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11th International Conference Interdisciplinarity in Engineering, INTER-ENG
2017, 5-6 October
2017, Tirgu-Mures, Romania
11th International Conference Interdisciplinarity in Engineering, INTER-ENG 2017, 5-6 October
2017, Tirgu-Mures, Romania
Aerodynamics and structural analysis of wind turbine blade
Aerodynamics
and
structural
of
windMESIC
turbine
a,
b analysis
b blade
Manufacturing
Engineering
Society
International
Conference
2017,
2017,
28-30 June
Sanaa
El Mouhsine
*, Karim
Oukassou
, Mohammed
Marouan
Ichenial
, Bousselham
P
P0F
2017, Vigo
(Pontevedra), Spain
a
P
P
P
P
a
b
Kharbouch
, Abderrahmane
Sanaa El Mouhsinea, *, Karim
Oukassou
, MohammedHajraoui
Marouan Ichenialb, Bousselham
a
a
Energetic
Laboratory,
Sciences Faculty,
AEU, Tetouan, BP: 2121,
93030, Morocco
Kharbouch
,optimization
Abderrahmane
Hajraoui
Costing models
for
capacity
in Tetouan
Industry
4.0: Trade-off
P
P
P
P
P0F
P
P
P
P
a
P
P
P
b
P
P
Systems of Communications and Detection Laboratory, FS Tetuan, BP: 2121, Tetouan 93030, Morocco
Energetic Laboratory,
Faculty, AEU,
Tetouan,
BP: 2121, Tetouan 93030,
Morocco
between
used Sciences
capacity
and
operational
efficiency
Systems of Communications and Detection Laboratory, FS Tetuan, BP: 2121, Tetouan 93030, Morocco
P
P
a
P
P
b
P
P
Abstract
A. Santanaa, P. Afonsoa,*, A. Zaninb, R. Wernkeb
a
of
4800-058
Guimarães,
Portugal
Abstract
The ultimate objective of the paper is toUniversity
increase
theMinho,
reliability
of wind
turbine
blades through the development of the airfoil
b
Unochapecó,
89809-000begins
Chapecó,
structure, to calculate an optimum blade shape
for the procedure
withSC,
theBrazil
choice of airfoils characteristics. Then an initial
The ultimate
objective
of the paper
is blade
to increase
themomentum.
reliability of
wind
turbine
through
the development
of the
airfoil
wind
blade design
is determined
using
element
The
blade
plays blades
a pivotal
role, because
it is the most
important
structure,
to
calculate
an
optimum
blade
shape
for
the
procedure
begins
with
the
choice
of
airfoils
characteristics.
Then
an
initial
part of the energy absorption system. Practical horizontal axis wind turbine (HAWT) designs use airfoils to transform the kinetic
wind
design
determined
using and
blade
The blade
pivotal
role,
because
is greatest
the mostefficiency.
important
energyblade
in the
windisinto
useful energy
it element
has to bemomentum.
designed carefully
to plays
enablea to
absorb
energy
withitits
Abstract
part
themany
energy
absorption
system.aPractical
horizontal
axis factor
wind turbine
(HAWT)
designs
use airfoils
to transform
kinetic
Thereofare
factors
for selecting
profile. One
significant
is the chord
length
and twist
angle which
depend the
on various
energy
in the windthe
intoblade.
usefulInenergy
and the
it has
to besections
designed
carefully
to enable
absorb
energy
with itsare
greatest
values throughout
this work,
airfoil
used
in horizontal
axistowind
turbine
(HAWT)
S818;efficiency.
S825 and
Under
themany
concept
offor"Industry
4.0", production
processes
be pushed
to twist
be increasingly
interconnected,
There
are
factors
selecting
One significant
factor iswill
the chord
and
angle which
depend
various
S826 airfoils
used
in NREL
phasea 2profile.
and phase
3 wind turbines.
They
havelength
several
advantages
in meeting
theonintrinsic
information
based
on
a
real
time
basis
and,
necessarily,
much
more
efficient.
In
this
context,
capacity
optimization
values
throughout
the blade.
In this
work, of
thedesign
airfoil sections
used in horizontal
axisand
wind
turbine properties.
(HAWT) areThe
S818;
and
requirements
for wind
turbines
in terms
point, off-design
capabilities
structural
lift S825
and drag
goes
beyond
the
traditional
aim
of capacity
maximization,
contributing
also
for
profitability
andintrinsic
value.
S826
airfoilsdata
used
in
NREL
phase
2 andarephase
3 wind
They
have
several
advantages
in meeting
the
coefficients
for
these
airfoils
sections
available
and turbines.
Matlab
code
were
used
toorganization’s
obtain
the coordinates
of a wind
turbine
Indeed,
leanformanagement
and
continuous
improvement
approaches
suggest
capacity
optimization
instead
of
requirements
wind
in terms
of design
point,
off-design
capabilities
and structural
properties.
The
lift
and drag
blade. Aerodynamic
andturbines
