PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Aerofoil trailing edge self-noise reduction by Surface Mounted
Attenuation Devices
Edvard SCHROEDER1; Tze Pei CHONG1; M. KAMRUZZAMAN2; Jeremy HURAULT2; Phillip
JOSEPH3
1

Department of Mechanical and Aerospace Engineering, Brunel University London Uxbridge, United Kingdom,
UB8 3PH2

Vestas Technology UK Ltd, Newport, Isle of Wight, United Kingdom, PO30 5TR
3

ISVR, University of Southampton, Southampton, United Kingdom, SO17 1BJ

ABSTRACTThis paper presents the results of a preliminary experimental study into the effect of add-on type finlets on the
aeroacoustic performance of a wind turbine aerofoil. The content mainly deals with the turbulent boundary
layer - trailing edge broadband noise characteristics subjected to the add-on finlets. The test program seeks totest various combinations of finlet height and spacing present on the (1) suction side only, (2) pressure side
only, and (3) both suction and pressure sides. Each finlet parameter configuration is tested at jet velocity
U=30m/s and 45m/s, at geometric angles of attack AOA (Angle of Attack) (geometric) = 10°, 0°, -10°. Basedon the data acquired thus far it is observed that a finlet usually performs best with increasing height anddecreasing spacing. Under configurations (1) and (2), finlets are able to produce up to 2dB Sound PowerLevel broadband noise reductions, where configuration (3) offers broadband reductions of up to 7dB Sound
Power Level, with potential to observe more reductions once optimised. The main parameter for improved
performance of finlets is the spacing rather than the height. Finlet height does not offer significant impact on
the performance if the spacing is not optimal. The established trend for optimal finlet parameters remains
consistent for all AOA, offering improved performance at high positive angles, which has a practicalapplication to wind turbine blades.
Keywords: finlets, trailing edge, aerofoil, noise, reduction

1. INTRODUCTION
The current GEN1 STE (Serrated Trailing Edge) technology enabled wind turbine manufacturers to
reduce the turbine self-noise predominantly in the range of 5-7dB in lab conditions (Gruber, Joseph, &Chong, 2010) (Moreau, Brooks, & Doolan, 2011) and validated to reduce in the range of 1.5-3dB invarious field tests (Mathew, Singh, Madsen, & Leon, 2016). Now, in a wider scope, noise regulations
on peri-urban areas place a strict clamp on noise emissions emitted from var ious aspects of thespecified environment, be it residential, transport, infrastructural, or industrial. The wind industry is
faced with a decision to meet these strict environmental regulations, either make the turbines quieter,or run them slower. It is evident that de-rating a wind turbine for several hours a day, over the span ofa year add up to an immense quantity of lost kilowatt-hours in AEP (Annual Energy Production), andtherefore a loss in profit. STEs have enabled turbines to run faster, and for longer under conditions
where they would normally have to be de-rated. This results in a 6% AEP increase per turbine (Van Der
Velden, Romani, & D.Casalino, 2018).
In a mission to further reduce noise emissions from wind turbines, enabling them to be placed either
closer to populated areas, or operate at higher RPMs (Revolutions Per Minute) under noise emission
restrictions, new types of passive devices must be considered beyond current STE technology. The
nominal target is to achieve a further 3dBA noise reduction across a grouping of turbines.
TBL - TE (Turbulent Boundary Layer – Trailing Edge) noise accounts for most of the noise
emission in wind turbine blades operating within their design regimes. As described in the previou ssection, the components of this mechanism include a turbulent boundary layer, resultant fluctuations inflow pressure, and a surface to scatter from, namely the trailing edge. To introduce changes into thismechanism, altering any one of these components will result in the spectral noise characteristics of thesubject aerofoil.
A device/technique of particular interest comes from research done by (Millican, 2017) and (Clark,
et al., 2015) from Virginia Polytechnic Institute which describes how the thick follicles on the trailing5327

