Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002

www.springerlink.com/content/1738-494x DOI 10.1007/s12206-011-0521-x

Aerodynamic design and performance analysis of

multi-MW class wind turbine blade† Bumsuk Kim1,*, Woojune Kim1, Sungyoul Bae1, Jaehyung Park2 and Manneung Kim1

1Green & Industrial Technology Center, Korean Register of Shipping, 305-343, Daejeon, Korea 2New Products R&D Team, DSME, 100-180, Seoul, Korea

(Manuscript Received July 10, 2010; Revised March 31, 2011; Accepted April 24, 2011)

----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Abstract The rotor blade is an important device that converts kinetic energy of wind into mechanical energy. It affects power performance, effi-

ciency of energy conversion, load and dynamic stability of a wind power generation system. This paper presents an aerodynamic design of 3 MW class blade using BEM and confirms that the design satisfies the initial design target by BEM and CFD analysis. To investigate the effects of radial flow at the inboard region, the result of static BEM analysis was compared with the result of CFD analysis. The result of quantitative comparison among thrust force, power coefficient and mechanical power depending on wind speed change is presented. Furthermore, design reference data such as pressure, streamline, torque and thrust force distribution on the blade surface is presented as well.

Keywords: Blade design; Blade element momentum theory; Computational fluid dynamics; Performance analysis; Wind turbine ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 1. Introduction

A wind turbine uses rotor blades to extract and convert ki-netic energy of wind into electrical energy. Therefore, a rotor blade requires optimal aerodynamic shape to maximize its efficiency and to improve power performance. To make opti-mum aerodynamic design of wind turbine blades, blade ele-ment momentum theory (BEMT) is widely used due to its effectiveness in design and rapid calculation. Aerodynami-cally, the evaluated values such as electrical power, power coefficient, axial thrust force, annual energy production (AEP) are concerned to secure design effectiveness of rotor blades. A typical design process starts with determining blade length and rated rotating speed according to design class and specifi-cation, and then design parameters such as blade chord length, twist angle and airfoil distribution are obtained by using BEMT to construct a blade plan form for baseline blade. The pitch and torque control schedule map should be determined to maximize the efficiency and to maintain the target power of blade with completed design.

It is difficult to expect a reliable result from performance analysis by using BEM based aero-elastic code, because it assumes that no momentum exchange exists in the direction of

blade radius. Furthermore, BEMT also has some limitations: first, the aerodynamic data for airfoils are prepared for a fixed Reynolds number; thus it does not match exactly for every blade element. Second, only the analysis of standardized type of blade for horizontal axis wind turbine is possible. Finally, it is impossible to find detailed flow characteristics around rotor blades which may affect the aerodynamic performance and dynamic reliability [1, 2]. To secure the optimal blade design factor, it requires extensive reliable experiments on flow char-acteristics and performance characteristics; however, it is not realistic because of the problem with the cost and the time.

Therefore, there have been various researches using CFD to identify the blade performance and flow characteristics. As CFD analysis utilizes the three-dimensional Navier-Stokes equation as the governing equation, it has the advantage of providing more accurate result of analysis compared to previ-ous aero-elastic code. On the contrary, to acquire reliable re-sult from computational method, a vast amount of computa-tional grids are required and advanced turbulence model needs to be applied [3, 4]. The computational method is very useful for understanding the aerodynamic characteristics of rotor blades, but it consumes too much time and resources; thus it is generally applied at the final performance evaluation stage after all the design process is completed.

In this study, aerodynamic design for variable-speed vari-able-pitch type 3-MW wind turbine blade was completed and analysis results by BEMT and CFD were compared. In addi-

† This paper was recommended for publication in revised form by Associate EditorJun Sang Park

*Corresponding author. Tel.: +82 42 869 9506, Fax.: +82 42 860 6031 E-mail address: bskim@krs.co.kr

© KSME & Springer 2011

1996 B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002

tion, flow characteristics on the blade surface will be pre-sented for reference.

2. Aerodynamic design of 3MW wind turbine blade

2.1 Initial design conditions

Wind turbine blade design starts from deciding the IEC Class as in Table 1. Wind turbine class is defined as the values of reference wind speed (Vref) and turbulence intensity (I15). Reference wind speed is the 10 minutes-averaged value for extreme wind speed which has the recurrence period of 50 years at the height of hub, and turbulence intensity is the value of turbulence intensity with the condition of 10 minutes-averaged wind speed of 15 m/s at the height of hub [5]. By considering the blade design for offshore wind power genera-tion IEC Class IB has selected (high reference wind speed and low turbulence intensity).