static structural
analyses
are
presented.
The
commercially
available
software
FLUENT
is employed
for
maximization.
The
study
of
capacity
optimization
and
costing
models
is
an
important
research
topic
that
deserves
coefficients
data
for
these
airfoils
sections
are
available
Matlab
code
were
used
to
obtain
the
coordinates
of
a
wind
turbine
calculation of the flow field using the Reynolds-averaged Navier Stokes (RANS) in conjunction with the k-omega shear stress
blade. Aerodynamic
and
structural method
analyses
are presented.
The
commercially
available
software
FLUENT
employed
for
contributions
both
the practical
and
theoretical
perspectives.
This
paper
presents
and
discusses
a ismathematical
transport
(SST),from
based
onstatic
finite-element
(FEM).
Both
grid
and
time
step
were
optimized
to reach
independent
solutions.
calculation
ofwork
the represents
flow
field using
the
Reynolds-averaged
Navier
Stokes
(RANS)
in conjunction
with
the
k-omega
shear
stress
The present
the basis
to
develop
an accurate
threemodels
dimensional
Turbine
(HAWT)
model
for capacity
management
based
on different
costing
(ABCHorizontal-Axis
and
TDABC).Wind
A generic
model
has model
been
transport
(SST),
on finite-element
method
(FEM).
Both
grid andstrategies
time step towards
were optimized
to reach independent
solutions.
and may be
useditbased
towas
support
wind
tunnel experiments.
developed
and
used
to analyze
idle
capacity
and
to design
the maximization
of organization’s
The
present
work
represents
the
basis
to
develop
an
accurate
three
dimensional
Horizontal-Axis
Wind
Turbine
(HAWT)
model
value. The trade-off capacity maximization vs operational efficiency is highlighted and it is shown that capacity
and2018
mayThe
be used
to support
windby
tunnel
experiments.
©
Authors.
Published
Elsevier
B.V.
optimization might hide operational inefficiency.
Peer-review
under responsibility ofthe scientific committee of the 11th International Conference Interdisciplinarity in
©
© 2017
2018 The
The Authors.
Authors. Published by Elsevier B.V.
©
2018 The Authors. Published by Elsevier B.V.
Engineering.
Peer-review
responsibilityofofthe
thescientific
scientificcommittee
committee
Manufacturing
EngineeringInterdisciplinarity
Society International
Conference
Peer-review under responsibility
ofof
thethe
11th
International Conference
in Engineering.
Peer-review under responsibility ofthe scientific committee of the 11th International Conference Interdisciplinarity in
2017.
Engineering.
Keywords:
wind turbine; blade design; Betz limit; blade loads; aerodynamic.
Keywords: Cost Models; ABC; TDABC; Capacity Management; Idle Capacity; Operational Efficiency
Keywords: wind turbine; blade design; Betz limit; blade loads; aerodynamic.
1. Introduction
cost of idle
capacity
is a fundamental information for companies and their management of extreme importance
* The
Corresponding
author.
Tel.: +212-662-729-823.
in modern
production
systems.
In general, it is defined as unused capacity or production potential and can be measured
E-mail address: sanaaelmouhsine0@gmail.com
in* several
ways:author.
tonsTel.:
of production,
available hours of manufacturing, etc. The management of the idle capacity
Corresponding
+212-662-729-823.
E-mailAfonso.
address:
sanaaelmouhsine0@gmail.com
* Paulo
Tel.:
+351 253 510 761; fax: +351 253 604 741
E-mail address:
psafonso@dps.uminho.pt
2351-9789©
2018 The
Authors. Published by Elsevier B.V.
Peer-review under responsibility ofthe scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
2351-9789©
2351-9789
© 2018
2017 The Authors. Published by Elsevier B.V.
B.V.
Peer-review under
under responsibility
responsibility of
ofthe
International
Conference
Interdisciplinarity
Engineering.
Peer-review
the scientific committee of the 11th
Manufacturing
Engineering
Society
InternationalinConference
2017.
2351-9789 © 2018 The Authors. Published by Elsevier B.V.
Peer-review under responsibility of the scientific committee of the 11th International Conference Interdisciplinarity in Engineering.
10.1016/j.promfg.2018.03.107
748
755
Sanaa El Mouhsine et al. / Procedia Manufacturing 22 (2018) 747–756
Sanaa El Mouhsine et al. / Procedia Manufacturing 00 (2018) 754–763
1. Introduction
The power efficiency of wind energy systems has a high impact in the economic analysis of this kind of
