风力机翼型尾缘厚度对粗糙敏感性影响的研究

黄宸武, 汪涛平

太阳能学报 ›› 2022, Vol. 43 ›› Issue (2) : 486-491.

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (2) : 486-491. DOI: 10.19912/j.0254-0096.tynxb.2020-0482

风力机翼型尾缘厚度对粗糙敏感性影响的研究

  • 黄宸武, 汪涛平
作者信息 +

STUDY ON ROUGHNESS SENSITIVITY OF WIND TURBINE AIRFOILS AFFECTED BY TRAILING-EDGE THICKNESS

  • Huang Chenwu, Wang Taoping
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文章历史 +

摘要

综合应用涡面元和RANS方法,研究DU93-W-210、DU91-W2-250及DU97-W-300这3种常用翼型经尾缘修型后尾缘厚度对粗糙敏感性的影响。在涡面元方法中采用设置固定转捩和在RANS方法中采用设置锯齿形边界条件的方式来模拟翼型前缘污染,研究发现前缘污染造成翼型吸力峰降低,引起翼型气动性能下降,然而随着尾缘厚度的适量增加,翼型最大升阻比及设计升力系数即气动性能的下降率呈减小趋势,表明适当增加尾缘厚度可有效降低风力机叶片粗糙敏感性。

Abstract

The surface roughness of wind turbine blade caused by pollution, especially the surface roughness of leading edge, is an important factor of power loss. In this paper, the effect of trailing edge thickness on roughness sensitivity of DU93-W-210, DU91-W2-250 and DU97-W-300 airfoils after trailing edge modification is studied by using vortex panel method and RANS method. To simulate the leading edge contamination of airfoil, the fixed transition is set in the vortex panel method. And the serrated boundary condition is set in RANS method. It is found that the leading edge pollution causes the decrease of the suction peak, and induces the reduction of the airfoil aerodynamic performance. However, with the appropriate increase of the trailing edge thickness, the decline rates of the maximum lift drag ratio and the design lift coefficient (i.e. aerodynamic performance) show a decreasing trend. It indicates that the roughness sensitivity of wind turbine blade can be effectively reduced by increasing the trailing edge thickness.

关键词

风力机 / 叶片 / 流动模拟 / 粗糙敏感性 / 尾缘厚度

Key words

wind turbines / blade / flow simulation / roughness sensitivity / trailing-edge thickness

引用本文

导出引用
黄宸武, 汪涛平. 风力机翼型尾缘厚度对粗糙敏感性影响的研究[J]. 太阳能学报. 2022, 43(2): 486-491 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0482
Huang Chenwu, Wang Taoping. STUDY ON ROUGHNESS SENSITIVITY OF WIND TURBINE AIRFOILS AFFECTED BY TRAILING-EDGE THICKNESS[J]. Acta Energiae Solaris Sinica. 2022, 43(2): 486-491 https://doi.org/10.19912/j.0254-0096.tynxb.2020-0482
中图分类号: TK83   

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基金

国家自然科学基金(51366013)

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