Abstract
The reduction of acoustic emission is one very important topic in product development of rotating sound sources and should be considered in early stages of development. Rotating airfoils of helicopter blades (Farassat in Theory of noise generation from moving bodies with an application to helicopter rotors. Langley Research Center, Harnpton, 1975 [7]), rotating wind turbines (Ramachandran et al. J Sound Vib 14:3058–3080, 2014 [19]) or fan blades (Dougherty in Locating and quantifying broadband fan sources using in-duct microphones. In: 16th AIAA/CEAS aeroacoustics conference, 2004 [5]), (Minck et al. in Fan noise analysis using a microphone array. In: Fan 2012—international conference on fan noise, technology, and numerical methods, 2012 [15]), (Herold and Sarradj Noise Control Eng J 63(6):546–551, 2015 [10]) cause unwanted noise. In this paper, a method is presented that allows the localization of stationary and rotating sound sources in the CFD simulation process. This enables a more detailed view on the geometry and offers a basic approach for an optimization concerning the localization and visualization of sound sources using a microphone array with suitable beamforming algorithm. A virtual microphone array (acoustic camera) is built in the CFD simulation and coupled to various beamforming codes. The method is presented on a rotating dipole (cylinder) and the results are compared to measurements with a real microphone array. To resolve the acoustical scales large eddy simulations (LES) are performed. The pressure data of the microphones is exported and the localization of the sound sources can be done in a post-processing procedure in an early stage of development with numerical software like Matlab or GNU Octave. Both time domain algorithms with retarded time (Maier in Practical and theoretic aero-acoustics, 2013 [14]) and frequency domain algorithms (Pannert and Maier in J Sound Vib 333(7):1899–1912, 2014 [17]) can applied to the CFD simulation data to visualize sound sources. Here the time domain version is used. With this approach, a method is presented that examined a rotating cylinder from a LES Fluent simulation with a rotational speed of 702 rpm anti clockwise that rotates at a radius of 0.48 m. This rotating dipole emits sound that the microphone array can visualize and assigning to the cylinder sound. By post processing these data it is possible to visualize the sound emitted by the cylinder. The novelty of this work is the visualization of rotating sound sources of a CFD Large Eddy Simulation.
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