AERODYNAMIC ANALYSIS OF A SMALL HORIZONTAL AXIS WIND TURBINE USING CFD

AERODYNAMIC ANALYSIS OF A SMALL HORIZONTAL AXIS
WIND TURBINE USING CFD
Journal of Wind and Engineering, Vol. 9, No. 2, July 2012, pp. 14-28
$ $
*M. Keerthana, M. Sriramkrishnan, T. Velayutham, *A. Abraham, *S. Selvi Rajan
$
and K. M. Parammasivam
*Wind Engineering Laboratory, CSIR-Structural Engineering Research Centre, Chennai
$
Madras Institute of Technology, Anna University, Chennai
Wind is a clean source of energy that is renewable and harnessing the green wind energy is one of
the key factors for sustainable growth and development. Such energy can be harnessed through
wind turbines. The present study deals with the computational analysis of a scaled model of 3 kW
small horizontal axis wind turbine (HAWT) using CFD (Computational Fluid Dynamics). The wind
turbine rotor configuration has been obtained using BEM (Blade Element Momentum) theory.A3-D
computational model of the rotor system has been created and CFD simulations have been carried
out using commercial CFD code FLUENT. The analysis has been carried out at various wind
speeds in the range of 4 m/s to 12 m/s using Shear Stress Transport k-ω (SST) model to study the
variation of torque, normal force and power with wind speed. The analysis for a range of tip speed
ratios (at constant flow velocity) also has been carried out. The flow field characteristics around
different sections of the blade were studied.
Keywords: HorizontalAxis WindTurbine, Computational Fluid Dynamics, Simulations
INTRODUCTION
One of the major challenges in this new century is the production of energy as well as its efficient
use from renewable sources. Researchers around the world have shown that global warming has
been caused in part by the greenhouse effect which is largely due to the use of fossil fuels for
transportation and electricity. So, the use of renewable energy sources such as geothermal, solar,
wind and hydroelectric power needs to be increased to protect the environment. As a renewable
energy, wind energy has taken an increasingly important place in energy policies at national and
international level as a response to climate change. Wind power usage in India is growing and
research in the field of wind energy will further improve the current situation. The estimate of wind
energy potential in India by the Centre for Wind Energy Technology (C-WET, an autonomous
research and development institution under the Ministry of New and Renewable Energy of India,
located in Chennai) is 103 GW at a hub height of 80m which is equivalent to only 8% of electricity
needs (in energy terms) in 2022 (Phadke et al., 2012). C-WET has published the Indian Wind Atlas
in 2010 (Figure 1), showing large areas with annual average wind power densities more than 200
2
Watts/m at 50 meter above ground level. The sites have been classified based on annual average
wind power density.
Wind turbines convert wind energy to electricity via mechanical energy. There are two primary
types of wind turbines, namely horizontal axis (HAWT) and vertical axis (VAWT) wind turbines, and
ABSTRACT

the efficiency of each wind turbine type varies by its design and fabrication. HAWTs are most
commonly used in wind farms (Howell et al, 2010).Atypical wind farm needs about 0.25 acres for a
1MW turbine. In cities, where there is a crowded population and the land being used to a maximum
extent, the availability of such huge area for setting up a wind farm is difficult. Also in the urban
environment, the wind speed required for harnessing higher power is less. For these reasons, small
wind turbines which can be installed on roof tops are suitable for use in urban areas, as well as rural
areas that are not connected to any electricity network. They are capable of producing power in a
range of 3 to 5 kW, which is sufficient to meet the needs of a household. Of all the factors
responsible for efficient energy production, the aerodynamics of flow around the wind turbine
blades plays an important role. In order to better treat the wind turbine aerodynamics, one of the
approaches is by application of computational fluid dynamics (CFD)
Numerical studies on aerodynamics of wind turbines have become an area of deep interest to
researchers all over the world. Digraskar (2010) carried out CFD simulations on the flow over
National Renewable Energy Laboratory (NREL, USA) Phase VI wind turbine rotor, with the
objective of performing the aerodynamic analysis of a horizontal axis wind turbine. The NREL
Phase VI test refers to a full scale unsteady aerodynamic experiment on a two bladed wind turbine
in the NASA Ames 80x120 foot wind tunnel. Results obtained from this experiment were then
considered as a benchmark for performing numerical studies (Fingersh et al., 2001).Asteady state,
incompressible flow solver for Multiple Reference Frames (MRF), Simple Foam was modified and
used for performing the analysis. The flow behavior was studied and the results from the
Figure 1: Wind power density map from the Indian Wind Atlas (2010)
Aerodynamic Analysis of a Small Horizontal Axis Wind Turbine Using CFD 15

