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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.

This paper discusses the development of a computationally efficient numerical method for predicting the acoustics of rattle events upfront in the design cycle. The method combines Finite Elements, Boundary Elements and SEA and enables the loudness of a large number of rattle events to be efficiently predicted across a broad frequency range. A low frequency random vibro-acoustic model is used in conjunction with various closed form analytical expressions in order to quickly predict impact probabilities and locations. An existing method has been extended to estimate the statistics of the contact forces across a broad frequency range. Finally, broadband acoustic radiation is predicted using standard low, mid and high frequency vibro-acoustic methods and used to estimate impact loudness. The approach is discussed and a number of validation examples are presented.

A hybrid FE-SEA analysis method has been developed to predict the structural response of complex systems at mid and high frequencies. At these frequencies, the dynamic properties of some components might be very sensitive to small perturbations while other components might exhibit a very robust behavior. This mixed dynamic behavior precludes the use of fully statistical approaches like SEA [1] or fully deterministic approaches like FE. In the hybrid method, either an SEA or an FE model is applied to each component of the complex system, and both descriptions are rigorously coupled in a generic way. An overview of the method is presented along with numerical and experimental validation studies.