Prediction and reduction of wind turbine noise - An overview of research activities in Europe

Guidati, Gianfranco; Ostertag, J.; Wagner, S.

doi:10.2514/6.2000-42

Cited by 18 publications

(7 citation statements)

References 1 publication

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“…For low Mach number flows without strong temperature inhomogeneities, as is the case for slat noise applications where the typical flow Mach number is about 0.2, the Lighthill stresses tensor can be reduced to 23,24,26 where 0  is the ambient density. []…”

Section: The Source Modelingmentioning

confidence: 99%

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Prediction of Slat Broadband Noise with RANS Results

Bai

Guo

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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This paper presents a RANS-based far field broadband noise prediction method for flow generated noise in low Mach number and high Reynolds number, such as slat noise. The compressible Navier-Stokes equations were linearized and reformulated firstly for acoustic generation and propagation. Then the far field noise power spectral density formulation was obtained, which relates the far field noise spectrum to the volume statistics and the exact Green's function that accounts for the sound flow coupling and propagation effects, including the diffraction and scattering effects caused by solid surfaces and the refraction effects by nonuniform flow. The adjoint Green function method was employed for the fast exact Green function computation. A semi-analytical and semi-numerical method was proposed to tackle the nearly singularity problem appeared in the computation of exact Green function. Thus, the homogeneous and isotropic turbulence was assumed for the source modeling based on the mean flow and turbulence statistics from RANS. Finally the method was applied into the prediction of slat broadband noise based on the mean flow of 30P30N multi-element airfoil at four degree of angle of attack under the uniform mean flow assumption. The computation of spatial source distribution demonstrates the downstream moving of the source location to reattachment region and the decreasing of the spatial dimension of source with the increase of the frequency. The comparison between the predicted spectral and the modeled spectral shows a good agreement in peak frequency and the middle frequency range, and demonstrate the accuracy of the method.

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Section: The Source Modelingmentioning

confidence: 99%

“…26 So the fourth-order correlation can be reduced to second-order correlations as shown in the second equality. 26 So the fourth-order correlation can be reduced to second-order correlations as shown in the second equality.…”

Section: The Source Modelingmentioning

confidence: 99%

Prediction of Slat Broadband Noise with RANS Results

Bai

Guo

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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“…For predicting trailing edge noise from rotating airfoil systems, the semi-empirical Brooks, Pope and Marcolini (BPM) model by Brooks et al 10 is commonly used. [11][12][13] This model was developed based on NACA 0012 airfoil experimental data at various angles of attack and Reynolds numbers ranging from 0.069 Â 10 6 to 1.47 Â 10 6 . Interestingly, despite the model simplicity, the experimental data obtained across various facilities compare well with the BPM model as observed by Doolan and Moreau.…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation of trailing edge noise from stationary and rotating airfoils

Zajamšek

Doolan

Moreau

et al. 2017

The Journal of the Acoustical Society of America

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Trailing edge noise from stationary and rotating NACA 0012 airfoils is characterised and compared with a noise prediction based on the semi-empirical Brooks, Pope, and Marcolini (BPM) model. The NACA 0012 is symmetrical airfoil with no camber and 12% thickness to chord length ratio. Acoustic measurements were conducted in an anechoic wind tunnel using a stationary NACA 0012 airfoil at 0° pitch angle. Airfoil self-noise emissions from rotating NACA 0012 airfoils mounted at 0° and 10° pitch angles on a rotor-rig are studied in an anechoic room. The measurements were carried out using microphone arrays for noise localisation and magnitude estimation using beamforming post-processing. Results show good agreement between peak radiating trailing edge noise emissions of stationary and rotating NACA 0012 airfoils in terms of the Strouhal number. Furthermore, it is shown that noise predictions based on the BPM model considering only two dimensional flow effects, are in good agreement with measurements for rotating airfoils, at these particular conditions.

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“…Efforts to quantify wind turbine noise have been ongoing for the past three decades [3,4,5]. There are two primary classes of noise sources on a wind turbine.…”

Section: Wind Turbine Aerodynamic Noisementioning

confidence: 99%

Survey of techniques for reduction of wind turbine blade trailing edge noise.

Barone¹

2011

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Aerodynamic noise from wind turbine rotors leads to constraints in both rotor design and turbine siting. The primary source of aerodynamic noise on wind turbine rotors is the interaction of turbulent boundary layers on the blades with the blade trailing edges. This report surveys concepts that have been proposed for trailing edge noise reduction, with emphasis on concepts that have been tested at either sub-scale or full-scale. These concepts include trailing edge serrations, low-noise airfoil designs, trailing edge brushes, and porous trailing edges. The demonstrated noise reductions of these concepts are cited, along with their impacts on aerodynamic performance. An assessment is made of future research opportunities in trailing edge noise reduction for wind turbine rotors.3 4

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Prediction and reduction of wind turbine noise - An overview of research activities in Europe

Cited by 18 publications

References 1 publication

Prediction of Slat Broadband Noise with RANS Results

Prediction of Slat Broadband Noise with RANS Results

Experimental investigation of trailing edge noise from stationary and rotating airfoils

Survey of techniques for reduction of wind turbine blade trailing edge noise.

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