摘要
围绕翼型的转捩问题,以NACA0012、NACA0015、NACA0018三种不同厚度的对称翼型为研究对象,基于TSST湍流模型的数值模拟方法,提出基于湍流强度的转捩判断方法并研究在5种大雷诺数条件下翼型表面流动的转捩规律,以期为风力机叶片设计提供新的参考思路。研究表明,基于湍流强度的转捩判断方法是有效、可行的,使用翼型表面湍流强度曲线的阶跃现象观测转捩,可有效避免转捩前流动扰动带来的影响。同时利用湍流强度的变化情况可为风力机叶片设计寻找最佳设计参数。研究发现,增大攻角和雷诺数使得翼型上翼面转捩位置前移、下翼面转捩位置后移。此外,随着攻角的减小、雷诺数的增大、翼型表面厚度的增加,在翼型转捩前的流动逐渐稳定。
In this paper,three symmetric airfoils with different thicknesses,NACA0012,NACA0015 and NACA0018,are used to study the transition problems of airfoils.The numerical simulation method based on the TSST turbulence model,the turbulence intensitybased turning judgment method and the study of the turning law of the airfoil surface flow under five large Reynolds number conditions are presented,and new reference ideas for wind turbine blade design are provided.The investigation shows that the transition judgment method based on turbulence intensity is practical and feasible.The effect of pre-transition flow disturbance can be effectively avoided by observing the transition using the step phenomenon of turbulence intensity profile on the airfoil surface.Moreover,the variation of turbulence intensity can be used to find the optimal design parameters for wind turbine blade design.It is found that the increase of the attack angle and Reynolds number cause the transition position of the upper airfoil surface to shift forward and the lower airfoil surface to move backward.In addition,the flow before the airfoil transition gradually stabilizes as the angle of attack decreases,the Reynolds number increases,and the airfoil surface thickness increases.
作者
杨从新
张根豪
李寿图
郭艳磊
岳念西
刘文杰
Yang Congxin;Zhang Genhao;Li Shoutu;Guo Yanlei;Yue Nianxi;Liu Wenjie(School of Energy and Power Engineering,Lanzhou University of Technology,Lanzhou 730050,China;Gansu Provincial Technology Centre for Wind Turbines,Lanzhou 730050,China;DEC Electrical Machinery Co.,LTD.,Deyang 618000,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2024年第1期326-333,共8页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(12062012)。
关键词
转捩
风力机
计算流体力学
γ-Reθ转捩模型
雷诺数
湍流强度
transition flow
wind turbines
computational fluid dynamic
γ-Reθtransition model
Reynolds number
turbulence intensity