simulations and wind tunnel experiments were compared. With the close comparison of numerical
results with that of experimental results, the ability of CFD techniques in simulating wind flow over
entire wind turbine assembly was demonstrated. Rajendran et al., (2011) demonstrated the
potential use of an incompressible Navier-Stokes CFD method for the analysis of horizontal axis
wind turbines. Results from the simulation revealed the flow details near and off the blades and
tower, thereby aiding in analyzing the aerodynamic performance of the system. The CFD results
were also validated against experimental data of the NREL power performance testing activities,
wind turbine verification program of non-yawed isolated rotor of a wind farm.
Carcangiu (2008) used Reynolds Averaged Navier-Stokes (CFD-RANS) approach for numerical
simulation of wind turbine aerodynamics. A full 3-D CFD-RANS approach was used, modeling the
whole rotor of a wind turbine by means of periodicity and in a moving reference system. A study on
the blade root and tip was carried out, to demonstrate the advantages of some recent
improvements in rotor blade design, and showing the capabilities of CFD as an optimization tool.
The rotational effects of rotor on the boundary layer of blades were studied and a complete solution
database was generated. Duque et al., (2003) performed CFD-RANS simulations on the two
bladed NREL Phase VI rotor made up of S809 airfoil with two commercial CFD codes, CAMRAD II
and OVERFLOW-D. Aerodynamic performance characteristics like power generation, force
coefficients, sectional pressure distribution were computed and matched with the benchmark
values. Sezer-Uzol and Long (2006) presented the results of 3D and time-accurate CFD
simulations of the flow field around the NREL Phase VI horizontal axis wind turbine rotor. The 3-D,
unsteady, parallel, finite volume flow solver, PUMA2, was used for the simulations, with a rotating
unstructured mesh. The pressure distribution over the blade agreed well with the experimental
results. Gonzalez and Munduate (2008) performed aerodynamic analysis of parked and rotating
configurations of the NREL Phase VI blade. The properties like attached flow, separated flow, and
stall were studied by performing 2D sectional analysis of the blades. The leading edge and trailing
edge separation were highlighted in their work. Aeroelastic analysis using three-dimensional CFD
have been conducted on wind turbine blades by a number of researchers to study the effect of blade
flexibility on the power of the wind turbine (Sajjan, 2009), enhancement of aeroelastic stability
analysis and prediction of dynamic response (Streiner et al., 2007).
From the literature, it can be observed that CFD can be used as a potential tool to study the detailed
flow field around wind turbine rotor. The other method to better understand the aerodynamics of
wind turbines is the use of dedicated experiments to increase knowledge and physical
understanding of the phenomena and to validate models. Clearly, the results from CFD need
validation, due to which exclusive use of CFD is not always preferred. In consideration of the fact
that research on small wind turbines in India is limited, the present study has been initiated with the
objective of studying the performance of a small HAWT computationally using CFD. The
simulations have been carried out in commercial CFD code FLUENT and GAMBIT has been used
as preprocessor. The results from CFD simulations aids in better understanding of the flow
structure around the turbine. From the literature, Moving Reference Frame (MRF) model (Luo et al.,
1994) has been observed to be widely used for rotational motion, of the rotor. Hence, the same
model has been used in the present study.
Journal of Wind and Engineering, Vol. 9, No. 2, July 2012, pp. 14-28 16