Table 2 shows the initial design factors for 3 MW blade cal-culated from nominal generator speed of 1800 rpm and gear ratio of 131:1. λdesign is defined as design tip speed ratio which is normally set at the range of 7 ~ 9 in large wind turbines; as the value of λdesign gets bigger, the blade will be more slender and flexible. A slender blade has the advantage of reducing the load; however, it may cause an interference problem be-tween tower and blade at extreme wind condition and the blade rotation speed may need to be increased to acquire the targeted power output. On the contrary, with a smaller value of λdesign, the blade will be thickened and it causes greater axial thrust force. Therefore, it is very important to set the proper value of λdesign [6].

The rated rotational speed of rotor blade can be calculated by using Eq. (1). It is just a reference value and the exact rota-tional speed will be determined after completing blade design. Annual averaged wind speed acquired from wind resources study at the installed area is applied as design wind speed

(Vdesign), a variable of the Eq. (1). It is well known that aero-dynamic noise could increase significantly and cause prob-lems for inhabitants if the rated rotational speed at the tip goes over 80 m/s. Therefore, in general, the rated tip speed is con-trolled to be set below or around 80 m/s for utility-scale wind turbines.

60 designrated

VD

λπ

⎛ ⎞Ω = ⎜ ⎟

⎝ ⎠. (1)

Fig. 1 shows blade tip speed changing trend per capacity

change of the modern wind turbine. For this research, tip speed is restricted to 75 m/s by referencing the trend in Fig. 1. An offshore wind turbine is less restricted compared to on-shore wind turbine in blade tip speed. However, the interfer-ence problem between blade and tower could occur if blade tip speed is too high.

2.2 Baseline plan form design

Most of the large wind turbines apply pitch control strategy for power regulation and are designed to be operated at vari-able speeds to acquire maximum performance at a broad range of wind speeds. The effective speed range of a doubly-fed induction generator (DFIG) is determined by the inverter ca-pacity. In this study, it is assumed ±30% from nominal operat-ing condition, and speed ranges for generator and rotor blades are listed in Table 3.

Diameter of the blade is decided to 94.8 m by using refer-ence values presented in Table 2. λdesign can be calculated from Eq. (2); for this research it is set to 7.5 since the design wind speed is 10 m/s according to IEC class IB. Tip loss exists be-cause of tip vortex for the rotating blade. To predict such loss, a tip loss model as Eq. (3), which was proposed by Ludwig Prandtl in 1919 and modified by Glauert (1935), is applied [8].

Since the exact flow induction factor value of a, a' can be acquired by iterative calculation after completing blade shape design, thus it is set preliminarily by Eq. (4) in the design stage. Wind turbine blade is designed in tapered and twisted

Fig. 1. Tendency of rated tip speed variation [7].

Table 1. Basic parameters for wind turbine classes, IEC 2nd Ed.

Class I II III IV S

Vref(m/s) 50 42.5 37.5 30

Vref(m/s) 10 8.5 7.5 6

I15 0.18 0.18 0.18 0.18 A

a 2 2 2 2

I15 0.16 0.16 0.16 0.16 B

a 3 3 3 3

Values specified

by designer

Table 2. Basic design parameter.

Rated power 3 MW Swept area 7,058 m2

Rated wind peed 12.1 m/s Rotor speed 15.11 rpm

Diameter 94.8 m Material GFRP

Number of blade 3 Power loss 0.855

Design class IB λdesign 7.5

Rated power 1800 rpm Gear ratio 131:1

B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002 1997

shape to create maximum power output with high efficiency. Tapered shape can be obtained by calculating chord length

at each element and the blade twist distribution can be set via twist angle at the same location. Calculation of blade chord length is possible via Eqs. (5), (6), (7), or (8). Many research-ers have suggested theoretical and/or empirical equations, but not the accuracy is depending on design condition and re-quired specifications.

designdesign

RV

ωλ = (2)

