48 11 48(11):125~131 2018 11 PERIODICAL OF OCEAN UNIVERSITY OF CHINA Nov.2018
121121211
(1. 266100;2. 266100)
: NACA4418 MATLAB CFD(Computational Fluid Dynamic) Fluent NACA4418 : ;;;
: T K 7 3 0 : A : 1 6 7 2 -5 1 7 4 (2 0 1 8 )1 1 -1 2 5 -0 7 DOI: 10.16441/j.cnki.hdxb.20160162
: .[J]. ( )201848(11):125-131. YUAN PengWANG Xu-ChaoWANG Shu-Jieet al.Study on optimization of hydrofoil of tidal turbine blade based on ge-
[] ():
netic algorithm J .Periodical of Ocean University of China 2018 4811 125-131.
[1]
Goundar HF-SxFx63137 NACA63815 [9];Bahaj [10];Gras so RFOIL [11];Mol land
(NASA) NACA NACA44
NACA63-2 NACA64-4
1980 XFOIL[12]
NREL-S
[2] (Delft university of tech-
nology) DU [3] RIS
RIS [4]
(F F A ) F F A W [5 ]
CAS-W [6] N P U -W A [7 ] C Q U -A [8]
XFOIL [1 3 ] ; R B F NSGA-II [14]; CFD Fluent NACA [1 5 ]
:(2015GSF115019);(51279191) Supported by the Key Research and Development Project of Shandong Province(2015GSF115019);the National Science Foundation of China(51279191)
:2016-06-22; :2017-05-21
: (1975-) E-mail:[email protected]
126
2 0 1 8
NACA4418 [16] NACA4418
1
1.1
: (1) ; (2) ; [17] (3) 20%; 40 % [18 ]
1.2
: (1) ; (2) ;
(3)
2
[19]
NACA4418 1
1 Fig.1 Flow chart of the hydrofoil design
3
11 : 127
3.1 : Vy =Usin= (1-a)V (6)
aa
a a [21 ] :
[20 ] : = f (x ) = z + e 2 / z
1a(1-a)2 () a=a=2=2 7
(1 ) z
3 9 :r
e1/4 :
e2
x = (l + l )cos
= r (8 )
V
:
e2(2) y=(l- )sin
l :l:
d L = 1 c U 2C L d r 2
l=eexp(()) (3) Taylor ():
( 9 ) ( 1 0 )
dL/dD (9)(10) :
dL=CL (11) dD CD
:CL ;CD (11)
(CL/CD ) :
f(X)= max(CL/CD ) (12)
3 .3
(4)()6:
X = (x 1 x 2 x 3 x 4 x 5 x 6 ) (1 3 ) 3 .4
NACA4418 18 % :
t/c=18% (14) :t ;c
NACA4418 30% :
Lmax =0.30 (15)
:
|S-S0|5% (16) S0
:S ;S0
d D = 1 c U 2C D d r 2
()=m1(1-cos)+n1sin+m2(1-cos)2 + n2sin2+L+mk(1-cos)k +nksink+L
k = 123L (4)
(4 ) = 0 ( ) = 0 mknk
3 .2
CP CP
r 2 V U c
2 Fig.2 Blade element velocity and load diagram
U Vx Vy :
Vx =Ucos=(1+a)r (5)
[22]
128
2 0 1 8
:
Le 3% (17)
[23 ] :
y u 1 y l 1 0 .0 1 (1 8 )
:y u 1 x = 1 y ;y l 1 x = 1y
:
4%w/c6% (19) :w ;c
:
4 5 % L w 5 0 % (2 0 ) 3 .5
[24] 3
3 Fig.3 Flow chart of the hydrofoil optimization and design
4
4.1
NACA4418
MATLAB 4
4 Fig.4 Comparison diagram of the initial hydrofoil and optimized hydrofoil
4.2
C F D N -S
XFOIL en
CFD Fluent
CFD Fluent
Gambit C 5
Fluent 1.5 m/s xy -5~ 25 Standard k- [25]
Standard k-
11
: 129
5NACA4418 Fig.5 The whole grid diagram and the grid partial enlargement diagram of NACA4418hydrofoil
15.351 3 10.489 2 46.35%
7NACA4418 Fig.7 Lift-to-drag ratio comparison diagram of NACA4418and the optimized hydrofoil
5
CFD Fluent
:
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4 .3
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CA4418 6 7
6NACA4418 Fig.6 Lift coeficient comparison diagram of NACA4418and the optimized hydrofoil
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7
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11 : 131
Study on Optimization of Hydrofoil of Tidal Turbine Blade Based on Genetic Algorithm
1 2 1 1 2 1 2 1 1 YUAN Peng WANG Xu-Chao WANG Shu-Jie TAN Jun-Zhe SI Xian-CaiBIAN Bing-Bing
(1.Colege of EngineringOcean University of ChinaQingdao 266100China;2.The Key Lab of Ocean Enginering of Shandong ProvinceQingdao 266100China)
Abstract: Hydrofoil profiles of the blades largely determine the performance of the tidal turbine.To get a tidal turbine hydrofoil with higher performanceoptimization was made on a prototype hydrofoil of NACA4418based on analysis of design method and design requirement of tidal turbine.A parameterized model was built with the method of Joukowski conformal transformation and optimization design was made by using the genetic algorithm with the software MATLABin which the global optimal solution was found in that the maximum lift-to-drag ratio as the objective function under seting design variables and constrains.CFD simulation of flow fields around hydrofoil of NACA4418and the one optimized were respectively conducted by using software FLUENT.Comparison of results shows that the lift coef-
ficient and the lift-to-drag ratio were largely raised by optimization. Key words: tidal curent turbine;blade hydrofoil;optimization design;genetic algorithm
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