renewable energies. The efficiency in these systems depends on many subsystems: blades, gearbox, electric
generator and control. Some factors involved in blade efficiency are the wind features, e.g.
Its probabilistic distribution, the mechanical interaction of blade with the electric generator, and the strategies
dealing with pitch and rotational speed control [1]. It is a complex problem involving many factors, relations and
constraints. The design of optimal blades involves aerodynamic, structural and control problems. However, the
design cycle can be practically approached as an iterative and stepped method. For aerodynamic optimization the
blade can be modelled as a series of sections along the pitch axis. Each section has an airfoil shape, chord length and
attach angle which is the result of a collective pitch angle and a local twist one.
This last is a property of the blade while the pitch angle depends on the control strategy of the whole energy
system. The computation of the wind flow around rotating blades is a very complex problem. For a precise
knowledge of the wind flow and the induced forces in the turbine surfaces it is necessary to solve the threedimensional Navier-Stokes equations in a rotating frame, but the computational cost to obtain such precise solution
prohibits their use in the design and analysis environments [2]. The blade element momentum theory (BEM) is
basically a one-dimensional simplified theory that is used routinely by wind power industry because it provides
reasonably accurate prediction of performance [3]. The BEM theory has shown to give good accuracy with respect
to time cost, and at moderate wind speeds, it has sufficed for blade geometry optimization [4,5,6]. The BEM theory
is the composition of two different approaches to study the forces in a wind turbine. The first is the momentum
theory that studies the global changes in wind momentary, axial and tangential, in an ideal turbine. Changes in axial
and rotational moment between upwind and downwind induce thrust and torque respectively in the rotor. The wind
flow is split in many differential non interacting annular stream tubes.
The second theory, the blade element, studies the aerodynamic forces acting in a local airfoil. As in aeronautics
wing theory, the forces are lift, which is perpendicular to the wind direction, and drag that is in the same direction.
Drag is mainly generated by friction between the viscous fluid and the airfoil surface. It is a dissipative force that
generates power loss and lack in momentum changes. The applications of thick airfoils are extended to the
assessment of wind turbine performance. It is well established that the power generated by a Horizontal-Axis Wind
Turbine (HAWT) is a function of the number of blades B, the tip speed ratio λ (blade tip speed/wind free stream
velocity) and the lift to drag ratio (C l /C d ) of the airfoil sections of the blade. The airfoil sections used in HAWT are
generally thick airfoils such as the S818, S825 and S826 of airfoils. These airfoils vary in (C l /C d ) for a given B and
λ, and therefore the power generated by HAWT for different blade airfoil sections will vary. Another goal of this
study is to evaluate the effect of different airfoil sections on HAWT performance using the Blade Element
Momentum (BEM) theory.
Nomenclature
C L Lift coefficient
C D Drag coefficient
C P Pressure coefficient
C Airfoil chord length (m)
P Pressure (Pa)
ρ Density of Air (kg/m3)
U Flow velocity vector (m/s)
µ Dynamic viscosity kg/(m/s)
µ t Turbulent viscosity (kg/m/s)
K Turbulent Kinetic energy (m²/s²)
ɛ Dissipation of turbulent kinetic energy (m²/s3)
v r Relative velocity (m/s)
ω Angular velocity (rad/s)
β* Turbulent stress tenser
α Angle of Attack (°)
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749
Pitch Angle of Blade to Rotor Plane (°)
φ Angle of Relative Wind to Rotor Plane (°)
β
2. Airfoils and General Concepts of Aerodynamics
A number of terms are used to characterize an airfoil. The mean camber line is the locus of points halfway
between the upper and lower surfaces of the airfoil. The most forward and rearward points of the mean camber line
are on the leading edge and trailing edges, respectively. The straight line connecting the leading and trailing edges is
the chord line of the airfoil, and the distance from the leading to the trailing edge measured along the chord line is
