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遗传算法在水平轴洋流机叶片优化设计中的应用
引用本文:余万,李春,杨阳.遗传算法在水平轴洋流机叶片优化设计中的应用[J].能源研究与信息,2018,34(1):5-10,15.
作者姓名:余万  李春  杨阳
作者单位:上海理工大学能源与动力工程学院/上海市动力工程多相流动与传热重点实验室
基金项目:国家自然科学基金资助项目(E51176129);上海市教育委员会科研创新(重点)项目(13ZZ120、13YZ066);教育部高等学校博士学科点专项科研基金(博导类)资助项目(20123120110008);上海市研究生创新基金资助项目(JWCXSL1402)
摘    要:水平轴洋流机是捕获洋流能的主要设备,其叶片外形直接影响捕能效率。通过Bezier参数化曲线描述定速定桨距洋流机的叶片弦长和扭角分布规律,采用叶素-动量理论计算其水动特性。以额定流速下能量利用系数系数最大为目标,基于遗传算法建立了叶片外形优化模型。同时,为了避免因汽蚀导致功率输出不稳定的现象,在优化过程中以汽蚀作为约束条件,与经典设计方法Wilson理论设计叶片进行了比较。结果表明:优化叶片在叶根处的扭角更小,具有更佳的抗扭性能;叶根和叶尖处弦长均更小,节省了材料;在设计流速范围内,优化叶片在低流速下效率更高,平均提高了4.6%,具有更好的启动性能。

关 键 词:洋流机  叶片  汽蚀  遗传算法  优化
收稿时间:2015/9/8 0:00:00

Application of Genetic Algorithm to the Optimization Design of Horizontal Axis Tidal Turbine Blade
YU Wan,LI Chun and YANG Yang.Application of Genetic Algorithm to the Optimization Design of Horizontal Axis Tidal Turbine Blade[J].Energy Research and Information,2018,34(1):5-10,15.
Authors:YU Wan  LI Chun and YANG Yang
Affiliation:School of Energy and Power Engineering/Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China,School of Energy and Power Engineering/Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China and School of Energy and Power Engineering/Shanghai Key Laboratory of Multiphase Flow and Heat Transfer in Power Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
Abstract:Horizontal axis tidal turbine is the key equipment to capture energy of the current.The blade shape can directly affect the capture efficiency.In this paper,the distribution of chord length and twist angle for tidal turbine blade with fixed speed and pitch was described by Bezier parametric curves.Blade-element momentum theory was applied to calculate its hydraulic dynamic characteristics.With the goal of maximizing the power coefficient at the constant flow velocity,the optimization model of blade shape was built based on genetic algorithm.Meanwhile,in order to avoid the instability of power output caused by cavitation,the cavitation resistance was used as constraints in the optimization model.Compared with the classical Wilson theory of blade design,the results showed that the torsional angle has reduced in the hub of the optimized blade and the better torsion properties was achieved.The root and tip chord length of the blade decreased,which could save materials.Within the range of designed flow rate,higher efficiency was achieved for the optimized blade under low flow rate.The efficiency increased by 4.6% on average.The better startup performance was achieved as well.
Keywords:tidal turbine  blade  cavitation  genetic algorithm  optimization
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