WIND TURBINE ROTOR CONFIGURATION
The process of selection of wind turbine rotor configuration typically includes selection of airfoil
section, design of blade for optimum performance, determination of number and pitch angle of the
blades, design of connecting rods, shaft and hub of the rotor.
The power output of the wind turbine in watts (P) is given by
(1)
Where C is the power coefficient
power
3
ρ is the density of air (1.2 kg/m )
R is the radius of the rotor
V is the free stream velocity
In the present study, the power output has been considered to be 3 kW. Power coefficient is the ratio
of power that could be extracted from the wind turbine to the wind power that is available. Betz
defined the limit of energy extraction as 59.26%, beyond which the flow takes place around the wind
turbine rather than through it (Manwell et al., 2009). Beyond Betz limit, the losses due to friction in
the bearings and electrical losses in generator occur in the system. Hence, power coefficient has
been taken as 35%, after all possible losses. The radius was found to be 2.9 m for a rated wind
speed of 8 m/s and aforementioned parameters. Boundary layer wind tunnel experiments on the
scaled model of the wind turbine at CSIR-SERC wind tunnel have been planned, for the purpose of
validation (the results of which are not included in the present paper). A scaling factor of 1:13 has
been considered, taking into account the blockage effects in the wind tunnel. Hence, scaled radius
of 0.225 m will be considered in further CFD studies.
The three bladed configuration offers the best balance between aerodynamic efficiency, noise
levels and blade stiffness. Hence it is the most common design for HAWT. Two bladed configuration
leads to lower cost, but complex dynamics due to flow around the system. In the present study,
number of blades has been chosen as three. HAWT blades have been conventionally designed
using airfoil sections, with thin airfoil at blade tip (for high lift to drag ratio) and thicker version of the
same airfoil at the root for structural support (Manwell et al., 2009). Airfoils commonly used in wind
turbine blades are NACA 44xx and NACA 230xx series due to maximum lift coefficients, low
pitching moment, and minimum drag. For the present study, NACA 4418 airfoil section has been
used. The aerodynamic characteristic of NACA4418 is given below:
 Maximum lift coefficient C of 1.797 which corresponds to critical angle of attack
Lmax
(stall point) of 15°
 Zero-lift angle of attack of -4°
 Maximum lift to drag ratio or glide ratio (C / C ) of 44.447 which corresponds to angle
L D max
of attack of 6.5° and lift coefficient of 1.209 (where C is the lift coefficient and C is the
L D
drag coefficient)
3 2
1
2
power
P C V R
 


Tip speed ratio (λ) is an important parameter in the design of wind turbines and is the ratio between
tip speed and undisturbed wind speed. It is given by Equation (2).
(2)
where  the angular velocity of the rotor. For a three bladed configuration, λ should be greater than
4 for electrical power generation (Manwell et al., 2009). The most common value of λ of 6 has been
chosen based on literature. In order to arrive at the blade configuration, strip theory or blade
element momentum (BEM) theory has been used, which relates blade shape to the rotor's ability to
extract power from the wind. The detailed formulations of BEM theory can be found elsewhere
(Manwell et al, 2009). Currently, the case of optimum rotor with wake rotation has been considered.
The blade has been divided into eleven elements as shown in Figure 2. The blade has been twisted
in such a way that angle of attack remains constant at all sections.The angle of attack of the blade at
each section corresponds to a maximum value of (C / C ). The angle of attack corresponding to
L D
(C / C ) (6.5°) is chosen as design angle of attack.
L D maximum
R
V



Figure 2: Schematic representations of blade elements and blade geometry for analysis
dr
c
r
r
R
Ω
dQ
dL dD
Vrel
dT
dN
Plane of the rotation
Chord line V = Relative wind
rel
velocity
p = Section pitch angle
 = Angle of attack
r = Angle of relative wind
dL = Lift force
dD = Drag force
dN = Normal force
DT = Tangential force
DQ = Torque

