “wind noise” it is necessary to model both: (i) the spatial and spectral statistics of the exterior fluctuating surface pressures (across a broad frequency range) and (ii) the way in which these fluctuating surface pressures are transmitted through a structure and radiated as interior noise (across a broad frequency range). One approach to the former is to use an unsteady CFD model. While CFD is used routinely for external aerodynamics, its application to the characterization of exterior fluctuating surface pressures for broadband interior noise problems is relatively new. Accurate prediction of both the convective and acoustic wavenumber content of the flow across a broad frequency range can therefore present some challenges.

Recent developments in the prediction of the contribution of wind noise to the interior SPL have opened a realm of new possibilities in terms of i) how the convective and acoustic sources terms can be identified, ii) how the interaction between the source terms and the side glass can be described and finally iii) how the transfer path from the sources to the interior of the vehicle can be modelled. This paper discusses in detail these three aspects of wind noise simulation and recommends appropriate methods to deliver required results at the right time based on i) simulation and experimental data availability, ii) design stage and iii) time available to deliver these results. Several simulation methods are used to represent the physical phenomena involved such as CFD, FEM, BEM, FE/SEA Coupled and SEA.

The need in the automotive industry to understand the physical behavior of trims used in a vehicle is high. The PEM (poro-elastic method) was developed to permit an explicit representation of the trims in the FEM full vehicle models and to give tools to diagnose the effect of the trims and test design changes (porous material property, geometry, etc.,). During the last decade, the evolution of software and hardware has allowed the creation of models with highly detailed trim description (porous material using Biot parameters, plastic trims, etc.,). These models can provide good correlation up to 400Hz compared to measurements in contrast to classical NSM (Non Structural Mass) methodology which shows limitations.

Since the last decade, the automotive industry has expressed the need to better understand how the different trim parts interact together in a complete car up to 400 Hz for structureborne excitations. Classical FE methods in which the acoustic trim is represented as non-structural masses (NSM) and high damping or surface absorbers on the acoustic cavity can only be used at lower frequencies and do not provide insights into the interactions of the acoustic trims with the structure and the acoustic volume. It was demonstrated in several papers that modelling the acoustic components using the poroelastic finite element method (PEM) can yield accurate vibro-acoustic response such as transmission loss of a car component [1,2,3]. The increase of performance of today's computers and the further optimization of commercial simulation codes allow computations on full vehicle level [4,5,6] with adequate accuracy and computation times, which is essential for a car OEM.

Recent developments in the prediction of the contribution of wind noise to the interior SPL have opened a realm of new possibilities. The main physical mechanisms related to noise generation within a turbulent flow and the vibro-acoustic transmission through the vehicle greenhouse is nowadays better understood. Several simulation methods such as CFD, FEM, BEM, FE/SEA Coupled and SEA can be coupled together to represent the physical phenomena involved. The main objective being to properly represent the convective and acoustic component within the turbulent flow to ensure proper computation of the wind noise contribution to the interior SPL of a vehicle.

It is well known today that Biot parameters are the intrinsic material properties of porous media such as foams and fibers. They are to porous media what Young’s modulus is to steel panels. Once these Biot parameters are accurately known, one can trust that a predictive simulation model will yield the corresponding level of accuracy. But how accurate must these Biot parameters be to warrant a safe level of accuracy of the resulting simulation models? This paper analyzes various round-robin tests publications related to measurements of Biot parameters (acoustic and elastic) and uses the reproducibility of measured data from the numerous laboratories involved to evaluate the effect of the observed measured variability on simulation models accuracy when predicting transmission loss, surface absorption and actual sound pressure level (SPL) response inside a vehicle.