An Approach to RANS Based Prediction of Airfoil Trailing Edge Far-Field Noise
M. Kamruzzaman, Th. Lutz and E. Krämer
Second International Meeting on Wind Turbine Noise, Lyon France September 20-21 2007
This paper describes a prediction scheme for the airfoil Turbulent Boundary Layer Trailing-Edge Interaction (TBL-TE) far-field noise to be applied for the combined aerodynamic and aeroacoustic airfoil design process. The model presented here follows the spectral solution of the Poisson equation for the surface pressure fluctuations underneath a turbulent boundary layer and evaluation of the noise emission from the trailing edge due to this fluctuating pressure by solving the diffraction problem. The final form of the model is expressed as an integral of the turbulence sources over the boundary layer height and another integral in the wave number direction. In previous investigations, an efficient prediction method was developed and successfully applied to acoustic airfoil design. With that method the acoustic sources are calculated by means of the EDDYBL boundary layer code in combination to the XFOIL airfoil analysis method. Presently, a RANS flow solver together with an appropriate turbulence model is coupled with the noise prediction scheme for the determination of source input parameters, and to improve the accuracy and consistency. The main advantage of the present RANS based approach is that a linearized viscous-inviscid coupling is avoided. Both approaches enable direct derivation of the required turbulence properties by means of different two equations and full Reynolds stress models. As a result the anisotropic behaviour of the turbulence noise source parameters can be analysed elaborately. Moreover, detailed investigations and a comparison study are carried out with the calculated noise spectra and source parameters (i.e. turbulent boundary layer parameters, vertical fluctuation velocity and integral length scale), and the experimental results obtained in the institute's Laminar Wind Tunnel (LWT). Encouraging results are obtained. The prediction scheme will be applied further in the design process of low noise airfoils.