J. Electromagnetic Analysis & Applications, 2009, 1: 102-107
doi:10.4236/jemaa.2009.12016 Published Online June 2009 (www.SciRP.org/journal/jemaa)
1
Dust Effect on the Performance of Wind Turbine
Airfoils
Nianxin Ren1,*, Jinping Ou1,2
1School of Civil Engineering, Harbin Institute of Technology, Harbin, 150090, China; 2School of Civil and Hydraulic Engineering,
Dalian University of Technology, Dalian, 116024, China.
Received January 9th, 2009; revised February 23rd, 2009; accepted March 3rd, 2009.
ABSTRACT
The full two-dimensional Navier-Stokes algorithm and the SST k-  turbulence model were used to investigate incom-
pressible viscous flow past the wind turbine two-dimensional airfoil under clean and roughness surface conditions. The
NACA 63-430 airfoil is chosen to be the subject, which is widely used in wind turbine airfoil and generally located at
mid-span of the blade with thickness to chord length ratio of about 0.3. The numerical simulation of the airfoil under
clean surface condition has been done. As a result, the numerical results had a good consistency with the experimental
data. The wind turbine blade surface dust accumulation according to the operational periods in natural environment
has been taken into consideration. Then, the lift coefficients and the drag coefficients of NACA 63-430 airfoil have been
computed under different roughness heights, different roughness areas and different roughness locations. The role that
roughness plays in promoting premature transition to turbulence and flow separation has been verified by the numeri-
cal results. The trends of the lift coefficients and the drag coefficients with the roughness height and roughness area
increasing have been obtained. What’s more, the critical values of roughness height, roughness area, and roughness
location have been proposed. Furthermore, the performance of the airfoil under different operational periods has been
simulated, and an advice for the period of cleaning wind turbine blades is proposed. As a result, the numerical simula-
tion method has been verified to be economically available for investigation of the dust effect on wind turbine airfoils.
Keywords: NACA 63-430 Airfois, Lift Coefficient, Drag Coefficient, Roughness Height, Roughness Area, Roughness
Location
1. Introduction
As is known to all, the world energy crisis is more and
more serious in our modern society. Wind energy, which
is the most mature technology among so many kinds of
clean and renewable energy, is developing with an
amazing speed now. The crucial to rotor design is the
subject of airfoils. One of the most critical problem for
wind turbine rotors is degradation of the performance,
and the unpredictability of stall due to dust accumulation
on blade surface area. The objective of this work is to
provide a better understanding for the effect of blade
surface roughness on the performance of the wind turbine
thick airfoil. It is very useful to enable wind turbine
designers to predict loads and energy losses during wind
turbines operating under dust conditions, it is necessary
to qualitatively and quantitatively know the change in the
aerodynamic properties due to the dust accumulation on the
surface of the blade. So, the analysis of airfoil surface
roughness has practical application interest in addition to
academic interest. Now, the importance of the dust effect on
the performance of the wind turbine airfoil is well realized.
Generally, roughness has a large effect on the flow
dynamic processes. Therefore, the stall-regulation phe-
nomena in wind turbines are affected by a high degree
due to the increase of the blade surface roughness. De-
spite some previous experimental and numerical work
where surface roughness is involved, the information that
has been obtained on this subject still remains far from
complete [1-3], and the processes of boundary-layer
separation and stall phenomena, which occur on the wind
turbines blade in the presence of surface roughness, are
not fully understood. To obtain more detailed information
about the effect of the surface roughness on the lift coef-
ficients and the drag coefficients of mid-span thick air-
foils, the full two-dimensional Navier-Stokes algorithm
and the SST k- turbulence model are used to investigate
incompressible viscous flow past the wind turbine two-
dimensional airfoil with surface roughness. The NACA
63-430 airfoil is chosen to be the subject, which is widely
used in wind turbine airfoil and generally located at
mid-span of the blade with thickness to chord length ratio

