the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Numerical Prediction of the Aerodynamics and Aeroacoustics of a Horizontal Axis Wind Turbine
Wen-Yu Wang
Yuh-Ming Ferng
Abstract. This study used low-frequency-based numerical methods to predict noise radiating from rotating horizontal axis wind turbine (HAWT) blades. ANSYS FLUENT was used to calculate flow parameters in the vicinity of blade surfaces, as required for the Ffowcs Williams–Hawkings (FW–H) equation. The numerical model was validated against the experimental results from the National Renewable Energy Laboratory Phase VI wind turbine blades. The coupling analysis was integrated with four Reynolds-averaged Navier–Stokes turbulence models and the FW–H equation under different boundary conditions. The SST k-ω and V2f turbulence models produced results in agreement with the available experimental pressure-coefficient and relative-velocity-distribution data. An INER 25-kW HAWT was employed to predict noise frequency distribution at nine points from the tower on the windward and leeward sides under different operating conditions. Noise frequency distributions on the windward and leeward sides showed little differences, whereas those on the left and right sides with respect to the tower were different owing to wind-shear influence. The peak amplitude of the noise was inversely proportional to the increasing distance from the tower but proportional to the wind and rotation speeds.
Wen-Yu Wang and Yuh-Ming Ferng
Status: open (until 13 Jun 2023)
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RC1: 'Comment on wes-2023-32', Anonymous Referee #1, 05 May 2023
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The paper presents a numerical method based on a commercial code to predict aerodynamic characteristics and noise emissions of HAWT. The CFD solution is coupled with FWH method to assess the noise spectrum at the observer locations. Different turbulence models are tested, and their results are compared with LES and experimental acquisitions.
The paper faces a very interesting problem related to the annoyance of wind turbines located near populated areas. The main aspects of the noise prediction method are touched by the authors, but the description of the single step is quite shallow and not complete.
For instance, the numerical method description is a general discussion of basic CFD concepts without a deeper discussion of the motivation behind setup choices. Classical PDE equations are reported with some typos (e.g. in Eq. 2 the time derivative term is missing), and also the turbulence model description is too detailed: references to the different model formulation should be enough. Same story for the FWH formulation.
Concerning the numerical model validation by using NREL HAWT, some important aspects of numerical simulation are missing: numerical schemes for diffusive and convective fluxes, detailed description od BCs., discussion about convergence criteria and so on. Moreover, is not crestal clear by looking at Fig. 3 that fine mesh performs better in terms of accuracy. Could the authors better explain their conclusions?
Moving to the INER 25-kW turbine, some aspects of the operating conditions are not so clear: why the rotational speed is expressed in m/s? Should it read rad/s or rpn? When the authors discussed the aerodynamic results, they compared the different turbulence model, without discussing the results in detail. Could the author make a thorough discussion of this? Finally, the comparisons on Fig.12 show some discrepancies, could the authors comment on that?
Concerning the noise prediction section, t is not clear how the CFD simulations used for noise predictions are performed. Do they rely on steady or unsteady simulations? Also, the FWH setup is not completely described: where the FWH surface is placed? Which is the sampling rate of the FFT? Moreover, is quite strange to see noise spectra with negative value in dB (that is under the human hearing threshold). In addition, is there a blade passing frequency in the spectra? If so, please discuss a bit on this aspect.
Finally, an English revision of the wording is highly suggested.
Citation: https://doi.org/10.5194/wes-2023-32-RC1
Wen-Yu Wang and Yuh-Ming Ferng
Wen-Yu Wang and Yuh-Ming Ferng
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