Development of a Generalized Inverse Beamforming tool for Aeroacoustic source imaging in Wind Tunnel and Computational Environments

In the realm of aeroacoustic applications, precise and detailed analysis of acoustic phenomena is essential for enhancing the comprehension of aerodynamic sound emission mechanisms and the design and performance of aerodynamic devices and systems, such as wings and engines. In this particular context, beamforming is currently receiving significant attention within the scientific community due to its ability to distinguish and measure acoustic sources through the use of phased arrays. This study proposes the development of an innovative UI-based beamforming tool implementing the Generalized Inverse Beamforming (GIBF) technique, which is a promising method resolving coherent and incoherent sparse source distributions that especially occur in aerodynamics. This approach is designed to enable accurate and reliable measurements both in physical wind tunnels and Computational AeroAcoustics (CAA) simulations. Through a three-dimensional source-to-microphone propagation model, a novel three-dimensional source reconstruction approach is implemented and applied. To reconstruct, only the most significant eigenmodes are selected by an algorithm that decomposes the Cross Spectral Matrix into eigenvectors. The resulting linear system is then inverted using an iterative process that aims to promote sparsity by minimizing the L-1 norm. Multipoles are all considered and detected simultaneously, reducing the solution’s dependence on the specific source model imposed. This approach represents a substantial advancement with respect to the field’s state-of-art, enhancing the explanation of the physics behind the acoustic production. Furthermore, the propagation model is adjusted to incorporate the effects of convection of acoustic sources caused by the average flow. Additionally, in wind tunnel measurements, the presence of a boundary layer between the sources and the laboratory environment, where pressure measurements are conducted, is taken into account by implementing corrections. Details on the implementation of GIBF and its practical applications in fictitious and real-world scenarios are presented, demonstrating its effectiveness in characterizing and interpreting acoustic events. The results showcase the framework’s ability to offer deep insights into the origin and distribution of acoustic sources, thereby contributing to the enhancement of aerodynamic performance and noise reduction in various aeronautical applications.