edge of an owl’s wing create a sort of canopy, and thus suppress any pressure fluctuations. The
parameters at play are the finlet spacing, height, and extension beyond the trailing edge. Firstly, thetrailing edge extensions are detrimental to noise reduction performance, so will not be included as aparameter in the testing. The height parameter increases the performance of the finlet, especially athigh AOAs (Clark, et al., 2015). The final parameter is the finlet spacing, where a smaller gap willcontinue to improve the noise reduction performance to the point where they are small enough to cause
vortex shedding. Noise reductions attained to date are in the region of 2-7dB SPL (Sound Pressure
Level) from 1.5 to 10kHz (Millican, 2017). An emerging hypothesis suggests that the finlet
performance is mainly accredited to the sheltering of the trailing edge from large turbulence structures,and the reduction of spanwise coherence of these structures.
A detailed study done by (Afshari, Szoke, Denghan, & Azarpeyvand, 2016) analysed through atemporal cross correlation method, has found that surface pressure fluctuations have the highest
correlation with upstream eddies. When implementing the finlets, results indicated a reduction incorrelation at regions far away from the surface of the aerofoil, leaving behind an increase in the nearwall correlation. This phenomenon is likely due to the breaking up of the large scale eddies down tosmaller ones when passing between the finlets.
Based on what is known, prospective methods lie ahead in studying the near wall TBL structures,with strict correlation studies with the outer boundary layer dynamics. In the long term, this should lay
the groundwork for exploring means to control the TBL through the breaking down o f turbulent eddies
from the upstream regions through to the trailing edge, in a goal to fine tune a passive device to reducenoise within a particular band. In addition, knowledge of the exact TBL structures, in near and outerwall regions, pre- and post-surface treatment, will shed light on numerical methods which can be
implemented in a specific finlet design task.

2. WIND TUNNEL FACILITY, DATA ACQUISITION, TEST PARAMETERS,BASELINE DEFINITION
Far field noise measurements were conducted in the anechoic chamber at Brunel University. The
anechoic chamber is fitted with an open loop open jet nozzle measuring 100mm in height, and 300mm
in width. This wind tunnel is characterised by a freestream turbulence intensity of 0.1-0.2%, and amaximum jet velocity of 80m/s. The open jet noise characteristics of this wind tunnel have beenvalidated by three case studies, all of which demonstrate a very low background noi se relative to noiseradiated from the test aerofoil (Vathylakis, Chong, & Kim, 2014). Far field noise measurements weretaken using a polar array of eight microphones at a 1.0m radius each, situated at θ = 50°, 60°, 70°, 80°,90°, 100°, 110°, 120° from the trailing edge respectively, with the aerofoil itself clamped between two
vertical sideplates extending from the nozzle. The noise data was acquired at a sampling frequency of
40kHz for 10s by a 16-bit DAC from National Instruments. The Power Spectral Density of 1Hz
Bandwidth and frequency resolution of 40kHz was generated using a 1024 po int Fast Fourier
Transform within MATLAB. The data is processed as
where
is the sound power
level, is the medium density, is the speed of sound in the given density, is the observer distance,is the acoustic pressure level at a given frequency interval, integrated across all microphone angles
where. The data is converted back to decibels by
where
Equation 1 PWL (Sound Power Level) definition
OAPWL (Overall sound power level) is derived by taking the integral of the power level spectrum.
To obtain a greater sensitivity to changes in noise emission/reduction, the spectra ar e integrated
between 1000-16000Hz. The OAPWL values were determined using the following method;

Equation 2 OAPWL (Overall Sound Power Level) definitionand ∆OAPWL is computed by taking the OAPWL of a given case and subtracting the dB values of
the respective baseline case from it. Therefore a negative value of ∆OAPWL denotes noise reduction,
while a positive one denotes noise increase.
In setting up the test aerofoil, a forced boundary layer transition was promoted using pieces ofturbulator tape placed on the suction and pressure side of the aerofoil. This removes the laminar
instability tonal noise as seen in Figure 1 at ~2kHz and ~3.5kHz for 30 and 45m/s respectively. The

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laminar instability noise is quite dominant in this aerofoil, therefore implementing a forced transition
method ensures that the results obtained are using a consistent turbulent boundary layer undercontrolled conditions. The setup comes with a trade-off as zig-zag tips of the trip tape generating avisible peak at 8kHz and 15kHz for U=30 and 45m/s respectively at AOA=-10°, seen in Figure 1 on theblack line spectra.

Figure 1 PWL, forced transition dependency,

Figure 2 PWL, baseline AOA dependency

AOA=0° at U=30, 45m/s.
To further characterise the aerofoil, it is important to understand how the spectrum is expected tochange with varying AOA, as shown in Figure 2. Under tripped conditions the spectra between AOA(geometric) = 10°, 0°, -10° shows a crossover between 2kHz and 4kHz, but this crossover is minimal.
This may suggest that the range of effective AOA is small across the range of geometrical AOA tested
in the current study.
By acquiring PWL data from a range of velocities U = 20, 30, 40, 50, 60m/s, any anomalies or
unaccounted for phenomena can be observed. Apart from the aforementioned trip tape tonal peakvisible at 30 and 40m/s for AOA=-10° at 8kHz and 16kHz respectively, the progression between
velocities appears to be predictable. Taking the OAPWL values of each velocity spectrum from Figure
3, the obtained OAPWL values can be scaled against the U power law in Figure 4. Seeing as bothcurves are near parallel, one could confirm that the trailing edge noise is being r adiated out in a dipole
source manner. In one observation, it is worth noting that despite a large change in AOA up to ±10°, thespectrum does not change significantly, even though the boundary layer is expected to varysignificantly at such angle deviations. Further boundary layer measurements will be required to
explore the matter.