Dust Effect on the Performance of Wind Turbine Airfoils 103
of about 0.3. The lift coefficients and the drag coeffi-
cients of NACA 63-430 airfoil have been computed un-
der different roughness heights, roughness areas, and
different roughness locations. The role that roughness
plays in promoting premature transition to turbulence and
flow separation has been verified by the numerical results.
Furthermore, the degenerate trend of performance for
NACA 63-430 airfoil under different operation periods
has been simulated.
2. Numerical Modeling
2.1 Governing Equations
The flow past the airfoil was modeled by the full Na-
vier-Stokes equation for two-dimensional, viscous, im-
pressible flow. The continuous equation and Momentum
equation based on Reynolds averaged N-S equations are
as follows:
i
0
x
i
u
 (1)
ij ''
i
ij
jijj
(uu)
(u)u p(u
tx xxx
i
u)



 
 
  (2)
where i, j=1, 2; =1.255kg/m3; =1.789410-5 kg/(ms).
2.2 SST k- Turbulence Model
The shear-stress transport (SST) k- model was devel-
oped by Menter [4] to effectively blend the robust and
accurate formulation of the k-

model in the near-wall
region with the free-stream independence of the k-
model in the far field. The SST k- model is described as
follows:
ijj
() k
() ()
txx x
ikkk
kkuG YS   

 

k

(3)
ijj
() () ()
txx x
i
uGYDS

 
 

 

 


(4)
where k represents the turbulence kinetic energy; 
represents the specific dissipation rate; Gk represents the
generation of turbulence kinetic energy due to mean ve-
locity gradients; G represents the generation of ; k
and  represent the effective diffusivity of k and , re-
spectively; Yk and Y represent the dissipation of k and 
due to turbulence; D represents the cross-diffusion term,
calculated as described below; Sk and S are user-defined
source terms.
The SST k- model is similar to the standard k-
model, but includes the following refinements:
·The standard k- model and the transformed k-
model are both multiplied by a blending function and
both models are added together. The blending func-
tion is designed to be one in the near-wall region,
which activates the standard k- model, and zero
away from the surface, which activates the trans-
formed k- model.
·The SST model incorporates a damped cross-diffusion
derivative term in the  equation.
·The definition of the turbulent viscosity is modified to
account for the transport of the turbulent shear stress.
·The modeling constants are different.
These features make the SST k- model more accurate
and reliable for a wider class of flows (e.g., adverse
pressure gradient flows, airfoils, transonic shock waves)
than the standard k- model. Other modifications include
the addition of a cross-diffusion term in the  equation
and a blending function to ensure that the model equa-
tions behave appropriately in both the near-wall and
far-field zones.
2.3 Modeling
The whole computational zone consists of a semicircle
with the radius of 10m and a rectangle with the length of
25m (Figure 1). The length of numerical airfoil which
locates near the center of the semicircle is 1m. The height
of the grid near the airfoil surface is 210-5m (Figure 2).
Reynolds number is 1.6106 [5].
3. Numerical Results
3.1 Numerical Simulation under Clean Surface
Condition
First of all, to ensure that the numerical model is avail-
able for the free-stream flow past the airfoil, the numeri-
cal simulation under clean airfoil surface condition was
made to compare with the wind tunnel experimental data
[5]. The simulative condition was according to the wind
Figure 1. The whole computational zone