2 21(( / 2)(1 ) / ) 1 ( ) /(1 )12 cos designN af e μ μ λ μ

π− + −− ⎛ ⎞

= ⎜ ⎟⎝ ⎠

(3)

22 2

1 1 1 (1 / )1 , '3 3 3

a a fa f f f aλ μ−

= + − − + = (4)

2 2

2 2

2 4 '

(1 ) ( (1 '))l

c ar N C a a

π λ μλ λμ

=− + +

(5)

2 89

design

l r

Vcr N C v

πλ

= (6)

2 2

22

2 4 ' 1

1'1 1l

c a aar N C a a f

f f

π λ μλ

λμ

⎛ ⎞⎜ ⎟−⎜ ⎟=⎜ ⎟⎛ ⎞ −⎛ ⎞ ⎛ ⎞ ⎜ ⎟− + +⎜ ⎟⎜ ⎟ ⎜ ⎟ ⎝ ⎠⎜ ⎟⎝ ⎠ ⎝ ⎠⎝ ⎠

(7)

8 229 0.8 0.8 l

cr C N

λμ πλ λ λ

⎛ ⎞= −⎜ ⎟⎝ ⎠

(8)

1tan(1 ')

aa

φλμ

−=

+ (9)

θ α φ= − . (10) Eqs. (5) and (6) do not consider the effect of blade tip loss

and drag force. Eq. (7) is the chord length calculation formula with consideration of the blade tip loss and ignores the drag force. Eq. (8) is the simplified practical equation which can acquire the linear approximation result directly per 70% ~ 90% of blade radius direction. No matter which of them is chosen, the lift coefficient is required at angle of attack where blade tip airfoil represents the maximum lift to drag ratio. NACA 64-618 is used for tip airfoil for the research and analysis of lift and drag force is accomplished by using X-Foil,

the airfoil aerodynamic characteristics analysis code based on panel method. The result of the analysis shows that the maxi-mum lift to drag ratio of NACA 64-618 appears at angle of attack being 4° and the value of Cl is 1.05.

Calculated blade chord length distributions by applying the equations from Eqs. (5)-(8) are shown in Fig. 2. For the result of Eqs. (6) and (7), it does not show much difference except in certain area of tip. For Eq. (5), there exist differences in cer-tain areas of hub and tip. Flow induction factors are calculated by Eq. (4), and chord length distribution is determined by Eq. (5) at design stage. The result shown in Fig. 2 for Eq. (5) has an excessively large value for the hub; thus chord length dis-tribution is simplified by using a straight line drawn through the 70% and 90% of span position from the blade root. The final result for chord length distribution is shown in Fig. 2. If they are compared to the value calculated from Eq. (8), it shows the chord length distribution being smaller towards the tip and larger towards the hub.

To calculate twist angle of blade, Eq. (9) is used to calculate inflow angle (φ ) at each blade element. Twist angle can be calculated by Eq. (10) and the final twist angle distribution is shown in Fig. 3.

2.3 Aerodynamic characteristics of airfoils

To determine cross-sectional shape of the blade, five DU-series airfoils developed by Delft University and one NACA- series airfoil are introduced.

Table 3. Determination of rotating speed range.

Item Value

Nominal generator speed 1,800 rpm

Gearbox ratio 131:1

Inverter range 70 % ~ 130 %

Rotor speed (min.) 9.62 rpm

Rotor speed (rated) 15.11 rpm

Rotor speed (max.) 17.86 rpm

Nominal generator torque 14.47 kNm

Fig. 2. Comparison of blade chord length.

Fig. 3. Twist angle distribution.

1998 B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002

DU00-W-410, DU00-W-350, DU97-W-300, DU91-W2-250, DU 93-W-210, and NACA 64618 airfoils are applied from hub to tip. Airfoil arrangement refers to the relative posi-tion of NM 3000 blade, 3 MW model developed by LM [9, 10], and detailed specification is listed in Table 4.

On the process of BEM analysis, aerodynamic data must be prepared for each blade element. It is well known that the airfoil lift coefficient of a rotating blade has a greater value than the predicted lift coefficient in 2-D or lift coefficient without rotation. Therefore, the predicted results obtained from BEMT based code do not reflect the 3-D rotating effects, especially for inboard region of blades, and some errors are inevitable [11].

