Numerical simulation for prediction of aerodynamic noise

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7m/s the sound intensity ratio of quadrupole to dipole at P1 location is about 21.1%, but as wind speed increases the sound ... With the purpose of a rough prediction of sound power level, CFD ... noise source can be classified into low frequency noise and ... of wind turbine blades changes according to time, the total.
Journal of Mechanical Science and Technology 25 (5) (2011) 1341~1349 www.springerlink.com/content/1738-494x

DOI 10.1007/s12206-011-0234-1

Numerical simulation for prediction of aerodynamic noise characteristics on a HAWT of NREL phase VI† Jang-Oh Mo1 and Young-Ho Lee2,* 1

Center for Ocean Energy Research and Education, Korea Maritime University, Busan, 606-791, Korea Division of Mechanical and Energy-System Engineering, Korea Maritime University, Busan, 606-791, Korea

2

(Manuscript Received June 17, 2010; Revised January 30, 2011; Accepted January 31, 2011) ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

Abstract The purpose of this study is to numerically predict the characteristics of aerodynamic noise generated from rotating wind turbine blades according to wind speeds using commercial CFD code, FLUENT. The near-field flow around a HAWT of NREL Phase VI is simulated directly by LES, whereas the far-field aerodynamic noise for frequencies below 500 Hz is modeled using FW-H analogy. As there was no experimental noise data, we first compared aerodynamic noise analysis with experimental data. This result showed a difference of power outputs by 0.8% compared with the experimental one with 6.02 kW. Then the characteristics of aerodynamic noise were predicted at a specific location P1 according to IEC 61400-11 international standard. When the wind turbine blades rotate with time, tipvortices occur at the tip of two blades and are generated periodically in a circle. These vortices in the vicinity of the blade tip cause intense aerodynamic noise due to the tip vortex-trailing edge interaction by local cross flows along the trailing edge. In a wind speed of 7m/s the sound intensity ratio of quadrupole to dipole at P1 location is about 21.1%, but as wind speed increases the sound intensity ratio increases up to 54.3% in the case of no-weighted correction. This means that there is a considerably close relation between the quadrupole noise by small and large scales and the increase of wind speeds. With the purpose of a rough prediction of sound power level, CFD results were compared with a simple model of previous researchers and showed a good agreement with one by Hagg of three other models. Keywords: CFD; Large eddy simulations; FW-H analysis; Aerodynamic noise; Sound pressure level; Dipole; Quadrupole; Tip vortex; Horizontal axis wind turbine; Overall sound pressure level; A weighted correction ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

1. Introduction Wind power generation is rapidly increasing worldwide. When supplying the wind power generator, the main focus in the past was put on the output performance. However, as the current technology development covers the required output performance to some extent, the additional problem of noise caused by the wind power generator becomes an important problem because it directly affects nearby residents. When a new wind power generator is designed and manufactured, type approval including noise evaluation is necessary. Among the necessary items for type approval, performance evaluation on the noise is classified as an optional item under the current IEC WT-01 system. However, most of the major countries which install wind turbines request noise evaluations as an essential item. Therefore, noise is considered as one of the important indexes in the product value of wind power †

This paper was recommended for publication in revised form by Associate Editor Jun Sang Park * Corresponding author. Tel.: +82 51 410 4293, Fax.: +82 51 403 0381 E-mail address: [email protected] © KSME & Springer 2010

generators. Generally, the noise caused by a wind turbine is classified into structural noise by machinery and aerodynamic noise by fluid flow. The aerodynamic noise from the blades is generally considered to be the dominant noise source if the mechanical noise is adequately treated [1]. The aerodynamic noise source can be classified into low frequency noise and high frequency broadband noise, as described in Ref. [2]. Previous studies on the aerodynamic noise have been conducted mainly to estimate the turbulence ingestion noise and the blade self noise of high frequency zone in the range of audible limit [3], and the two aerodynamic noise noises are known to have a relatively large influence on the surroundings. According to the tendency of large capacity of the wind power generator, rotational speed of wind turbine blade becomes reduced and the low frequency noise becomes relatively high. As concerns for the harmfulness of low frequency noise are extended, studies for on the influence of low frequency noise on the human body, the growth of livestock and the increase of unpleasantness by the noise are necessary. Therefore, it is expected that more studies for the prediction

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Table 1. Specification of NREL phase VI wind turbine. Number of blades

Z

2

Rotor diameter

D

10.058 m

Rotational speed

N

71.9 rpm

Cut-in wind speed

Vc

6 m/s

Rated power

19.8 kW

Power regulation

stall

Rotational direction

CCW

Global pitch angle Fig. 1. Real model of NREL Phase VI.

