Turbulent Boundary Layer-trailing Edge Research Articles

Hybrid control of aerofoil self-noise by coupling air blowing and trailing-edge serration

Active and passive control methods have been extensively studied and employed for reducing turbulent-boundary-layer (TBL) trailing-edge (TE) noise of aerofoils, for example air blowing and TE serration. To further explore the potential of noise reduction, this paper proposes a hybrid method coupling blowing and serration at the trailing edge, and investigates the effects of air blowing, TE serration, and the hybrid blowing-serration (HBS) on the TBL TE noise of a NACA0012 aerofoil at a Reynolds number of Rec=4×105. Large eddy simulation and Ffowcs Williams–Hawkings acoustic analogy were used to analyse these effects and the respective noise reduction mechanisms. The numerical results show that the HBS method exhibits superior acoustic performance to the blowing and serration methods, with a maximum reduction of 20.5 dB in broadband noise and 5.7 dB in overall sound pressure level. It is revealed that the HBS method functions primarily through three noise reduction mechanisms. Firstly, blowing eliminates the outward flow motion at the serration root and tip, resulting in a forced flow alignment. Secondly, it weakens the turbulence energy in the near wake as for air blowing. Finally, this method mitigates spanwise coherence at the trailing edge, thereby causing destructive interference of noise sources, similar to the effect of TE serration.

Airfoil self-noise prediction using deep neural networks

This study explores the prediction of airfoil self-noise through Deep Learning whilst focusing more specifically on the so-called turbulent boundary layer trailing edge (TBL-TE) noise. To this end, a predictive model relying on a Deep Neural Network (DNN) is developed, being then trained using an experimental database of TBL-TE noise signatures previously acquired by NASA. The DNN is favorably benchmarked against the test results, demonstrating its superiority over a popular semi-empirical prediction tool, i.e., the BPM model from NASA. Special attention is paid to the sensitivity of the DNN towards its architecture and/or its training extent. All in all, the DNN proves robust and accurate, reproducing faithfully the TBL-TE noise signatures with an average error of about 1.5 ∼ 2.5 dB in terms of Sound Pressure Level. Special attention is also paid to sensitivity of the DNN towards the composition of its training dataset, whose consistency is enforced by clustering all datapoints belonging to an identical test configuration. This allows evaluating how far the model constitutes a true prediction tool, i.e., can extrapolate the experimental database instead of merely interpolating it through overfitting. Finally, the sensitivity of the DNN towards its training data is further explored to tentatively discriminate which quantities constituting the experimental database may contribute more significantly to the correct prediction of the noise signatures and − by extension – to their underlying physical mechanisms.

Sensitivity Analysis of Wind Turbine Broadband Noise Estimation to Semi-Empirical Models Parameters

The continuous increase of energy demand and the rising concerns on climate change, are pushing the European Union decarbonization strategies and transition toward renewable based energy systems, with wind energy playing a leading role. It is therefore necessary to have a better understanding of how wind turbines (WTs) impact on their surroundings, including their noise emissions. Among the different methods to compute noise emissions of WTs, semi-empirical models are a valid choice to have a-priori estimations of noise spectra and sound pressure levels. These models are based on correlation laws for different physical mechanisms that contribute to noise generation. Popular models for dominant noise sources include the Amiet approach for inflow turbulence noise and the Lowson model for turbulent boundary layer-trailing edge noise. Determining the parameters involved in these models can be challenging, potentially leading to significant errors in noise prediction. In this study, we conducted a novel sensitivity analysis of the models by varying different parameters such as turbulent intensity and dissipation, boundary layer thickness, and temperature. The selected test case is the reference multi-MW horizontal axis wind turbine Neg-Micon 80. The results of the multilevel-multivariate analysis, involving 63,360 combinations of the input parameters, clearly demonstrate a significant dependence of these models on atmospheric turbulence parameters. Furthermore, these models exhibit an higher sensitivity to input parameters at lower frequencies of the noise spectrum, which are generally associated with higher values of sound pressure level.

