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This paper describes a practical approach to extract the global static stiffness of a body in white (BIW) from dynamic measurements in free-free conditions. Based on a limited set of measured frequency response functions (FRF), the torsional and bending stiffness values are calculated using an FRF based substructuring approach in combination with inverse force identification. A second approach consists of a modal approach whereby the static car body stiffness is deduced from a full free-free modal identification including residual stiffness estimation at the clamping and load positions. As an extra important result this approach allows for evaluating the modal contribution of the flexible car body modes to the global static stiffness values. The methods have been extensively investigated using finite element modeling data and verified on a series of body in white measurements.

Despite the fact that Transfer Path Analysis (TPA) is a well known and widely used NVH tool it still has some hindrances, the most significant being the huge measurement time to build the full data model. For this reason the industry is constantly seeking for faster methods. The core concepts of a novel TPA approach have already been published in a paper at the ISMA 2008 Conference in Leuven, Belgium. The key idea of the method is the use of parametric models for the estimation of loads. These parameters are frequency independent as opposed to e.g. the classical inverse force identification method where the loads have to be calculated separately for each frequency step. This makes the method scalable, enabling the engineer to use a simpler model based on a small amount of measurement data for quick troubleshooting or simply increase accuracy by a few additional measurements and using a more complex model.

Source identification applied to a truck engine and using inverse numerical acoustics is presented. The approach is based on acoustic transfer vectors (ATV) and truncated singular value decomposition (SVD). Acoustic transfer vectors are arrays of transfer functions between surface normal velocity and acoustic pressure at response points. They can be computed using boundary element methods (indirect, direct or multi-domain direct formulations) or finite element methods (in physical or modal coordinates). Regularization techniques such as the so-called L-curve approach are used to identify the optimum SVD truncation. To increase the reliability of the source identification, the approach can use velocity measurements on the boundary surface as well as the standard nearfield pressure measurements. It also allows for linear or spline interpolation of the acoustic transfer vectors in the frequency domain, to increase computational speed.