Tower height

5° H

12.192 m

and the evaluation of the low frequency noise caused by wind turbine will be needed. The purpose of this study is to numerically predict aerodynamic noise generated from a HWAT of NREL Phase VI according to the variation of wind speeds using commercial CFD code, FLUENT. The flow field around NREL Phase VI and the noise characteristics for frequencies below 500Hz were simulated using LES and FW-H analogy. The near-field noise around the wind turbine generator including the tower, nacelle and blade was directly analyzed using LES and the far-field noise was calculated at the specific locations away from the wind turbine using FW-H analogy.

2. Computational methodologies 2.1 Specification of NREL phase VI wind turbine NREL successfully completed an experimental test for a Phase VI wind turbine in a wind tunnel (24.4 m x 36.6 m) at NASA Ames Research Center in May 2000. After the test, NREL revealed the experimental test results and shape information of the test wind turbine blade on a website in order to verify analysis performance of the commercial codes developed in the world. Therefore, the present study adopts the shape of wind turbine blade of Phase VI as an analysis target for CFD simulation because the NREL Phase VI blade shape can be accurately embodied using the released blade data information, and reliable test results for the turbine can be easily obtained. A real model of Phase VI wind turbine as shown in Fig. 1 is controlled by stall-regulated method, and produces a rated output power of 19.8 kW. The turbine blade diameter, rotational speed and blade number are D=10.058 m, N=71 rpm and Z=2, respectively. Detailed specifications of the turbine model are shown in Table 1. The blade shape of the Phase VI wind turbine is comprised of airfoil S809 from root to tip. The airfoil S809 has 21% thickness of chord length, and is designed to have less sensitivity to the surface roughness at the leading edge of the wind turbine blade in order to improve the turbine output power [4]. The computational domain for the wind turbine generator is illustrated in Fig. 2. Two block grid is used. Since the position of wind turbine blades changes according to time, the total domain is chosen to consist of two regions, the interior region

Fig. 2. Computational domain.

including the wind turbine blades and external region except for the sphere. In the computational domain, a cylindrical cross-section with an area less than the actual tunnel crosssection is used, corresponding to a radius of 15.087m. The aerodynamic analysis of this research does not need a large calculation region because it is a method to calculate aerodynamic noise at the specific position using FW-H analogy with noise sources, not a method to predict noise generation and propagation, leading directly to far-field sound. By the reference length of blade diameter D, spatial resolutions of 2.5 times the length to calculations domain inlet, 3.5 times the length to the downstream region and 3.5 times the length to radial direction of the wind turbine model are applied to the calculation domain. Total cell numbers of the numerical grids are about Ng=5 × 106 and the numerical grids are composed of two kinds of grid shape, hexahedral and tetrahedral grids. In Fluent solver, near-wall treatment for LES is as follows. When the mesh is fine enough to resolve the laminar sublayer, the

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Table 2. Analysis conditions. Wind speed(Vin), m/s