104 Dust Effect on the Performance of Wind Turbine Airfoils
Figure 2. Local amplified grids for the airfoil
tunnel set-ups, for example, Reynolds number 1.6106;
free stream turbulence level of 1%. The lift coefficients
and the drag coefficients of the NACA 63-430 airfoil
were computed under the angle of attack between 0 and
25 degree, based on the full two-dimensional Navier-
Stokes algorithm and the SST k- turbulence model. The
comparison between numerical results and experimental
data shows in Figures 3-4.
In the above two figures, it was obvious that the nu-
merical results had a good consistency with the experi-
mental data, despite small discrepancy in comparison of
drag coefficient curves. Therefore, the numerical model
was confirmed to be available for the free-stream flow
past the NACA 63-430 airfoil. Then, in the following of
the paper, the numerical model would be used to investi-
gate the airfoil surface roughness effect.
3.2 Numerical Simulation under Different Sur-
face Roughness Heights
It is supposed that all the surface of the airfoil is rough-
ness area and the angle of attack is 10.6 degree. That’s
because at this angle of attack the numerical results have
a perfect consistency with the experimental data. Then,
numerical simulations of the NACA 63-430 airfoil under
different surface roughness heights has been done and the
results are shown in Figure 5.
Figure 3. Comparison of lift coefficient curves
NACA 63-430 Airfoil
0.00
0 5
Angl e)
Dra
Figure 4. Comparison of drag coefficient curves
Figure 5. Numerical results of Cl and Cd under different
roughness heights
In Figure 5, it is evident that the lift coefficient curve
decreased very rapidly when the roughness height is less
than 0.3mm. However, the lift coefficient curve decreases
very slowly when the roughness height is more than
0.3mm. The same trend of the change also happened in
the drag coefficient curve, which increases very rapidly
when the roughness height is less than 0.3mm, but in-
creases very slowly when the roughness height is more
than 0.3mm. That’s because the surface roughness plays
a role in promoting premature transition to turbulence
and flow separation. When the roughness height is less
than 0.3mm, the effect of roughness is very obvious. But,
when the roughness height is more than 0.3mm, the
whole airfoil has already fully become turbulent bound-
ary and at the same time the flow separation is very serious,
so the effect of roughness on the performance of the airfoil
seems no longer evident. Therefore, the roughness height of
0.3mm could be viewed as a roughness critical height.
Besides lift coefficients information and drag coeffi-
cients information of the airfoil, the numerical results
contain more information of the flow past the airfoil un-
NACA 63-430 Airfoil
0
0
1
0
Ro
C ue
.0
.2
0
0
0
1
l and Cd val
.4
.6
.8
.0
.2
.00.5 1.0
ughness height(mm)
Lift coefficient
Drag coefficient
NACA 63-430 Airfoil
Lift coefficient
Drag coefficient
Roughness height (mm)
0.0 0.5 1.0
C1 and Cd value
1.2
1.0
0.8
0.6
0.4
0.2
0.0
NACA 63-430 Airfoil
0.0
0.2
0.4
0.6
0.8
1.0
0
Angl )
L t
1.2
1.4
510 1520 25
e of attack(degree
ift coefficien
Numerical results
Experimental data
0 5 10 15 20 25
Angle of attack(degree)
N
umerical results
Experimental data
NACA 63-430 Airfoil
Lift coefficient
1.4
1.2
0.8
0.6
0.4
0.2
0.0
0.05
0.10
0.15
0.20
0.25
51015 202
e of attack(degre
g coefficient
Numerical results
Experimental data
NACA 63-430 Airfoil
N
umerical results
Experimental data
0 5 10 15 20 25
Angle of attack (degree)
Drag coefficient
0.25
0.20
0.15
0.10
0.05
0.00