The chord (c) and the angle of relative wind ( ) of the blade at every section has been found from
r
Equations (3) and (4) (Manwell et al., 2009)
(3)
(4)
Where , r is the radial length of the element and R is the rotor radius. B is the number of
blades.The blade twist (θ ) is given by
T
(5)
θ is the blade pitch angle and θ is the blade pitch angle at the tip. θ can be obtained from
p p,0 p
(6)
α is the design angle of attack (the angle between chord line and the relative wind). The chord and
twist variations of the blade found from BEM theory are given in Table 1. The CAD model of the
blade is shown in Figure 3.

1
2 1
tan
3
r
r


  
  
 
 
8
1 cos r
Ldesign
r
c
BC


 
r
r
R
 
 
  
 
,0
T p p
  
 
p r
  
 
S. No
Radius (r)
(mm)
Chord (c)
(mm)
Twist angle (θT)
(degree)
1 25 35.872 31.232
2 45 32.852 20.229
3 65 27.13 13.680
4 85 22.452 9.5624
5 105 18.942 6.7943
6 125 16.299 4.8246
7 145 14.267 3.3586
8 165 12.666 2.2280
9 185 11.377 1.3310
10 205 10.321 0.6027
11 225 9.4400 0
Table 1: Geometry of the blade

Figure 3: CAD model of the blade
Figure 4: Modeled rotor geometry
CFD MODELLINGANDANALYSIS
Preprocessing:
The blade and the whole rotor assembly were modeled using the preprocessor GAMBIT. The co-
ordinates of the geometry of the airfoil were imported into GAMBIT and then connected. The blade,
hub and connecting rod were created as separate volumes and were united using Boolean addition.
The modeled rotor assembly is shown in Figure 4.
The problem under consideration requires modeling of rotating component (rotor and the fluid
region around the rotor) and stationary part (rest of the computational domain). Moving Reference
Frame (MRF) model is one of the approaches for such problems involving multiple zones, and the
same has been adopted in the present study. It is a steady-state approximation in which individual
cell zone moves at different rotational and/or translational speeds. The flow in each moving cell
zone is solved using the moving reference frame equations, which takes into account the Coriolis
acceleration and centripetal acceleration in the momentum equation. For the stationary zone, the
stationary equations are used. At the interfaces between cell zones, a local reference frame
transformation is performed to enable flow variables in one zone to be used to calculate fluxes at the
boundary of the adjacent zone. The detailed formulations are available elsewhere (FLUENT, 2006).
The governing equations have been solved using relative velocity approach, rather than absolute
velocity approach.

Computational Domain :
Two different zones of fluid for treatment in the stationary and moving reference frames have been
created while modeling the computational domain. A cylinder of diameter 1.5D (D is the rotor
diameter) and length 0.5D has been created around the rotor (for rotating part). The fluid passing
inside this region will be analysed using MRF model. Outside this cylinder, another cylinder of
diameter 5D and length 20D has been created (stationary part) with one face of the cylinder located
at a distance of 5D upstream of the rotor and other face of the cylinder located at a distance of 15D
downstream of the rotor. The fluid close to the rotor blades is the region of interest in the present
analysis, hence fine meshing has been adopted in these regions, whereas outside this region
coarse mesh has been used. Since this is an external flow problem, the geometry that is part of the
wind turbine (as a solid) is suppressed from the model. The rotor faces have been meshed using
triangular elements of size 1 mm, using paving scheme. The inner volume has been meshed with
Tetra/hybrid elements. The mesh primarily consists of tetrahedral elements but may include
hexahedral, pyramidal or wedge shaped elements wherever appropriate. Velocity inlet and
pressure outlet boundaries have been defined at the upstream face and downstream face of the
outer cylinder, respectively. Symmetry boundary condition has been assigned to the curved surface
of the outer cylinder. The rotor faces have been assigned wall/no-slip boundary condition. The
mesh comprised of 0.8 million cells. The computational domain with boundary conditions is shown
in Figure 5.
Figure 5: Computational Domain indicating the boundary conditions
(a) Schematic representation (b) Actual mesh generated
Inner Cylinder
(rotating)
Velocity
inlet
Pressure
outlet
Symmetry
Symmetry
Rotor (wall)
(a)
(b)
Inner Cylinder
(rotating)
Velocity
inlet
Pressure
outlet
Symmetry
Symmetry
Rotor (wall)

