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Statistical estimation of trailing edge noise from finite wall-mounted airfoils

Contributor(s): Material type: TextTextOnline resources: In: Acoustics 2016 Proceedings 9-11 November 2016, Brisbane, AustraliaAbstract: It is important to be able to accurately model the flow and noise generated by finite wall-mounted airfoil flows because of the many engineering applications in which these flows occur. One method for predicting turbulent trailing edge noise is the Reynolds-averaged Navier-Stokes based statistical noise model (RSNM) of Doolan et al. (Proceedings of 20th International Congress on Acoustics, ICA 2010). The RSNM method has previously been used successfully on a range of two-dimensional geometry-flow cases. In this paper a new turbulent velocity cross-spectrum model and improved implementation are proposed to allow the RSNM method to be used to effectively and efficiently predict turbulent trailing edge noise from more complex three-dimensional cases. Reynolds-averaged Navier-Stokes (RANS) simulations of a series of wing-in-junction cases are used in combination with the developed acoustic model to predict the far-field noise and compared against experimental noise measurements.
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It is important to be able to accurately model the flow and noise generated by finite wall-mounted airfoil flows because of the many engineering applications in which these flows occur. One method for predicting turbulent trailing edge noise is the Reynolds-averaged Navier-Stokes based statistical noise model (RSNM) of Doolan et al. (Proceedings of 20th International Congress on Acoustics, ICA 2010). The RSNM method has previously been used successfully on a range of two-dimensional geometry-flow cases. In this paper a new turbulent velocity cross-spectrum model and improved implementation are proposed to allow the RSNM method to be used to effectively and efficiently predict turbulent trailing edge noise from more complex three-dimensional cases. Reynolds-averaged Navier-Stokes (RANS) simulations of a series of wing-in-junction cases are used in combination with the developed acoustic model to predict the far-field noise and compared against experimental noise measurements.

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