RPM

ρ , kg/m3

Case1

7

71.9

1.225

Case2

10

71.9

1.225

Case3

13

71.9

1.225

Case4

15.1

71.9

1.225

Case5

25.1

71.9

1.225

wall shear stress is obtained from the laminar stress-strain relationship. If the mesh is too coarse to resolve the laminar sublayer, it is assumed that the centroid of the wall-adjacent cell falls within the fully turbulent layer, and law of the wall is employed [3]. In this study, the average value of y + and first height from the wall of the blade is, respectively, about 0.8 and 0.05 mm at the rated wind speed. As boundary conditions, a velocity condition with 3% of turbulent intensity is applied at the upstream boundary of the cylindrical domain where the flow comes into the domain, and ambient pressure condition at the downstream of the cylindrical domain where the flow leaves. Five kinds of inflow velocity in the range of Vin = 7 m/s ~ 25.1 m/s are adopted for the calculation of the wind turbine generator. Analysis conditions are summarized in Table 2. 2.2 Large eddy simulations Turbulent flows are characterized by eddies with a wide range of length and time scales. The largest eddies are typically comparable in size to the characteristic length of the mean flow. The smallest scales are responsible for the dissipation of turbulence kinetic energy. It is possible, in theory, to directly resolve the whole spectrum of turbulent scales by using an approach known as direct numerical simulation (DNS). No modeling is required in DNS. However, DNS is not feasible for practical engineering problems involving high Reynolds number flows. The cost required for DNS to resolve the entire range of scales is proportional to Ret, where Ret is the turbulent Reynolds number. Clearly, for high Reynolds numbers, the cost becomes prohibitive. LES can be considered as an intermediate between DNS and RANS (Reynolds-averaged Navier-Stokes equations). In an LES approach, it is recognized that the large turbulent structures are generally much more energetic than the small scale ones and their size and strength make them by far the most effective transporters of the conserved properties. The small scales are normally much weaker, and provide little transport of these properties. These large structures are resolved to ensure accuracy, while scales smaller than the size of the computational mesh are modeled. Since these small sub-grid scales tend to be more homogeneous and isotropic than the large structures, they can be reasonably represented by large eddy simulation [5]. The filtered continuum and Navier-Stokes equations are defined as the following [6]:

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∂ρ ∂ + ( ρ ui ) = 0, ∂t ∂xi

(1)

∂ ∂ ∂ ∂ p ∂τ i , j − ( ρ ui ) + ( ρ ui u j ) = (σ i , j ) − ∂t ∂x j ∂x j ∂xi ∂x j

(2)

where σ i , j is the stress tensor due to molecular viscosity defined by ⎡ ⎛ ∂u ∂u j ⎞ ⎤ 2 ∂u i ⎟⎥ − µ l δ i, j + ⎢⎣ ⎜⎝ ∂x j ∂xi ⎟⎠ ⎥⎦ 3 ∂xl

σ i, j ≡ ⎢µ ⎜

(3)

and τ i , j is the subgrid-scale stress defined by τ i , j ≡ ρ ui u j − ρ u i u j .

(4)

The subgrid-scale stresses resulting from the filtering operation are unknown, and require modeling. The subgrid-scale turbulence models employ the Boussinesq hypothesis [7] as in the RANS models, computing subgrid-scale turbulent stresses from 1 3

τ i , j − τ k , k δ i , j = −2 µ t S i , j

(5)

where µt is the subgrid-scale turbulent viscosity. The isotropic part of the subgrid-scale stresses τ k , k is not modelled, but added to the filtered static pressure term. Si , j is the rate of strain tensor for the resolved scale defined by 1 ⎛ ∂u ∂u j ⎞ ⎟. Si , j ≡ ⎜ i + 2 ⎜⎝ ∂x j ∂xi ⎟⎠

This simple model was first proposed by Ref. [8]. In the Smagorinsky-Lilly model, the eddy-viscosity is modelled by

µt = ρ L2s S

(6)

where Ls is the mixing length for subgrid scales and, Ls is computed using S ≡ 2Si , j Si , j , Ls = min(κ d , CsV 1/ 3 )

(7)

where κ is the von Karman constant, d is the distance to the closest wall, Cs is the Smagorinsky constant, and V is the volume of the computational cell. In this study, the Smagorinsky constant was used as the value of 0.1, which is known to yield the best results for a wide range of flows. 2.3 Acoustic analogy methods FW-H equation has been widely used for the successful prediction of helicopter rotors, propellers and fans [9]. The FW-H equation is the most general form of the Lighthill

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Fig. 3. Definition of aerodynamic noise sources.

acoustic analogy and can be used to predict the noise generated by complex arbitrary motions. This is relevant to the present research of rotating wind turbine blades. The FW-H equation is based on an analytical formula which relates the farfield pressure to integrals over a closed surface that surrounds all or most of the acoustic sources. The FW-H equation is an exact rearrangement of the continuity and the momentum equations into the form of an inhomogeneous wave equation with two surface source terms (monopole and dipole) and a volume source term (quadrupole) as expressed in the form of Eq. (8). First term on the right side is a quadrupole source caused by unsteady shear stresses, the second term is a dipole source by unsteady external forces, and third term is a monopole caused by unsteady mass injection.