Numerical Simulation :
Numerical simulations have been carried out using commercial CFD code, FLUENT. Double
precision pressure based solution has been used in the present work to predict good results, by
minimizing truncation errors. The mean velocity at the inlet has been given as 8 m/s (rated wind
speed). Turbulence intensity of 5% has been chosen as the flow has been observed to be fully
developed at this level of turbulence intensity (Mukhund, 2009). The outer diameter of the cylinder
has been assigned as the hydraulic diameter. In the pressure outlet, gauge pressure has been set
to zero and the same turbulence intensity (5%) and hydraulic diameter as velocity inlet were given
to reduce convergence difficulties. The faces of the inner cylinder serve as an interface between
stationary and rotating part of the model. The rotating zone has been selected as the inner cylinder
and the moving reference frame option has been enabled. Corresponding to the tip speed ratio of 6,
the angular velocity has been given for the inner domain fluid.
The choice of the turbulence models influences the resultant flow field and the computational
resource and time required to achieve solutions. Turbulent flows are characterized by eddies with a
wide range of length and time scales. Large scale eddies have dimensions comparable to the
characteristic length of mean flow. Small scale eddies are responsible for dissipation of turbulent
kinetic energy.There are three approaches to modeling turbulence, namely, DNS (Direct Numerical
Simulation), LES (Large Eddy Simulation) and RANS (Reynolds Averaged Navier-Stokes)
approaches. DNS approach involves directly resolving the entire range of turbulent scales. The
3
computational cost for RNS is proportional to Re (Re is the Reynolds number of flow), making DNS
not feasible for practical engineering problems, involving high Reynolds numbers. In LES
approach, the large scale eddies are resolved directly, whereas the small scale eddies are modeled
using sub-grid scale modeling. The computational demand and mesh requirement for LES
approach is lesser than DNS, but many orders of magnitude higher than for RANS approach where
the entire range of turbulent scales are modeled. Hence, in the present study, RANS based
turbulence model has been used for modeling turbulence.
Among RANS based turbulence models, commonly used two-equation turbulence model, viz,
Shear Stress Transport (SST) k- model has been used (model equations available in FLUENT,
2006) since it performs well in flow fields with large separation in comparison with standard k-ε and
standard k- model. SST model combines the positive features of both standard k-ε and standard
k- model by adopting standard k- model near the wall and standard k- ε model near the boundary
layer edge, thereby showing good performance under adverse pressure gradients. The standard k-
model and the k-ε model are both multiplied by a blending function and both models are added
together. The blending function 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 standard k-ε model.
The pressure field is linked to velocity through SIMPLE (Semi-Implicit Method for Pressure linked
equations) pressure-velocity coupling algorithm. For momentum, turbulent kinetic energy and
specific dissipation rate second order upwind discretization scheme has been used. Initial values
for various flow variables over the entire computational domain were set equal to the inlet boundary


 



values. The steady state converged solution has been obtained. The normal force and torque have
been obtained using the rotor disc area as characteristic area, by integrating the pressures acting
on the rotor faces. Power has been obtained as the product of torque and angular velocity.
RESULTSAND DISCUSSIONS
Variation of normal force and torque:
Using the tip speed ratio of 6 initially assumed, the CFD simulations were carried out for different
wind speeds and the performance parameters, namely, normal force, torque and power were
obtained. The variation of normal force, torque and power with wind speed are shown in Figures 6, 7
and 8 respectively.
Figure 6: Variation of normal force with wind speed at a tip speed ratio of 6
Figure 7: Variation of torque with wind speed at a tip speed ratio of 6