designated as the chord of the airfoil. The thickness is the distance between the upper and lower surfaces, also
measured perpendicular to the chord line. Finally, the angle of attack α is defined as the angle between the relative
wind and the chord line.
a
b
Fig. 1. (a) Angle of Attack and Chord Line of an Airfoil, (b) Airfoil cross-sections used in the design of the wind turbine rotor blades
3. Lift, drag and non-dimensional parameters
Theory and research have shown that many flow problems can be characterized by non-dimensional parameters.
The most important non-dimensional parameter for defining the characteristics of fluid flow conditions is the
Reynolds number. Force and moment coefficients, which are a function of Reynolds number, can be defined for
two- or three-dimensional objects. Force and moment coefficients for flow around two-dimensional objects are
usually designated with a lower case subscript lift and drag coefficients that are measured for flow around two- or
three-dimensional object are usually designated with an upper case subscript. Rotor design usually uses twodimensional coefficients, determined for a range of angles of attack and Reynolds numbers, in wind tunnel tests. The
two-dimensional lift coefficient is defined as:
Cl =
Ll
1 2 ρU 2c
(1)
The two-dimensional drag coefficient is defined as:
Cd =
Dl
1 2 ρU 2c
(2)
where ρ is the density of air, U is the velocity of undisturbed airflow, c is the airfoil chord length and l is the airfoil
span. Other dimensionless coefficients that are important for the analysis and design of wind turbines include the
power and thrust coefficients and the tip speed ratio, the pressure coefficient, which is used to analyze airfoil flow:
Sanaa
El Mouhsine
et al. / Procedia
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22 754–763
(2018) 747–756
Sanaa El
Mouhsine
et al. / Procedia
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00 (2018)
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757
Cp 
p  p
(3)
1 2 ρU 2
Under similar ideal conditions, symmetric airfoils of finite thickness have similar theoretical lift coefficients.
This would mean that lift coefficients would increase with increasing angles of attack and continue to increase until
the angle of attack reaches 90 degrees. The behavior of real symmetric airfoils does indeed approximate this
theoretical behavior at low angles of attack. For example, typical lift and drag coefficients for a S818, S825, and
S826airfoils,the profiles of which are shown in Fig. 2 to 3 as a function of angle of attack and Reynolds number.
a
b
Fig. 2. (a) Lift coefficients variations vs angle of attack, (b) Drag coefficients for the S818 airfoil at Re=1.106
a
b
Fig. 3. (a) Lift coefficients variations vs angle of attack, (b) Drag coefficients for the S825 airfoil at Re=1.106
a
b
Fig. 4. (a) Lift coefficients variations vs angle of attack, (b) Drag coefficients for the S826 airfoil at Re=1.106.
Note that, in spite of the very good correlation at low angles of attack, there are significant differences between
actual airfoil operation and the theoretical performance at higher angles of attack. The differences are due primarily
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to the assumption, in the theoretical estimate of the lift coefficient, that air has no viscosity. Surface friction due to
viscosity slows the airflow next to the airfoil surface, resulting in a separation of the flow from the surface at higher
angles of attack and a rapid decrease in lift. This condition is referred to as stall. Airfoils for horizontal axis wind
turbines (HAWTs) often are designed to be used at low angles of attack, where lift coefficients are fairly high and
drag coefficients are fairly low. The lift coefficient of this symmetric airfoil is about zero at an angle of attack of
zero and increases to over 1.0 before decreasing at higher angles of attack. The drag coefficient is usually much
lower than the lift coefficient at low angles of attack. It increases at higher angles of attack. The lift coefficient at
low angles of attack can be increased and drag can often be decreased by using a cambered airfoil.
4. Blade Element Momentum (BEM) Theory
The blade element momentum (BEM) theory is a compilation of both momentum theory and blade element