Fig. 4. Measurement location of aerodynamic noise.

∂2 1 ∂ 2 p′ 2 ′ − ∇ = p {Ti, j H ( f )} ∂xi ∂x j a02 ∂t 2



∂ ⎡ Pi , j n j + ρ ui (un − vn ) ⎤⎦ δ ( f ) ∂xi ⎣

+

∂ {[ ρ0vn + ρ (un − vn )]δ ( f )}. ∂t

{

}

Fig. 5. Comparison of mechanical powers between CFD and experimental data.

(8)

P′ is the sound pressure at the far field. f = 0 denotes a mathematical surface introduced to “embed” the exterior flow problem (f > 0) in an unbounded space, which facilitates the use of generalized function theory and the free-space Green function to obtain the solution. The surface (f = 0) corresponds to the source (emission) surface, and can be coincident with a body (impermeable) surface or a permeable surface off the body surface. nj is the unit normal vector pointing toward the exterior region (f > 0), a0 is the far-field sound speed, and Ti,j is the Lighthill stress tensor, ui is fluid velocity component in the xi direction, un is fluid velocity component normal to the surface f=0, vi is surface velocity component in the xi direction, vn is surface velocity component normal to the surface, is the Dirac delta function, H(f) is Heaviside function, Pi,j is the compressive stress tensor. In this study, the noise sources generated from a HAWT of NREL Phase VI are classified into three sources: the blade (dipole+quadrupole), blade (dipole) and tower (dipole). As shown in Fig. 3 the blade (dipole+quadrupole) means the noise sources adding a quadrupole around the blades to a di-

pole by the blade surface, and the blade(dipole) and lower(dipole) represent noise source by only pressure fluctuation of the surfaces at the blade and tower, respectively. Except for this quadrupole source around blades, the other quadrupole sources are not considered due to a little weak effect to the acoustic receiver. 2.4 Measurement location of radiated aerodynamic noise Generally, the noise of a wind power generator is evaluated according to the variation of wind speeds with the IEC 6140011 international standard after the wind power generator is set up. KS standard in Korea also has been established in the same contents of the IEC 614000-11 international standard. Therefore, in the present CFD calculation, the observation location of aerodynamic noise caused by the analysis model of wind power generator is determined at the reference distance R, which is the sum of the turbine tower height H from the earth's surface to the turbine blade center and the turbine blade radius D/2 according to the IEC 61400-11 international standard. The measurement location of aerodynamic noise caused by the wind power generator using the top and front views is shown in Fig. 4.

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3. Results and discussion A HAWT of NREL Phase VI for an analysis model applied in this research has only released the test results of aerodynamic performance according to the variation of wind speeds. But, at that time no aerodynamic noise test was performed. Therefore, experimental data for verification to compare the results of aerodynamic noise analysis do not exist in the present analysis. But, the aerodynamic noise generated from some objects on the airflow is possible to predict to some extent: in the case of aerodynamic performance results such as power and torque within allowable error compared with experimental data because the radiation pattern of the aerodynamic noise is determined by the pressure fluctuation resulting from the separated flow around body through a medium. Fig. 5 shows the comparison of the power outputs between the measured time-averaged data and the time history of calculated data for wind speed of 7 m/s. The periodic and stable mechanical power oscillation is generated with the amplitude of 0.1 kW at the reference of averaged output with 6.06 kW. Also, these results show difference of power outputs by 0.8% compared with experimental data of 6.02 kW. Generally, mechanical output is converted to electrical output through the power train and generator, and mechanical output always has higher value than electrical output if system loss is considered. In the present analysis, the numerical results corresponding to mechanical output represent a little higher than the timeaveraged results corresponding to electrical output. The tip-vortices in the blade tip region are shown in Fig. 6 according to the variation of computational time. As a method of various mathematical expressions representing vortex core, we employed second-invariant of deformation tensor as the following Eq. (9): 1 Q = (Ω 2 − S 2 ) 2

Time : 2.84(s)

Time : 2.92(s)

Time : 3(s)

