CAA-based acoustic beamforming for noise identification in complex media

Vincent Fleury (1) , Daniel Mincu (1) , Cyril Polacsek (1)

1 ONERA - The French Aerospace Lab [Châtillon]

Beamforming methods use analytical Green functions to describe the acoustic propagation between noise sources and microphones. For example, due to flow heterogeneity and complex boundary conditions, the Green functions become analytically difficult to determine in the case of a realistic turbofan engine. The aim of this work is to overcome the analytical Green functions determination difficulties by employing CAA tools. In order to numerically evaluate these functions, we propose a method based on non linear euler equations implemented in the Onera's sAbrinA-v0 code. The noise source area is sampled as a finite distribution of monopoles which emit simultaneously. The sound field is then computed from the source points to the microphones. An ARMA based algorithm is applied to evaluate Green functions betweenn each monopole and each microphone. First of all, the approach is validated from analytical simple test cases, such as the propagation of a monopole in uniform flow. Once achieved, more delicate problems will be processed, such as the presence of multiple sources, flow gradients and complex geometries.

Mots clés: CAA; Green functions; Turbofan; Beamforming

Domaines: Acoustique [physics.class-ph]

Vincent Fleury, Daniel Mincu, Cyril Polacsek. CAA-based acoustic beamforming for noise identification in complex media. Acoustics 2012, Apr 2012, Nantes, France. ⟨hal-00811126⟩