Figure 3 PWL, U dependency, AOA=0° at U=20,

Figure 4 U power scaling, showing TE noise as30, 40, 50, 60m/s.
dipole noise source
In order to confirm the noise reduction characteristics of finlets, a set of parameters described in
Figure 5 were outlined in Table 1 with the following ratios of finlet height, and spacing, relative to aunit finlet thickness. The test program seeks to test all the various combinations of fi nlet height andspacing for the suction side only, and pressure side only as stated in Table 1, to observe the individual
perceived reductions in OAPWL, and ∆OAPWL in relation to the baseline tripped aerofoil. Each f inlet
parameter configuration is tested at U=30m/s, and 45m/s, at AOA (geometric) = 10°, 0°, -10°.

SS Finlet height (hX)PS Finlet height (hX)

Finlet spacing (s)Figure 5 Finlet parameters described5329

Finlet height (hX)hA < hB < hC < hD < hE

Finlet spacing (sX)sA < sB < sC <sD

Table 1 Finlet parameters as ratios of unit thickness

3. SPACING-HEIGHT MATRICES, RESULTS AND OBSERVATIONS
To fulfil the aim of the current study into finlets, a series of test were conducted in combining theparameters outlined in Table 1. There is a separate case-set for AOA (geometric) = 10°, 0°, -10° at
U=30m/s and AOA (geometric) = 10°, 0°, -10° at U=45m/s for pressure side of the aerofoil. The tested
configurations are visible along the x-axis on the left-side absolute OAPWL plot, using spacing as anintermittent independent variable, and finlet height as the dependent. This way, the overall noise
reduction trends can be visualised as a function of finlet height and spacing.
By observing the data ∆OAPWL surface plots, we can see an increase in performance withincreasing finlet height, and reduction in finlet spacing. It is evident th at the finlet performancedecreases with high spacing and low height, as it would be exposing more of the trailing edge, now
with additional bluntness. Where the finlets really do perform exceptionally is at high angles of attack.
Based on the data, the additional height of the finlet does not add any detriment to the acoustic
performance at near-zero AOA, but does add a considerable advantage at AOA=±10°.
With regards to the finlet parameters, spacing becomes the dominant factor, a trend which is
confirmed by the works of (Clark, et al., 2015) and (Millican, 2017). By analysing the trend in absolute
OAPWL, more closely packed finlets show greater increased in performance for every additional
percent in added height. This however does not hold for more widely spaced finle ts. What becomescurious with the suction side finlet performance in Figure 6 and Figure 7, is the relationship betweensA and sB finlets. In both 30 and 45m/s cases, we see that the sB finlet shows a gradual performanceincrease with finlet height, where with sA the performance remains relatively unchanged up to andincluding sC. at hD, the sA finlets show an abrupt increase in performance. When observing data fromthe pressure side finlets, performance changes are more gradual across all spacings with the sA finlet
performance scaling well with increasing height.
3.1 Finlet suction/pressure side only, U=30m/s, U=45m/s

Figure 6 Finlet SS, OAPWL plot, ∆OAPWL surfplot, U=30m/s, AOA=0°

Figure 7 Finlet SS, OAPWL plot, ∆OAPWL surfplot, U=45m/s, AOA=0°5330

Figure 8 Finlet PS, OAPWL plot, ∆OAPWL surfplot, U=30m/s, AOA=0°

Figure 9 Finlet PS, OAPWL plot, ∆OAPWL surfplot, U=45m/s, AOA=0°
3.2 Finlet suction and pressure side combination
Figure 10 show the PWL spectra for finlets at suction and pressure sides when the same finlet
configurations sA and hE are installed respectively. PWL produced by the untreated aerofo il is also
included for comparison. Both cases exhibit good level of broadband noise reduction, but the surface
add-on treatment on the pressure side seems to generate larger level of noise reduction than the suction
side. This could be due to the finlet being more optimised to the TBL at the pressure side than thesuction side. To understand more about the relationship between finlet configuration effects on the
TBL, further testing and examination will be required. Secondly, is that in combination, the re duction
performance is significantly augmented in the broadband spectrum, being able to offer reductions from
2kHz and upwards, while tracking the jet noise very closely offering reductions up to 7dB PWL.