(9)

where Ω and S represent rate of rotation tensor and strain rate. When the wind turbine blades rotate with time, tipvortices occur at the tip of two blades and are generated periodically in a circle. Very complex three-dimensional vertical flow structures associated with the tip vortices can be identified. These vortices in the vicinity of the blade tip cause intense aerodynamic noise due to the tip vortex-trailing edge interaction by local cross flows along the trailing edge [3]. It is known that the blade tip shape has a strong influence on the generation of the tip vortex. As previously mentioned, sources of aerodynamic noise around the wind turbine in the present analysis are defined into three parts: blade (dipole + quadrupole), blade (dipole) and tower (dipole). After LES calculations, information of the pressure field and turbulence such kinetic and dissipative energy around the wind turbine was known. The calculations were performed by FW-H analogy using the above-mentioned information from sources to the location (P1). Figs. 7-9 illustrate the pressure fluctuations for the variation of wind speeds

Time : 3.04(s) Fig. 6. deformation-invariant contour according to variation of time for 7 m/s of wind speed.

taken at a point P1 between 0.1 s and 1.5 s. In Fig. 7, the acoustic pressure by the tower (dipole) is oscillated with relatively small amplitude compared with the two other sources. But, the acoustic pressures by the blade (dipole + quadrupole) and blade (dipole) vary relatively greatly in the range of 0.03 Pa and show a similar tendency. These results mean that the quadrupole around the blade has little influence on the acoustic pressure at a low wind speed of 7m/s. As wind speeds

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Fig. 7. Comparison of acoustic pressures for wind speed of 7 m/s.

Fig. 8. Comparison of acoustic pressures for wind speed of 15.1 m/s.

Fig. 10. Comparison of A-weighted sound pressures level for wind speed of 7 m/s.

Fig. 11. Comparison of A-weighted sound pressure levels for wind speed of 15.1 m/s.

Fig. 9. Comparison of acoustic pressures for wind speed of 25 m/s.

Fig. 12. Comparison of A-weighted sound pressures levels for wind speed of 25 m/s.

increase as shown in Figs. 8 and 9, these figures show many peaks in the result of the blade (quad. + dipole) source in comparison to one of the blade (dipole) source between 0.1 and 1.5(s). In the condition of high wind speeds, the energy coming to P1 location is more amplified because of the combination of the dipole source by unsteady external forces and quadrupole source by unsteady shear stresses. As a result, the amplitude of acoustic pressure by the blade (quad. + dipole) source remarkably becomes larger than one by the blade (di-

pole) source. In other words, there is a very close relation between the strength of quadrupole and increase of wind speed. No experimental data of pressure fluctuations is currently available for comparison. However, it has been confirmed in the comparison of aerodynamic performance that the present numerical method is robust and provides accurate results for pressure fluctuations. Figs. 10-12 represent A-weighted sound pressure levels(SPLs) using Figs. 7-9 data by an FFT analysis. SPLs are

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Table 3. Comparison of sound intensity ratio of quadrupole to dipole at P1 location.

expressed by ⎛ p ⎞ Lp = 20log ⎜ ⎟ dB ⎝ pre ⎠

(10)