Furthermore, a wind turbine blade will not be in deep stall during normal power production, but it has the possibility of stalling if the extreme wind speed changes, and if malfunction occurs for the yaw or pitch device. Therefore, comprehensive aerodynamic data set range from -180° to +180° must be pre-pared for each blade element.

With the stall delay by the rotational effect, lift coefficient, drag coefficient and pitching moment coefficient are acquired by applying aspect ratio and Reynolds number per each blade element for this research. ATG V.3.1 developed by ECN (En-ergy research Center of the Netherland) is used for aerody-namic data preparation and lift coefficients, drag coefficients and pitching moment coefficients and are shown in Figs. 4, 5 and 6, respectively.

3. Performance analysis by BEM code

GH-Bladed is integrated load calculation software devel-oped by Garrard-Hassan and widely used to calculate aerody-namic and structural loads of wind turbine system. Its aerody-namic calculation module is based on BEM theory; thus it is chosen to predict blade power performance in this study. Fig. 7 shows the changes in mechanical power for variation of λ. λdesign value was 7.5 as mentioned in design stage, and maxi-mum efficiency occurred at the design λ with CP max of 0.462.

Fig. 8 shows the mechanical power distribution of design blade for variable wind speeds. Mechanical power turns into electrical power as it goes through drive train and generator. Since the goal of this research was to design a blade which generates 3 MW of electrical power, the mechanical power shown in Fig. 8 is always higher than electrical power due to

the system loss. At rated condition, mechanical power is pre-dicted a value of 3.31 MW along with 394.5 kN of thrust force and it meets the criteria with condition of rated wind speed at 12.1 m/s. The wind power generation system controls genera-tor torque at below rated wind speed to continuously maintain maximum efficiency. It also controls blade pitch to regulate power output at the rated level in the region above rated wind speed. To find proper blade pitch angles above rated wind speed, numerical iteration is required for pitch angles at each wind speed. After that, pitch schedule map shown in Fig. 9 is made by acquiring pitch angle of the points where electrical output becomes 3.0 MW.

Table 4. Airfoil distribution of LMH 46-5 rotor blade.

Airfoils Location(m) Rate(%)

DU00-W-401 8.717 18.39

DU00-W-350 14.604 30.81

DU97-W-300 19.704 41.57

DU91-W2-250 24.487 51.66

DU93-W-210 28.146 59.38

NACA64618 31.109 65.63

Fig. 4. Comparison of lift coefficients.

Fig. 5. Comparison of drag coefficients.

Fig. 6. Comparison of pitching moment coefficients.

B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002 1999

To operate wind turbine most efficiently, torque control strategy is required below rated wind speed. As shown in Fig. 7, power coefficient has its maximum value at λ=7.5, and is called optimum tip speed ratio. Thus, a variable speed wind turbine controls rotating speed to satisfy optimum tip speed ratio, and the result shown in Fig. 10 is achieved. Mechanical power output and power coefficient with torque and pitch control strategy are plotted together in Fig. 11. Power coeffi-cient is kept at maximum value at the wind speeds from 4 m/s to 10 m/s continuously. Also, it is confirmed that due to the maximum efficiency maintained for wider region, more power output can be achieved at low wind speed. In the aspect of

pitch control, power output above rated wind speed is main-tained at rated value, but the power coefficient is decreased continuously since pitch control strategy regulates power per-formance even though the potential wind energy is getting higher.

4. CFD simulation

4.1 Computational grid and calculation conditions

Computational grid domain is divided into rotational part and stationary part. Rotational part is configured with domain which surrounds the blade and the rest. To generate numerical grid, ANSYS ICEMCFD V11.0 is used and hexagonal grid is applied for the purpose of improving the accuracy and con-vergence of the solution. About 5.0 million nodes are gener-ated for a single blade domain that rotates, and 1.5 million nodes are used for stationary domain. A numerical grid on the blade surface and surroundings are shown in Fig. 12.

To conduct numerical simulation, rotational speed of the ro-tor blade is fixed at the rated value of 15.1145 RPM and 10 cases of wind speed is chosen from cut-in to rated (4 m/s ~ 12.1 m/s). Uniform velocity inlet condition, averaged static pressure outlet condition and rotational periodic condition are applied as the boundary conditions. ANSYS CFX V11.0 and cluster computer with 34 CPU and 40 GB Ram are used for the analysis. The k-ε turbulent model adopted for general CFD code cannot predict the separation accurately; thus lift force is

Fig. 7. Cp – TSR curve.

