Acoustic Simulation of Side Mirror Noise With Adaptive Spectral Reconstruction
A new method called Adaptive Spectral Reconstruction (ASR) for the stochastic reconstruction of broadband aeroacoustic sources starting from steady CFD analyses is presented and applied to the evaluation of the noise radiated by a model automotive side mirror.
The new approach exploits some ideas from both SNGR and RPM, and for some aspects can be considered as a sort of mixing between the two methods since it permits to reconstruct of both the frequency content of the turbulent field (as done by SNGR) and the spatial cross-correlation (as done by RPM).
The turbulent field is reconstructed with a sum of convected plane waves, but two substantial differences are introduced in respect of SNGR. The first difference concerns the spatial variation of the parameters that define each wave, which depends on the wavelength of each wave, rather than being kept constant or related to the CFD correlation length. The second innovative aspect is the usage of a dedicated full hexa adaptive mesh that is refined in the function of the expected local correlation length, ensuring that the mesh is enough refined to capture the relevant acoustic length scales.
The method is here applied to the evaluation of a classical side mirror model test case, and results are presented in terms of comparisons with measurements for both in-plane and out-of-plane microphones. Visualizations of reconstructed acoustic sources are also presented.
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Posted by Piergiorgio Ferrante
Piergiorgio Ferrante earned a master’s degree in Aeronautical Engineering at the Polytechnic of Milan. He worked for more than a decade in design, simulation, and testing of low noise technologies for turbofan aero-engine nacelles, within an industrial company active in aeronautics. He is currently an spplication engineer in the Acoustic Group at NUMECA International (Brussels).