Figure 10 PWL comparison, baseline, finlet SS and PS, jet noise, AOA=0°, U=30m/s, 45m/s
To supplement the conclusion of improved finlet performance in relation to a baseline at high AOA,
Figure 11 shows that between finlet-only configurations, performance is improves with increasing
AOA. This is demonstrated by the red curves for AOA=10°, with noise emissions rising for AOA=0°
and AOA=-10° respectively. Interestingly, the greater sensitivity of TE noise radiation with respect to
the AOA, as exhibited by aerofoil with finlet treatment in Figure 11, is markedly different with theuntreated, baseline aerofoil shown in Figure 2. This demonstrates that the finlet has disrupted thedevelopment of turbulent boundary layer far greater than the variation in pressure gradient. In aprevious observation, it was stated that the main performance altering factor in finlets is the spacing
parameter, and not so much the height. This would point into the direction that finlets exploit aboundary layer structure, whose prominence is characterised by a spanwise corr elation length scale.

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Figure 11 PWL, finlet SS+PS combi. AOA dependency
To model noise emissions of aerofoils under various configurations, a number of numerical models
were devised over the years in the field of aeroacoustics. One of the better known methods was done by
Amiet, which requires knowledge of the wall pressure spectrum near the trailing edge. The model
itself does contain some inherent limitations, the first being the aerofoil is assumed to be a straightinfinite flat plate extended into the upstream or downstream direction for leading and trailing edge
noise respectively. The geometric effects of an aerofoil such as its shape, camber, thickness, trailingedge thickness is not considered, but rather the local wall pressure data used in the model. The far field
acoustic spectrum
can be predicted by Amiet’s model from:

Equation 3 Amiet TE noise modelis the observer position with the origin located at centre-span on the trailing edge,
is the observer location relative to the origin,

where

is the acoustic wave number andis the chord length, is the foil semi span, is the acoustic transfer function
wherebeing the transfer function of the trailing edge, andthe back-scattering leading edge correction
done by (Roger & Moreau, 2005),
is the wall pressure power spectral density,s thespanwise correlation length, The spanwise length correlationis brought by the Corcos model(Corcos, 1967), same as in the Modified Howe model asis the convective
velocity, is a variable constant, and is a specified angular frequency.
In the works of (Clark, et al., 2015), (Millican, 2017), and (Afshari, Szoke, Denghan, &Azarpeyvand, 2016), a common hypothesis is upheld, where the performance of the finlet is mainly
characterised by a combination of shifting the large turbulent structures away from the trailing edge,
and the reduction of the spanwise coherence. In relation to the Amiet mode l presented in Equation 3,
this would be seen in the reduction of the spanwise correlation, brought by the Corcos model(Corcos, 1967). The second parameter is the reduction of surface pressure fluctuations near the trailingedge as described by (Afshari, Szoke, Denghan, & Azarpeyvand, 2016) and (Bodling & Sharma, 2018)
which would be impacting on theparameter of the model.

Figure 12 Comparison between spectra from current study (left) and study conducted by (Clark, et al., 2015)(right).
In the absence of detailed flow measurement in the current study, the results obtained in this study
are found to be in line to that of (Clark, et al., 2015), as shown in Figure 12. The results obtained here
confirm some of the basic trends observable in finlet configuration ge ometry with regards to theiraeroacoustics performance at varying speeds and AOA.

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4. CONCLUSIONS AND FURTHER WORK
To conclude this short study into the aeroacoustic performance trends of finlets, several outcomes
become clear; Finlet performance improves with increasing finlet height, and decreasing spacing.
Individually, finlets are able to produce up to 2dB broadband noise reduction with no trade-off. A
combination of suction side and pressure side finlets offers excellent reductions up to 7dB, and canoffer more once optimised. The main parameter for improved performance of finlets is the spacing
rather than the height. Finlet height does not offer any significant impact on the performance if thespacing is not optimal. With regards to AOA performance, the established trend for optimal finlet
parameters remained consistent for all AOA, offering greater reduction s at high angles, which is agood sign for practical applications in wind turbine blades.
Further work based on this study would include the boundary layer measurements through the useof multi-hotwire and wall pressure transducers. This is required to understand how finlets affect the
aforementioned spanwise correlation, and surface pressure fluctuation variables. The
main focus would be to correlate the near wall changes in the boundary layer to the simultaneouschanges in the far-field measurements. This would serve well in developing a numericalsolution/extension to an existing semi-empirical aerofoil noise model to get a closer look into the fullpotential of optimised finlet reduction performance.
Exploring the TBL eddy structure in the near wall and outer wall region in details is imperative,
especially that a non-linear effect for the boundary layer contribution to the noise radiation subjected
to finlet treatment has been observed. Having the ability to use correlation studies to char acterise theuse of finlets in breaking down large TBL structures into smaller ones could shed light on the future
development of multi-stage noise reduction devices. These devices would focus on the upstream flow
to disrupt turbulence inducing phenomena, paired with methods of sheltering the trailing edge fromhigh energy turbulent structures.

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