theory [6,7]. Momentum theory, which is useful in predicted ideal efficiency and flow velocity, is the determination
of forces acting on the rotor to produce the motion of the fluid. Theory determines the forces on the blade as a result
of the motion of the fluid in terms of the blade geometry. By combining the two theories, BEM theory, also known
as strip theory, relates rotor performance to rotor geometry.
5. Aerodynamic Load
Aerodynamic load is generated by lift and drag of the blades airfoil section, which is dependent on wind velocity,
blade velocity, angle of attack and yaw [8]. The angle of attack is dependent on blade twist and pitch. The
aerodynamic lift and drag produced are resolved into useful thrust in the direction of rotation absorbed by the
generator and reaction forces. It can be seen that the reaction forces are substantial acting in the flat wise bending
plane, and must be tolerated by the blade with limited deformation. For calculation of the blade aerodynamic forces
the widely publicized blade element momentum (BEM) theory is applied. Working along the blade radius taking
small elements δr, the sum of the aerodynamic forces can be calculated to give the overall blade reaction and thrust
loads.
6. Blade Geometry
The main objective in the design of wind turbines is to find a rotor that meets the basic conditions requested. The
most important condition is to get a rotor to deliver output power required at a particular speed. For this, the first
assumption of the aerodynamic rotor is its diameter, which can be roughly estimated power. In addition, it is
necessary to take into account the importance of the geometry of the rotor, taking into consideration the most
important, the aerodynamic performance, strength and stiffness conditions, and costs. However, power generation
through wind turbines also play a decisive role in the design of the aerodynamics of the rotor, which is influenced by
other parameters such as power generator and control system. The results of the optimal distribution of the cord and
twist for a blade of 43.2 m in diameter and having various profiles are summarized in Fig. 5.
a
b
Fig. 5. (a) Chord length distribution as function of radius, (b) twist distribution as function of radius for Horizontal-Axis wind turbine calculated
with blade element momentum methods.
Sanaa El Mouhsine et al. / Procedia Manufacturing 22 (2018) 747–756
Sanaa El Mouhsine et al. / Procedia Manufacturing 00 (2018) 754–763
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759
a
b
Fig. 6. (a) Airfoils superposed on the wind turbine blade and (b) Top view of a subset of the airfoil cross-sections illustrating blade twisting.
7. Mathematic Model
The governing equations are the continuity and Navier-Stokes equations. These equations are written in a frame
of reference rotating with the blade. This has the advantage of making our simulation not require a moving mesh to
account for the rotation of the blade. The equations that we will use look as follows:
Conservation of mass:
∂ρ
+ ∇.ρvr =0
∂t
(4)
Conservation of Momentum (Navier-Stokes):
∇.( ρvr ) + ρ ( 2ω × vr × ω × ω × r ) =−∇p + ∇.τ r
(5)
Wherev r is the relative velocity (the velocity viewed from the moving frame) and ω is the angular velocity.
7.1. Turbulence model. The k-omega SST turbulence model
The SST 𝑘𝑘 − 𝜔𝜔 turbulence model [9,10] is a two equation eddy-viscosity model which has become very popular.
The shear stress transport (SST) formulation combines the better of two worlds. The use of a 𝑘𝑘 − 𝜔𝜔 formulation in
the inner parts of the boundary layer makes the model directly usable all the way down to the wall through the
viscous sub-layer; hence the SST 𝑘𝑘 − 𝜔𝜔 model can be used as a Low-Re turbulence model without any extra
damping functions. The SST formulation also switches to a 𝑘𝑘 − 𝜀𝜀 behaviour in the free-stream and thereby avoids
the common 𝑘𝑘 − 𝜔𝜔 problem that the model is too sensitive to the inlet free-stream turbulence properties. Authors
who use the SST 𝑘𝑘 − 𝜔𝜔 model often merit it for its good behaviour in adverse pressure gradients and separating
flow. The SST 𝑘𝑘 − 𝜔𝜔 model does produce a bit too large turbulence levels in regions with large normal strain, like
stagnation regions and regions with strong acceleration. The SST 𝑘𝑘 − 𝜔𝜔 turbulence model is governed by:
∂ui
∂
Dρk
= τij
+ β* ρωk +
∂x j
∂x j
Dt

