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On the noise prediction for serrated leading edges

Published online by Cambridge University Press:  03 August 2017

B. Lyu Open the ORCID record for B. Lyu [Opens in a new window]  and
M. Azarpeyvand
B. Lyu*
Affiliation:
Department of Engineering, University of Cambridge, Cambridge CB2 1PZ, UK
M. Azarpeyvand*
Affiliation:
Department of Mechanical Engineering, University of Bristol, Bristol BS8 1TR, UK
*
†Email addresses for correspondence: bl362@cam.ac.uk, m.azarpeyvand@bristol.ac.uk
†Email addresses for correspondence: bl362@cam.ac.uk, m.azarpeyvand@bristol.ac.uk
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Abstract

An analytical model is developed for the prediction of noise radiated by an aerofoil with leading-edge serration in a subsonic turbulent stream. The model makes use of Fourier expansion and Schwarzschild techniques in order to solve a set of coupled differential equations iteratively and express the far-field sound power spectral density in terms of the statistics of incoming turbulent upwash velocity. The model has shown that the primary noise-reduction mechanism is due to the destructive interference of the scattered pressure induced by the leading-edge serrations. It has also shown that in order to achieve significant sound reduction, the serration must satisfy two geometrical criteria related to the serration sharpness and hydrodynamic properties of the turbulence. A parametric study has been carried out and it is shown that serrations can reduce the overall sound pressure level at most radiation angles, particularly at small aft angles. The sound directivity results have also shown that the use of leading-edge serration does not significantly change the dipolar pattern of the far-field noise at low frequencies, but it changes the cardioid directivity pattern associated with radiation from straight-edge scattering at high frequencies to a tilted dipolar pattern.

JFM classification

Acoustics: Aeroacoustics Acoustics: Noise control
Type
Papers
Information
Journal of Fluid Mechanics , Volume 826 , 10 September 2017 , pp. 205 - 234
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Copyright
© 2017 Cambridge University Press 

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