where Pre is the reference pressure of 20 x 10-6 Pa and P is the root-mean square(rms) sound pressure(Pa). The pure SPLs were corrected by A-weighted curve, which is a correction method that is the most suitable to sensitivity of the human ear. The sample data during 2.0 s, which corresponds to approximately over 2.5 rotations of wind turbine blades, was into 730 data, meaning a frequency resolution of 0.687 Hz. Because of the characteristics of A-weighted curve that large correction is applied to the low frequency bandwidth, relatively low SPLs is shown in the frequency range below 100 Hz as shown in Fig. 10. Quadrupole noise by the turbulence disturbance and dissipation is relatively small among the noise sources in the whole frequency band except between 400 Hz and 500 Hz. In the frequency bandwidth below 400 Hz, the SPLs for both the blade (dipole + quadrupole) and blade (dipole) show almost similar trend. However, in the frequency band over 300 Hz in Figs. 11 and 12, the SPLs show apparent difference. It is judged that the difference results from the influence by the dipole source plus quadrupole source by the blade in the frequency range over 300 Hz. It becomes more apparent according to increase of wind speeds, and marked tonal noises are observed in the whole frequency region between 300 and 500Hz. However, we cannot exactly know where these discrete frequency noises between 300 and 500Hz come from because it is impossible to find the specific location of noise source on or around the blade as present CFD technique. In Figs. 8 and 9, there are many peaks, which are periodic with the time interval of 0.1(s) for 15.1 m/s and 0.7(s) for 25.1 m/s with the unaided eye. These time intervals correspond to 10 Hz and 1.43 Hz, respectively. However, it is not easy exactly to confirm the periodicity and SPL with the unaided eye. So FFT analysis method using acoustic pressure data has been widely used to date. Through FFT analysis, SPL and frequency corresponding to these time intervals is approximately 60.5 dB at 12.4 Hz for 15.1 m/s, 58.7 dB at 2.75 Hz for 25.1m/s. This information is not confirmed in Figs. 11 and 12 due to the characteristics of A-weighted correction, whose method is the most suitable one for sensitivity of the human ear. Fig. 13 represents a comparison of no-weighted and Aweighted overall sound pressure level(OSPLs) between blade (dipole) and blade (quadrupole) directly to investigate effects of the turbulent stresses with various wind speeds at P1 location. OSPL means the sum of the sound pressure levels in the whole frequency region. The intervals of OSPLs between the blade (quadrupole) and the blade (dipole) become more and more narrow with the increase of wind speed. OSPLs by blade (quadrupole) have larger slope than ones by blade (dipole). This means that there is a considerably close relation between the quadrupole noise by small and large scales and the in-

Wind speed (m/s)

No-weighted

A-weighted

Iquad./Idip.

Iquad./Idip.

7

21.1%

8.5%

10

30.2%

21.6%

13

36.3%

30.9%

15.1

38.0%

25.7%

25.1

54.3%

25.4%

Fig. 13. Comparison of no-weighted and A-weighted OSPLs between blade(dipole) and blade(quadrupole) at P1 location.

crease of wind speeds. And the results of OSPLs by Aweighted correction are much lower than ones by no-weighted correction due to the characteristics of A-weighted correction. A little singular result of the blade (dipole, A-weighted) in the wind speed of 7 m/s is observed to have a little higher value than two cases of 10 m/s and 13 m/s. It is judged that the frequency range is restricted below 500 Hz because of the limits of computational time and cost. Overall sound pressure level can be expressed as sound intensity meaning sound power per unit area as shown in Table 3. In the case of no-weighted correction the sound intensity ratio of quadrupole to dipole at P1 location is about 21.1% at a wind speed of 7 m/s and linearly increases up to 54.3% at a wind speed of 25.1 m/s. But, in the case of A-weighted correction, as wind speeds increase, the sound intensity ratio linearly does not increase. That is because the A-weighting curve has been differently corrected in the total frequency region according to variation of wind speeds. Namely, the distribution of the sound pressure level differently and irregularly exists at a narrow frequency region in the various forms. Table 4 shows a comparison of sound power levels of CFD with predicted models. Sound power level means the acoustic power radiated by a given source with respect to the international reference of 10−12 W. Previous researchers, Lowson, Haw and Hagg et al, suggested a simple model shown in Eqs. (11)-(13) for rough prediction of sound power level[3]. They require only simple input parameters, such as

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Table 4. Comparison of sound power levels of CFD with predicted models.

Sound Power Level (dB(A))

CFD

Lowson

Hau

Hagg

87.8

93.0

94.1

84.9

Fig. 14. Comparison of A-weighted SPL and theory equation according to distance from center of hub.

rotor diameter, power, and wind speed. CFD result shows a good agreement with one by Hagg. However, the results of the other two models are highly estimated in comparison with CFD result. Lowson eq.

L WA = 10log10 PWT + 50,

(11)

Hau eq.

L WA = 22log10 D + 72,

(12)

Hagg eq.

L WA = 50log10 Vtip +10log10 D − 4,

(13)

L P = L WA -10log10 (2πR 2 ) - αR .