Fig. 8. Mechanical power curve.

Fig. 9. Pitch schedule curve.

Fig. 10. Torque schedule curve.

Fig. 11. Comparison of Cp and power.

2000 B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002

calculated excessively when stall delay occurs due to high attack angle. This phenomenon is caused by failure to estimate boundary layer separation in the viscosity sub-layer.

Thus, in order to improve the estimation of wall shear stress in the viscosity sub-layer, new models have been developed and applied such as the Wilcox model, BSL (baseline model) model that takes the advantages of Wilcox model, and SST (shear stress transport) model that calculates the transport term of turbulent shear stress. Especially, the SST model is known to accurately predict the size of a vortex and the location of the separation point caused by adverse pressure gradient [12]. Hence, the SST model is chosen to the turbulence model for this study. For the determination of convergence, RMS resid-ual is set to 10-4 and turbulence intensity at inlet boundary surface is set to 16%. Torque and power coefficient values were monitored as reference value of convergence criterion. Calculation was conducted until the point of stabilization of monitored value even at RMS residual was in the range of convergence criterion. It takes about 20 hours per each analy-sis.

4.2 Surface streamlines and pressure distributions

Fig. 13 shows the surface pressure distribution and stream-lines on suction side of the blade. As wind speed increases, the strength of radial flow becomes bigger in the inboard region of suction side. The pressure difference and centrifugal accelera-tion force increase in the direction of hub to tip because the growth of radial flows, and aerodynamic characteristics at the blade inboard region are changed. Generally, power perform-ance is affected negatively due to radial flow, but BEMT as-

sumes that there is no radial interaction between adjacent ele-ments. Therefore, corrections for aerodynamic data consider-ing blade rotation effect should be concerned to perform BEMT analysis. Snel et al. suggested a 3-D correction model for lift coefficients, but it does not contain the correction for drag coefficients [13, 14].

4.3 Thrust and torque acting on blade surface

The load on the blade is the biggest in the direction of rotat-ing axis and it is concentrated at shear web and spar cap. Therefore, in general, the spar cap is designed to be the thick-est laminated structure. It is important to design the spar cap with proper strength since the weight of the blade will increase as laminate thickness increases. Recently, a hybrid type blade with carbon fiber has been applied to reduce the weight and to improve the strength. Axial thrust force distribution on blade surface was investigated for the purpose of finding the region for carbon fiber enhancement and to determine the proper laminate thickness at structural design stage.

Result of analysis of thrust force distribution on suction side of blade is shown in Fig. 14. Thrust force on suction side in-creases as wind speed increases and it is concentrated mainly in the region within 50% from leading edge. It almost corre-sponds to the region where the spar cap is generally placed and can be used as useful information for structural design.

Torque distribution is shown in Fig. 15 and it is useful to find the range and size of torque intensive area on the blade

Fig. 14. Thrust distributions at suction side.

Fig. 15. Torque distributions at suction side.

Fig. 12. Computational grids.

Fig. 13. Surface streamlines at suction side.

B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002 2001

surface while a wind turbine is in normal operation. It is shown that as wind speed increases, the magnitude of blade torque and the effective range for generating torque also in-crease simultaneously. In case of rated condition, most of blade torque occurs mainly in 30% ~ 90% sections from hub at the suction side leading edge area. Therefore, it is important to be careful in selection of airfoil, blade chord length and twist angle for the 30% ~ 90% section when carrying out the blade aerodynamic design.

4.4 Performance analysis

The compared result of blade power output analysis is shown in Fig. 16. Result of CFD analysis was compared di-rectly with the result of GH-Bladed. It shows that the CFD result is relatively in good agreement with the result of GH-Bladed both qualitatively and quantitatively throughout the wind speed range. However, the result of CFD analysis at wind speed of 6, 7 and 8 m/s shows higher value compared to that of GH-Bladed and those discrepancies have effects on power coefficients shown in Fig. 17. At the rated wind speed of 12.1 m/s, 3.28 MW of mechanical power output is pre-dicted by CFD analysis. Fig. 17 shows the result of predicted power coefficient comparison between CFD and GH-Bladed and it is not matched well at 5 ~ 8 m/s range. To confirm the accuracy of two different analysis codes, reliable experiment data need to be compared, but it is almost impossible to ac-quire test data of self designed large blade. Therefore, if the difference of analysis method is used for assessment, the result of Navier-Stokes equation based CFD analysis is more reli-able than the result of analysis based on simplified BEMT. Maximum power coefficient of 3 MW blade is 0.479 for CFD analysis result and 0.462 for GH-Bladed analysis result.