Figure 8: Variation of power with wind speed at a tip speed ratio of 6
The variation of normal force and torque with wind speed were quadratic and the variation of power
with wind speed has been found to be cubic. The plots reflect the theoretical variation of normal
force, torque and power (as in Eq. 1) with wind speed. From Figure 8, the value of power (in Watts)
corresponding to rated wind speed of 6 m/s has been observed to be 6 W. The value of C for
power
power of 5.4 W has been found to be 0.26, which deviates from the assumed value of 0.35 by about
24%.Adeviation of this order is acceptable for numerical simulations.
Similarly, the analysis has been carried out using different tip speed ratios for a fixed wind speed of 8
m/s. The variation of torque and power with tip speed ratio is given in Figures 9 and 10 respectively.
The torque has been observed to be almost constant in the tip speed ratio range of 0 to 2. For tip
speed ratio beyond 2, the torque rises steeply and reaches a maximum value at tip speed ratio of
4.7 and then decreases. Above a tip speed ratio of 9, if the flow is forcefully rotated at the required
angular velocity by MRF approach, generation of torque that opposes the motion has been
observed. This could be probably due to continuous decrease in angle of attack beyond a tip speed
ratio of 6, which leads to production of forces and moments in opposite direction. Detailed
investigations are required to study the limitations of applying MRF approach for higher tip speed
ratios.
Figure 9: Variation of torque with tip speed ratio at a wind speed of 8m/s

Figure 10: Variation of power with tip speed ratio at a wind speed of 8m/s
Further, the variation of power with tip speed ratio shows the maximum value of power being
attained at a tip speed ratio of 5.8. Initially, the configuration of the rotor has been obtained based on
tip speed ratio of 6. The maximum power being attained at the same tip speed ratio shows that the
results are in agreement with the theory, with a variation of 3.33 %. Beyond the tip speed ratio of 5.8,
power reduces with increase in tip speed ratio.
Flow field analysis:
The relative velocity vectors were plotted at different sections along the span of the blade. For a
wind speed of 8m/s and using a tip speed ratio of 6, the vector plots of relative velocity at two typical
sections with radius 0.065 m and 0.185 m, are shown in Figures 11 and 12 respectively. Since the
optimum tip speed ratio has been used in calculating the angular velocity, the flow has been smooth
and no flow separation has been identified. The flow separation has not been observed for wind
speeds in the range of 5 m/s to 9 m/s. However, for wind speed of 3 m/s and 4 m/s, the flow has been
observed to be separated in two sections with radius of 0.065 m and 0.105 m as shown in Figures
13 and 14. This could probably have lead to lower values of the normal force and torque as
observed in Figures 6 and 7.
Figure 11: Flow field at r = 0.065 m for tip speed ratio of 6 and wind speed of 8 m/s