 μ + σ μ ∂k
k t ∂x

j

(
)






1 ∂k ∂ω


∂u
Dρω
i − βρω2 + ∂  μ + σ μ  ∂ω  +2 ρ ( 1 − F1 ) σ ω
= νγ τ


t
ij


Dt
k
∂
x
∂
x
∂
x

ω ∂x j ∂x j
t
j
j 
j 
where β* =ε kω and the turbulence stress tensor is
(6)
(7)
Sanaa El Mouhsine et al. / Procedia Manufacturing 22 (2018) 747–756
Sanaa El Mouhsine et al. / Procedia Manufacturing 00 (2018) 754–763
760
 ∂u

∂u j 2 ∂u
k δ  − 2 ρkδ
τij =
μt  i +
− ρu'i u'j =
−
ij
 ∂x j ∂xi 3 ∂x ij  3
k


753
(8)
=
The turbulence viscosity can be estimated
by νt a1k max (a1k, ΩF2 ) , where Ω is the absolute value of the
vorticity, and the function F2 is given by:

 2 k 500ν  



F2 = tanh  max 
' y2ω 

0.09ωy





2
(9)
where y is the distance to the nearest surface, the coefficients β, γ, σ k and σ ω is defined as functions of the
coefficients of the k − ω and k − ε turbulence models and they are listed as follows:
β= F1 β1 + (1 − F1 ) β2 ,γ= F1 γ1 + (1 − F1 ) γ2
(10)
σ k  F1σ k 1  1 F1  σ k 2 ,σ ω  F1σ ω1  1 F1  γ2 σ ω 2
(11)
where F1 function is:



k  4 ρσ ω 2 k  

F1 = tanh   min  max 

,
0.09ωy  CDkω y 2  







4





(12)
The coefficient CD kω is:


1 ∂k ∂ω
CDkω = max  2 ρσ ω 2
,10−20 


ω ∂x j ∂x j


Table 1. The empirical constants of the k − ω SST model are as follows:
β*
σ
β1
β2
γ1
γ2
σ k2
k1
0.09
0.075
0.075
0.5532
0.4404
0.85
1.0
(13)
σω1
0.5
σ ω2
0.856
7.2. Mesh Generation
In order to create the computational domain and generate mesh, the commercially available software “ANSYS
Meshing tool” is used to build a wind tunnel model and generate an unstructured mesh around the blade in the
computational domain. As shown in Fig.7, a 3D straight untapered blade is placed inside a computational domain
(mimicking a wind tunnel) with inflow and outflow boundaries. The wall boundary condition is applied to the right
and lift surface of the computational domain. The back and front surfaces of the computational box are set as
symmetry boundary condition due to the free motion of air on these surfaces. As shown in Fig. 9-3, one important
part of the mesh shape is that it must be smooth and dense enough to be suitable for any arbitrary airfoil shape and
3D Horizontal-Axis Wind Turbine. The wind tunnel geometry is always the same, but the airfoil/blade in the center
of the tunnel changes from one generation to the next. This poses a challenge for mesh generation in 3D. Faces are
meshed using quadrilateral cells, and we require that the number of nodes on opposite faces be identical. To ensure
this distribution, we define a set number of nodes (and not relative node spacing) along each edge. Otherwise,
thicker or more cambered airfoil edges would have more nodes than thinner ones if a relative distribution was used.
A refined boundary layer is carefully constructed around the airfoil to capture the boundary layer behavior.
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a
b
Fig. 7. (a) Planar cut to illustrate mesh grading toward the rotor blade, (b) Rotationally periodic domain with wind turbine blade shown in the
center.
8. Result and discussion
The Horizontal-Axis Wind Turbine (HAWT) is 43.2 meters long and starts with a cylindrical shape at the root
and then transitions to the airfoils S818, S825 and S826 for the root, body and tip, respectively. This wind blade also
has pitch to vary as a function of radius, giving it a twist and the pitch angle at the blade tip is 4 degrees.
Accordingly, the stress limit of the blade is determined by the strength of the E-glass used in the skin of the blade.
The turbulent wind flows towards the negative z-direction at 12 m/s which is a typical rated wind speed for a turbine
at this size. This incoming flow is assumed to make the blade rotate at an angular velocity of-2.22 rad/s about the zaxis. The tip speed ratio is therefore equal to 8 which is a reasonable value for a large wind turbine. The blade root is
offset from the axis of rotation by 1 meter. The process of CFD simulation begins with the creation of a three
dimensional domain and its proper discretization. We define the velocity at the inlet of 12 m/s with turbulent
intensity of 5% and turbulent viscosity ratio of 10 and the Pressure of 1 atm in order to validate the present
simulation. As mentioned in the beginning of this work, the aerodynamic performance of wind turbines are
primarily a function of the steady state aerodynamics that is discussed. The analysis presented provides a method for
determining average loads on a wind turbine. However, a number of important steady state and dynamic effects that
cause increased loads or decreased power production from those expected with the BEM theory presented here,
especially increased transient loads.
Fig. 8. Force analysis for S818 airfoil section.
Fig. 9. Force analysis for S825 airfoil section.
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Fig. 10. Force analysis for S826 airfoil section.
a
b
Fig. 11. (a) velocity distribution on the blade surface, (b) Pressure contours at several blade cross-sections at viewed from the back of the blade.
The large negative pressure at the suction side of the airfoil creates the desired lift.
a
b
Fig. 12. (a) Full Blade Deformation for Cut-Out Wind Speed, (b) Stress for Cut-Out Wind Speed.s
Fig. 8 to 10 gives the obtained result of the force analysis on the airfoil sections. Fig. 11 and 12 show Static
pressure, velocity magnitudes, deformation and stress distribution of the Horizontal-Axis Wind Turbine (HAWT).
9. Conclusion
In this study, we applied the finite element model of aerodynamics and static structural analyses of HorizontalAxis Wind Turbine (HAWT). The first part of the paper focused on the wind turbine geometry modeling, mesh
generation, and numerical simulation of Horizontal-Axis Wind Turbine (HAWT). The fluid and structural meshes
are compatible at the interface and may be employed for the coupled FSI analysis. These aerodynamic models have
been coupled with a nonlinear formulation describing the structural dynamics to moderate deformations. A
comprehensive look at blade design has shown that an efficient blade shape is defined by aerodynamic calculations
based on chosen parameters and the performance of the selected airfoils. Aesthetics plays only a minor role. The
optimum efficient shape is complex consisting of airfoils sections of increasing width, thickness and twist angle
towards the hub. This general shape is constrained by physical laws and is unlikely to change. However, airfoils lift
and drag performance will determine exact angles of twist and chord lengths for optimum aerodynamic
performance. Due to the large and flexible structure of the wind turbine blades, there will probably be aeroelastic
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instability. The displacement of the tip of the blade at the nominal wind speed (12 m / s) is obtained (0.045 m) a
reduction in the power performance of the turbine, which implies a reduction in the rated power. In order to do the
intensive study of the structural models and aeroelastic behavior of the blade, the aerodynamic is constructed
correctly.
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