Fig. 18 shows the result of axial thrust force distribution. The result of GH-Bladed and the result of CFD analysis corre-spond fairly well, and the blade axial force gets bigger as wind speed increases.

5. Conclusions

Aerodynamic design of 3 MW wind turbine blade is carried out using BEMT, and performance analysis is performed by BEMT and CFD code. The targeted maximum power output is generated at design wind speed of 10m/s and 3.3 MW is produced at rated wind speed of 12.1m/s. Pitch and torque schedule map is presented. Also it is possible to control the power output for a rated value and maintain maximum effi-ciency for vast range of wind speeds. Flow and performance analyses performed on 3MW blade using CFD code and pres-sure, streamlines, torque and thrust force result are investi-gated. As a result, optimal aerodynamic design is necessary to improve power output in the section 30% ~ 90% from blade hub. And also, strength reinforcement must be concerned within 50% from leading edge where thrust forces are concen-trated. By comparing the maximum power coefficient, CFD predicted about 3.5% higher value than GH-Bladed and thrust force is qualitatively well agreed in all of the wind conditions.

Nomenclature------------------------------------------------------------------------

α : Angle of attack a : Axial flow induction factor a’ : Tangential flow induction factor c : Chord length Cl : Lift coefficient CP,Max : Maximum power coefficient

Fig. 16. Comparison of mechanical power.

Fig. 17. Comparison of power coefficient.

Fig. 18. Comparison of thrust force.

2002 B. Kim et al. / Journal of Mechanical Science and Technology 25 (8) (2011) 1995~2002

D : Diameter of rotor f : Tip loss factor θ : Twist angle of local blade element I15 : Turbulence intensity λ : Tip speed ratio (TSR) λdesign : Design tip speed ratio μ : Non-dimensional radial position, r/R N : Number of blade Ωrated : Rated rotational speed of rotor φ : Inflow angle r : Radius of blade element R : Rotor tip radius νr : Local effective flow velocity Vref : Reference wind speed Vdesign : Design wind speed

References

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[2] M. O. L. Hansen, Aerodynamics of wind turbines, Second Ed., Earthscan, London, UK (2008).

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[5] International Electrotechnical Commission, Wind turbine generator systems Part 1: Safety requirements, Second Ed., IEC-61400-1 (1999).

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[7] European Wind Energy Association, Wind Energy – The Facts, Sterling, London, UK (2009).

[8] H. Glauert, Windmills and fans-Aerodynamic theory, Springer, Berlin, Germany (1935).

[9] C. Lindenburg, E. Bot and H. B. Hendriks, NM 3000-LMH46-5 blade design: Aerodynamic parameter sensitivity study, ECN -C 00 077 (2001).

[10] T. Dobbe, R. Bensoussan and R. van den Berg, Concept design of a 3MW offshore rotor blade: LMH 46-5-X02, OD.00.034, rev.1. (2000).

[11] S. P. Breton, Study of the stall delay using numerical ap-proaches and NREL’s wind tunnel tests, Doctoral Disserta-tion, NTNU (2008).

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[13] H. Snel, R. Houwink and W. J. Piers, Sectional prediction of 3D effects for separated flow on rotating blade, 18th European Rotorcraft Forum (1992).

[14] C. Lindenburg, Modeling of rotational augmentation based on engineering considerations and measurements, European Wind Energy Conference (2004).

Bumsuk Kim received his B. S. in Mechanical Engineering in 2001 from Korea Maritime University, and his M. S. and Ph. D. in Mechanical Engineering in 2003 and 2005, respectively, from Korea Maritime University. He has been a principal research engineer since 2007 in the Green and Industrial Technology

Center, Korean Register of Shipping. His research interests cover aerodynamic and structural design of large wind turbine blade and design assessment.