Investigating the Effects of Tip Modification on High-Frequency Noise Emission of CART II Wind Turbine using a Hybrid Computational Aeroacoustic Approach

This study carries out computational aeroacoustic calculations around the tip region of the CART II wind turbine blade. Additionally, two modified tip designs, namely; tip O and tip R, are further investigated to determine how the geometry of the tip region affects the noise emission characteristics of the wind turbine. The study focuses on the tip vortex noise mechanism using hybrid computational aeroacoustic to tackle the issue of the enormous computational power required for direct noise simulation. Improved Delayed Detached Eddy Simulation (IDDES) technique is used to calculate the instantaneous turbulent flow field near the sound source region, and the noise prediction in far-field is performed using the Ffowcs Williams and Hawking’s (FW-H) acoustic analogy. The method visualizes the flow field near the blades’ tip, assisting researchers to have an accurate understanding of aerodynamically induced noise mechanisms in that highly complex flow region, thus being able to modify tip design in a way that contributes to lower overall noise emission. The results for the outboard section of the CART II wind turbine’s blade are validated with experimental data. Broadband noise sources such as turbulent-boundary-layer trailing-edge (TBL-TE) noise and the tip vortex noise mechanisms are investigated for the base case as well as tip O and tip R. The results show that the overall sound pressure level (OASPL) and the generated torque of tip R and tip O, are 2.0 %, 5.0 % and 0.8 %, 2.2 % lower than the base case, respectively.

Impact of Porous Media on Boundary Layer Turbulence

The subsonic flows around NACA 0012 aerofoils with a solid, a porous, and a poro-serrated trailing edge (TE) at a Reynolds number of 1 × 106 are investigated by a hybrid Reynolds-averaged Navier–Stokes (RANS)/large-eddy simulation (LES) approach. The porosity is treated by the method-of-volume averaging. In the RANS, a two-equation low Reynolds number k-ε turbulence model is modified to include the porous treatment. Similarly the equations in the LES are extended by the Darcy–Forchheimer model. The simulation is set up with the broadband turbulent boundary layer trailing edge (TBL-TE) noise prediction as a future objective in mind, i.e., the noise sources in the trailing edge region are captured by the LES. To enforce a physically realistic transition from an averaged RANS solution towards a resolved turbulent flow field, at the inflow of the LES coherent structures are generated by means of the reformulated synthetic turbulence generation (RSTG) method. For the poro-serrated TE, turbulence statistics vary in the spanwise direction between the two extremes of a pure solid and a rectangular porous TE, where porosity locally increases the level of turbulence intensity and alters the near wall turbulence anisotropy.

An alternative permeable topology design space for trailing-edge noise attenuation

This study focuses upon a new permeable topology design concept as an alternative to porous metal foams, for turbulent boundary layer trailing-edge (TBL-TE) noise attenuation. The present permeable topology has unconventional characteristics with respect to the metal foams: a combination of low flow resistivity r and high form drag coefficient C. The unconventional characteristics are realized by a Kevlar-covered 3D-printed perforated structure. An experimental study featuring a NACA 0018 airfoil model with a Kevlar-covered 3D-printed TE insert at chord-based Reynolds numbers up to [Formula: see text] is carried out. The airfoil with this TE insert gives a broadband TBL-TE noise reduction up to approximately 5 dB, compared to a solid TE. This reduction varies only slightly with airfoil loading (lower than 1 dB variation), in contrast to the porous metal foams (up to 3 dB variation). When comparing the variation of noise attenuation given by all the permeable materials considered, the variation is found to decrease with the increasing C. This is because C specifies the permeable material's ability to withstand the increasing pressure difference, which causes cross flow that might interfere with the noise attenuation mechanism. Additionally, the drag coefficients as well as the roughness noise of the airfoil equipped with the present TE insert are also significantly lower than those of the metal-foam TE, and are mostly negligible compared to the fully solid airfoil. Based on the findings, design guidelines for permeable TE are proposed: the permeable material shall have a combination of a low flow resistivity and a high form drag coefficient as well as a negligible surface roughness.

Beamforming based extension of semi-empirical noise modelling for low-speed axial flow fans

The application of the turbulent boundary layer trailing edge (TBL-TE) noise component of the semi-empirical Brooks-Pope-Marcolini (BPM) model in an axial flow fan case study is presented herein. The spanwise distribution of the strength of the emitted TBL-TE noise was estimated using the model for various rotational speeds, taking inlet axial velocity profile measurements and two-dimensional (2D) empirical aerodynamic cascade correlations providing input data to the model. The calculated source strength distributions were compared to corrected beamforming results from phased array microphone measurements. In the frequency ranges dominated by the TBL-TE noise, the applicability of the BPM model has been confirmed to circular-arc cambered plate blades, over extensive ranges of geometrical and aerodynamic parameters.

