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Target setting at Body-In-White (BIW) level is typically done for natural frequencies of global modes. Target values are commonly set based on experience or from benchmark studies with competitor vehicles. A link between these targets at BIW level and the vibro-acoustic targets at Trimmed Body (TB) level is not yet well established. Therefore, it is not always guaranteed that the TB targets will be met when the targets at BIW level are reached. Also, the other way around, not reaching a frequency target for a certain BIW mode does not necessarily imply that TB targets will not be met. Hence, there is a clear need for getting more insights in the relation between BIW dynamic properties and TB vibration behavior. In this paper techniques will be presented that establish the link between BIW and TB dynamic behavior. In addition, a large DOE campaign has been carried out to further link these dynamic properties to specific areas in the body design.

The prediction of the acoustic radiation of vibrating structures is traditionally based on the acoustic boundary element method. This approach leads to good predictions, provided that the dynamic behavior of the system is well known. This paper presents the integration of experimental vibration analysis with numerical acoustic radiation prediction. The developed methodology involves several steps: (i) measure the accelerations on the surface of a vibrating body, (ii) expand these experimental data onto a numerical model, using the modal information of a finite element model, and (iii) run a boundary element analysis to determine the acoustic radiated field. This procedure presents the advantages that the dynamic behavior is as accurately as possible defined and that the boundary element approach opens wide results interpretation (contribution and sensitivity analysis…). A real-life application example (car engine) is shown to illustrate and validate the developed methodology.

This paper presents a model updating method based on experimental receptances. The presented method minimises the so called ‘indirect receptance difference’. First, the reduced analytical dynamic stiffness matrix is expressed as an approximate, linearised function of the updating parameters. In a numerically stable, iterative procedure, this reduced analytical dynamic stiffness matrix is changed in such a way that the analytical receptances match the experimental receptances at the updating frequencies. The updating frequencies are a set of selected frequency points in the frequency range of interest. Some considerations about an optimal selection of the updating frequencies are given. Finally, a mixed static-dynamic reduction scheme is discussed. Dynamic reduction of the analytical dynamic stiffness matrix at each updating frequency is physically exact, but it involves a great computational effort.