(14)

With the purpose of rough prediction of sound pressure level according to variation of distance, a simple model is often used of Eq. (14) suggested by the International Energy Agency and based on the hemispherical noise propagation over a reflective surface, including air absorption. Here, absorption coefficient, α =0.005 dB(A) per meter, R is distance from center of hub of wind turbine. Using the result of a simple model suggested by Hagg of these three models, this value is applied to the Eq. (14). In Fig. 14, the results of FW-H model by CFD show a good tendency with those of theory equation even though there is a little gap in the quantitative side due to assumption of point source in case of theory result. At the nearfield within 20 m from the center of the hub, the sound pressure level is, respectively, reduced by average values of 4.5 and 6.04 dB(A) per doubling of distance in the cases of FW-H and

theory results. At the far-field over 20 m, respectively, reduced by averaged values of 5.7 and 6.33 dB(A).

4. Conclusions (1) For a wind speed of 7 m/s, a periodic and stable mechanical power oscillation was generated with the amplitude of 0.1 kW at the reference of averaged output power of 6.06 kW, and the results of aerodynamic performance showed a good agreement with the experimental with an error of 0.8%. (2) Very complex three-dimensional vertical vortex structures associated with the tip vortices were identified. These vortices in the vicinity of the blade tip are known to cause intense aerodynamic noise due to the tip vortex-trailing edge interaction by local cross flows along the trailing edge. (3) As wind speeds increased, marked tonal noises were observed in the whole frequency region between 300 and 500Hz. There was a very close relation between strength of quadrupole source and increase of wind speed. (4) Sound intensity ratio of quadrupole to dipole at P1 location was about 21.1% at wind speed of 7m/s, but increased up to 54.3% at a wind speed of 25.1 m/s in the case of noweighted correction. (5) The calculated result of sound power level at the P1 location was compared with simple models of previous researchers, and showed a good agreement with the result suggested by Hagg of three other models.

Acknowledgment This work is the outcome of a Manpower Development Program for Marine Energy by the Ministry of Land, Transport and Maritime Affairs(MLTM).

Nomenclature-----------------------------------------------------------------------D H Lp L WT

Ng N PWT

Q R Vc Vtip Z

: : : : : : : : : : : :

Blade diameter Tower height Sound pressure level Sound power level Grid number Rotational speed Rated power Second-invariant of deformation tensor Radius of blade Cut-in wind speed Rotational speed of rotor blade tip Number of blades

References [1] C. Arakawa, O. Fleig, M. Iida and M. Shimooka, Numerical approach for noise reduction of wind turbine blade tip with earth simulator, Journal of the Earth Simulator, March

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(2005) 2, 11-33. [2] T. Burton, D. Sharpe, N. Jenkins and E. Bossanyi, Wind energy handbook, John Wiley & Sons Ltd. (2001) 531-553. [3] S. Wangner, R. Bareis and G. Guidati, Wind turbine noise, Springer-Verlag, Berlin (1996). [4] D. Simms, S. Schreck, M. Hand, L. J. Fingersh, NREL/TP500-29494 (2001). [5] A. Leonard, Energy cascade in large-eddy simulations of turbulent fluid flows, Advances in Geophysics (1974) 18A, 237-248. [6] ANSYS FLUENT 12.0 Theory Guide (2010) 171-188. [7] J. O. Hinze, Turbulence, McGraw-Hill Publishing Co., New York (1975). [8] J. Smagorinsky, General circulation experiments with the primitive equations. I. The Basic Experiment, Monthly Weather Review, 91 (3) (1963) 99-164. [9] J. E. Ffowcs Williams and D. L. Hawkings, Sound generation by turbulence and surfaces in arbitrary motion, Phil. Trans. of the Royal Soc. of London, A: Mathematical and Physical Science, 264 (1151) (1969) 321-342.

Jang-Oh Mo is currently a Research Engineer at Center for Ocean Energy Research and Education in Korea Maritime University. He received his B.S, M.S and Ph.D. in Mechanical Engineering from the Korea Maritime University in 2001, 2003 and 2009, Korea. He worked as a CFD consulting engineer from 2004 to 2009 in ATES. His research interests include design and aerodynamic noise of wind turbine blade and software development for on and off-shore wind turbine blade design.

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Young-Ho Lee received his B.E. and M.E. degrees from Korea Maritime University, Korea. He received his Ph.D. in Engineering from the University of Tokyo, Japan. Dr. Lee is currently a Professor at the Division of Mechanical and Information Engineering, Korea Maritime University. His research interests include ocean energy, wind energy, small hydro power, fluid machinery, PIV, and CFD.