Separated flow
Separated flow

CONCLUSIONS
In the present study, the configuration of a small HAWT has been obtained based on BEM theory.
The rotor blade configuration has been obtained, based upon the criteria that the angle of attack at
each section remains constant and equals to the value corresponding to maximum C / C of the
L D
chosen blade (NACA 4418) The computational analysis of 1:13 scaled model of the wind turbine
.
rotor has been carried out using GAMBIT as preprocessor, with analysis and post processing done
in FLUENT. An attempt to use the MRF technique with constant tip speed ratio for the analysis of
rotating part of the computational model comprising of rotor has been successful, with certain
limitations. Variation of normal force, torque and power with wind speed for an optimum tip speed
ratio of 6 agree well with the theoretical trend.Also, for a fixed wind speed of 8m/s, torque and power
were plotted against tip speed ratio. The maximum power has been obtained at the tip speed ratio of
5.8, which is in agreement with the initial assumption of 6 (with error of 3.33 %). However, unsteady
CFD simulations are required to get real physics of the flow around the wind turbine, but are
computationally very intensive. The results of CFD have to be validated with the boundary layer
wind tunnel experimental results by conducting tests on scaled models and full-scale
measurements on prototype structure.
ACKNOWLEDGMENT
This paper is being published with the kind permission of Director, CSIR-SERC, Chennai. The
authors acknowledge with thanks the fruitful technical discussions and valuable suggestions
provided by Dr. P. Harikrishna, Shri. G. Ramesh Babu and Dr. S. Arunachalam from Wind
Engineering Laboratory of CSIR-SERC.
REFERENCES
1. Phadke, A., Bharvirkar, R. and Khangura, J., (2012), “Reassessing wind potential estimates
for India-Economic and Policy Implications.” International Energy Studies.
2. Howell, R., Qin, N., Edwards, J., Durrani, N., (2010), “Wind tunnel and numerical study of a
small vertical axis wind turbine.” Renewable Energy, Vol 35, 412-422.
3. Digraskar, D.A., (2010) “Simulations of Flow over Wind Turbines.” Master's thesis, University
of Massachusetts,Amherst.
4. Fingersh, L.J., Simms, D., Hand, M., Jager, D., Cotrell, J., Robinson, M., Schreck, S.,
Larwood, S., (2001), “Wind tunnel testing of NREL's unsteady aerodynamics experiment.”
AIAAPaper 2001-0035, 194-200
5. Rajendran, C., Madhu, G., Tide, P.S. and Kanthavel, K., (2011), “Aerodynamic Performance
analysis of Horizontal Axis Wind Turbine using CFD technique.” European Journal of
Scientific Research, Vol 65 (1), 28-37.
6. Carcangiu, C. E., (2008), “CFD-RANS Study of Horizontal Axis Wind Turbines.” Doctoral
thesis, Università degli Studi di Cagliari, Cagliari, Italy.

7. Duque, E.P.N., Burklund, M.D., and Johnson, W., (2003), “Navier Stokes and Comprehensive
Analysis Performance Predictions of the NREL Phase VI Experiment.” Journal of Solar
Energy Engineering, Vol 125, 457-467.
8. Sezer-Uzol and Lyle N. Long., (2006), “3D Time-Accurate CFD simulations of wind turbine
th
rotor flow fields.” 44 AIAAAerospace sciences meeting and exhibit.
9. Gonzalez, A., and Munduate, X., (2008), “Three Dimensional and Rotational Aerodynamics
on NRELPhase VI WindTurbine Blade.” Journal of Solar Energy Engineering, Vol 130, 17.
10. Sajjan, S.V., Savanur, R.A., and Mudkavi, V.Y., (2009), “CFD Analysis of 500kW Horizontal
th
Axis Wind Turbine Blades: Straight and Bent Cases.” 11 Annual CFD Symposium, 2009,
Bangalore.
11. Streiner, S., Kramer, E., Eulitz, A., and Armbruster, P., (2007), “Aeroelastic analysis of wind
turbine applying 3D CFD computational results.” Journal of Physics: Conference Series, Vol
75, 1-8.
12. Luo, J.Y., Issa, R.I., and Gosman, A.D., (1994), “Prediction of Impeller-Induced Flows in
Mixing Vessels Using Multiple Frames of Reference.” In IChemE Symposium Series, No 136,
pp 549-556.
13. Manwell, J.F., McGowan, J.G., and Rogers, A.L., (2009) “Wind Energy Explained: Theory,
Design andApplication.” Second Edition, John Wiley & Sons Ltd, United Kingdom.
14. FLUENT6.3, 2006, User's Guide,ANSYS Fluent Inc, Lebanon, USA.
15. Mukhund, P.R., (2009), “Wind and Solar Power systems-Design, Analysis and Operation.”
Taylor & Francis, USA.

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