Dust Effect on the Performance of Wind Turbine Airfoils 105
der different roughness conditions, which are also very
useful to clarify the physical mechanism of the surface
roughness effect. For example, the turbulent intensity
distribution and pressure coefficient distribution of the
airfoil surface are shown in Figure 6 and Figure 7, re-
spectively.
In Figure 6, it is clear that the turbulent intensity of the
airfoil under clean condition is very small, however, with
the roughness height increasing from 0 to 0.3mm, turbu-
lent intensity increases very obviously, especially for the
leading edge of the airfoil. In Figure 7, the area enclosed
by the pressure coefficient curve of the airfoil obviously
decreases with the roughness height increasing from 0 to
0.3mm, especially for the location at the front 50% of the
chord length.
Furthermore, the two pictures could be better to dem-
onstrate and clarify that surface roughness plays a role in
promoting premature transition to turbulence and flow
separation. By the way, it also could be found that the
increase of turbulent intensity and the change of the
pressure coefficient are no longer evident when the
roughness height is more than 0.3mm.
Figure 6. Turbulent intensity curves under different rough-
ness heights
Figure 7. Pressure coefficient curves under different rough-
ness heights
3.3 Numerical Simulation under Different
Roughness Areas
To clarify the effect of different roughness areas on per-
formance of the airfoil, simulations under the angle of
attack 10.6 degree and roughness height 0.3mm were
done. The roughness area is denoted by the ratio of the
chord length covered with roughness, which is calculated
from the leading edge. The simulation results are shown
in Figure 8. It is obvious that the lift coefficient curve
decreases rapidly when the roughness area is less than 0.5.
However, the lift coefficient curve decreases very slowly
when the roughness height is more than 0.5. It can be
concluded that the front 50% of the chord length more
easily promotes premature transition to turbulence and
flow separation. In the flowing section, further study and
explanation will be given.
3.4 Numerical Simulation under Different
Roughness Locations
Furthermore, to see the effect of different roughness lo-
cations on performance of the airfoil more clearly, simu-
lations under the angle of attack 10.6 degree and rough-
ness height 0.3mm have been done. The whole NACA
63-430 airfoil is averagely divided into 10 parts, and each
part is with a length of 0.1m. The simulation results are
shown in Figure 9. The decrease percentage of the lift
coefficient is defined by:
NACA 6
% 100%
clean roughness
decrease
clean
Cl Cl
Cl Cl


(5)
From the Figure 9, it could be seen that the influence
of surface roughness located at the front 50% of the
chord length is more obvious than that located at the back
50% of the chord length. On one hand, it is because the
roughness located at the front 50% of the chord length
more easily promotes premature transition to turbulence
and flow separation. On the other hand, it is also because
the airfoil at font 50% of the chord length is generally
thicker than that at the back 50% of the chord length.
Therefore, the roughness location at 25% of the chord
length had the most obvious effect, where is the location
of the largest thickness.
It is worth to be noticed that, when the roughness loca-
tion is at the trailing edge 10% of the chord length, the
lift coefficient under surface roughness condition is about
3% larger than that under clean surface condition. So, it
could be concluded that properly increasing the surface
roughness of trailing edge could be benefit to promote the
airfoil’s lift coefficient to some degree, which has a good
agreement with experimental data [6]. The conclusion
would be useful for practical projects.
3-430 Airfoilclean
0
0.0
0.1
Turbulent intensity
5
0.1
5
0.2
00.2 0.40.6 0.81
x/c
0.1mm roughness
0.3mm roughness
1mm rou
g
hness
0 0.2 0.4 0.6 0.8 1
x/c
NACA 63-430 Airfoil
Turbulent intensity
0.2
0.15
0.1
0.05
clean
0.1mm roughness
0.3mm roughness
1mm roughness
0
NACA 63-430 Airfoil
-2.5
0 0.20.40.60.8 1
-2
-
-
Pressure coefficient
1.5
-1
0.5
0
0.5
1
1.5
x/c
clean
0.1mm roughness
0.3mm roughness
1mm rou
g
hness
NACA 63-430 Airfoil
1.5
1
Pressure coefficient
0.5
0
-0.5
-1
-1.5 clean
0.1mm roughness
-2 0.3mm roughness
1mm roughness
-2.5
x/c