Surface roughness effect on rotor broadband noise

The change of helicopter rotor broadband noise due to different surface roughness during ice accretion is investigated. Comprehensive rotor broadband noise measurements are carried out on rotor blades with different roughness sizes and rotation speeds in two facilities: the Adverse Environment Rotor Test Stand facility at The Pennsylvania State University, and the University of Maryland Acoustic Chamber. In both facilities, the measured high-frequency broadband noise increases significantly with increasing surface roughness height. Rotor broadband noise source identification is conducted and the broadband noise related to ice accretion is thought to be turbulent boundary layer-trailing edge noise. Theory suggests turbulent boundary layer-trailing edge noise scales with Mach number to the fifth power, which is also observed in the experimental data confirming that the dominant broadband noise mechanism during ice accretion is trailing edge noise. A correlation between the ice-induced surface roughness and the broadband noise level is developed. The correlation is strong, which can be used as an ice accretion early detection tool for helicopters, as well as to quantify the ice-induced roughness at the early stage of rotor ice accretion. The trailing edge noise theories developed by Ffowcs Williams and Hall, and Howe both identify two important parameters: boundary layer thickness and turbulence intensity. Numerical studies of two-dimensional airfoils with different ice-induced surface roughness heights are conducted to investigate the extent that surface roughness impacts the boundary layer thickness and turbulence intensity (and ultimately the turbulent boundary layer-trailing edge noise). The results show that boundary layer thickness and turbulence intensity at the trailing edge increase with the increased roughness height. Using Howe’s trailing edge noise model, the increased sound pressure level of the trailing edge noise due to the increased displacement thickness and normalized integrated turbulence intensity are 6.2 and 1.6 dB for large and small accreted ice roughness heights, respectively. The estimated increased sound pressure level values agree reasonably well with the experimental results, which are 5.8 and 2.6 dB for large and small roughness height, respectively.

Noise Emission of a 200 kW Vertical Axis Wind Turbine

The noise emission from a vertical axis wind turbine (VAWT) has been investigated. A noise measurement campaign on a 200 kW straight-bladed VAWT has been conducted, and the result has been compared to a semi-empirical model for turbulent-boundary-layer trailing edge (TBL-TE) noise. The noise emission from the wind turbine was measured, at wind speed 8 m/s, 10 m above ground, to 96.2 dBA. At this wind speed, the turbine was stalling as it was run at a tip speed lower than optimal due to constructional constraints. The noise emission at a wind speed of 6 m/s, 10 m above ground was measured while operating at optimum tip speed and was found to be 94.1 dBA. A comparison with similar size horizontal axis wind turbines (HAWTs) indicates a noise emission at the absolute bottom of the range. Furthermore, it is clear from the analysis that the turbulent-boundary-layer trailing-edge noise, as modeled here, is much lower than the measured levels, which suggests that other mechanisms are likely to be important, such as inflow turbulence.

Trailing edge noise reduction of wind turbine blades by active flow control

AbstractIn the current study, we investigate a route to reduction of the turbulent boundary layer–trailing edge interaction noise. The trailing edge noise is generated by surface pressure fluctuations beneath a turbulent boundary and scattered at the trailing edge of wind turbine blades. Trailing edge noise is considered to be the dominant noise source of modern wind turbines. Therefore, efforts are constantly made to attenuate the noise. Today, noise emission can be reduced by proper airfoil design or passive devices, such as trailing edge serrations. A further improved candidate technology for trailing edge noise attenuation is active flow control in the form of wall‐normal suction. With active flow control, the boundary layer features responsible for trailing edge noise generation can be manipulated, and correspondingly the trailing edge noise can be reduced. Detailed experimental investigations were performed at the Universities of Tel‐Aviv and Stuttgart. The tests showed that steady wall‐normal suction has a positive effect on the trailing edge noise by reducing the boundary layer thickness, and with it the integral length scales of the eddies within the boundary layer. Copyright © 2014 John Wiley & Sons, Ltd.

Broadband Airfoil Trailing-Edge Noise Prediction from Measured Surface Pressures and Spanwise Length Scales

In this paper an effective approach to estimate airfoil Turbulent Boundary-Layer Trailing-Edge (TBL-TE) far-field noise from measured surface pressure fluctuations (SPF) is evaluated. Measurements of both SPF and TE noise were performed on a NACA 0012 airfoil of 0.4 m chord at Reynolds numbers of 1.0–1.9 millions for various angles of attack. A non-homogeneously spaced array of five Kulite-sensors near the TE at x/ c = 0.989 is employed to measure point spectra and spanwise two-point correlations of surface pressure fluctuations. Finally spanwise SPF length-scales are derived as function of frequency. Comparisons to measured TE noise and semi-empirical predictions of surface pressures and far-field noise show very good agreement. It is found, that the proposed method can cover a larger frequency range than standard acoustic measurement techniques. Therefore it can provide valuable assistance in extending spectra obtained conventionally, mainly to low frequencies. Furthermore, pressure and suction side contributions to far-field noise can be obtained separately.