Multi-objective optimal design of airfoil based on multi-island genetic algorithm

截面	NACA	r/mm	c/r	c/mm	(t/c)/%	t/mm	β/(°)
1	63858	60	0.483 3	29.00	58.00	16.87	23.00
2	63825	120	0.558 3	67.00	25.00	16.75	19.00
3	63823	180	0.369 8	66.56	22.80	15.51	12.35
4	63822	240	0.261 3	62.72	21.90	13.73	9.96
5	63820	300	0.197 7	59.30	20.05	12.07	8.91
6	63819	360	0.155 3	55.92	18.80	10.51	8.00
7	63817	420	0.126 1	52.98	17.15	9.14	7.03
8	63816	480	0.107 2	51.44	16.10	8.08	6.21
9	63815	540	0.092 3	49.82	15.10	7.05	5.74
10	63813	600	0.073 3	44.00	12.80	5.54	5.50

Table 2. Optimization parameters

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Table 2. Optimization parameters

参数	权重	优化条件
$ C\mathrm{_l}\boldsymbol{/}C_{\rm{d}} $	0.20	$ C_{\mathrm{l}}\boldsymbol{/}C_{\rm{d}} > \left(C_{\mathrm{l}}\boldsymbol{/}C_{\rm{d}}\right)_0 $
$ {C_{\rm{d}}} $	0.20	$ {C_{\rm{d}}} \leqslant {C_{\rm{d0}}} $
$ {T_{\rm{m}}} $	0.30	$ \left[ {{T_{\rm{m}}} - {T_{{m0}}}} \right] \leqslant 0.001 $
$ {R_{\rm{LE}}}/c $	0.15	$ {R_{\rm{LE}}}/c \leqslant 0.02 $
$ \beta $	0.15	$ \beta \leqslant {\beta _0} = 11.25^\circ $

Table 3. Control parameters of multi-island genetic algorithm
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Table 3. Control parameters of multi-island genetic algorithm
参数名数值
子种群规模 7
子种群岛数量 8
进化代数 50
杂交概率 0.96
变异概率 0.02
迁移率 0.02
迁移间隔 6

Table 4. Number of turbine grids

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Table 4. Number of turbine grids

网格等级	优化前网格数量	优化后网格数量	优化前推力/N	优化后推力/N	实际推力/N
1	160×10⁴	161×10⁴	342.5	351.5	350.0
2	244×10⁴	245×10⁴	348.1	368.7
3	338×10⁴	341×10⁴	356.3	380.8
4	451×10⁴	456×10⁴	356.8	380.5

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Zhiyang ZHANG, Xu LIU, Linyan WU, Shaohua CHEN, Weixing LIU, Lin CUI. Multi-objective optimal design of airfoil based on multi-island genetic algorithm[J]. Chinese Journal of Ship Research, 2024, 19(4): 148

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