106 Dust Effect on the Performance of Wind Turbine Airfoils
Figure 8. Lift coefficient under different roughness areas
Figure 9. Lift coefficient under different roughness locations
3.5 Numerical Simulation Under Different
Operational Periods
In this section, considering the effect of the blade surface
dust accumulation, the performance of the wind turbine
NACA 63-430 airfoil under different operational periods
has been studied. The relationship between surface
roughness and operational period is determined by field
investigation, which was done by Khalfallah [2]. Then,
the roughness heights and the roughness areas under
different operational periods can be calculated by the
following linearization function proposed by Khalfallah,
which is not taken the rain washing effect into consid-
eration. As a result, the specific four operation periods
are list in Table 1.
0.08 0.02
d
DT (6)
/25
a
DT (7)
where, Dd is the dust size (diameter in mm); T is length of
operational period in months; Da is the dust area in per-
centage of the chord length.
Subsequently, the former available numerical model
has been used again to investigate the performance of the
NACA 63-430 airfoil under the four operation periods
and the numerical results are shown in Figure 10 and
Figure 11.
It can be seen that, the dust effect on the performance
of wind turbine airfoil is obvious when the operation pe-
riod is 5months. The decrease of the lift coefficient and
the increase of the drag coefficient are remarkable to a
large degree, especially for the angle of attack around 13
degrees. That’s because the roughness height of the
5months operational period is 042mm, which is larger
than the critical value 0.3mm. As the operation period
increasing from 5months to 12.5months, the roughness
area is increasing from 0.2 to 0.5, which just reaches the
critical roughness area value (0.5). Therefore, the lift co-
efficient further decreases to a large degree at the angle
of attack less than 13 degrees. But, when the operational
period is longer than 12.5 months, the change of the lift
coefficient is rather small. That’s because that, when the
operational period is longer than 12.5 months, the rough-
ness height and roughness area both larger than the criti-
cal values proposed in the previous section. As a result,
the effect of the surface roughness on promoting prema-
ture transition to turbulence and flow separation tends to
be neglectable.
NACA 63-430
Table 1. Roughness heights and roughness areas according
to different wind turbine operational periods
T(months) Dd (mm) Da
2.5 0.22 0.1
5 0.42 0.2
12.5 1.02 0.5
20 1.62 0.8
Figure 10. The comparison of lift coefficient curves during
different operation periods
-1
x/c
0%
0%
10%
20%
30%
5%15%25% 35% 45%55% 65% 75%85% 95%
Cl decrease
percentage
NACA 3-430 6
5% 15% 25% 35% 45% 55% 65% 75% 85% 95%
x/c
30%
20%
10%
0%
-10%
C1 decrease
percentage

Dust Effect on the Performance of Wind Turbine Airfoils 107
·The performance of NACA 63-430 airfoil is more sen-
sitive to roughness location at the front 50% of the
chord length than roughness location at the back 50%
of the chord length. In particular, proper roughness
height at the trailing edge can be benefit to promote the
lift coefficient to some degree. This conclusion is very
useful for the wind turbine blade designer to further
improve the performance of the blade.
·Considering the dust accumulation effect, the per-
formance degenerate trend of NACA 63-430 airfoil
under different operation periods has been studied. As
a result, the period of 3 months without any rain is
proposed as the proper period of cleaning the blade
surface.
As a result, the numerical simulation method has been
verified to be economically available for the investigation
of the dust effect on the performance of the wind turbine
airfoil.
Figure 11. The comparison of drag coefficient curves during
different operation periods
In practical project, it is of great economic interest to
keep the good performance of the wind turbine blade, so
it is very meaningful to periodically clean the dust of the
blade surface when there is no rain washing for a long
time. Considering the performance degenerate trend of
the wind turbine airfoil according to the operational pe-
riod, the period of 3 months is proposed for the proper
period of cleaning the blade surface.
5. Acknowledgments
The support of the National Science Foundation of China
under project No. 50538020 and the National Science and
Technology Planning under project No. 2006BAJ03B00
is gratefully acknowledged.
4. Conclusions REFERENCES
In this paper, the full two-dimensional Navier–Stokes
algorithm and the SST k- turbulence model were used
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