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An aerodynamic optimization design study on the bio-inspired airfoil with leading-edge tubercles
Engineering Applications of Computational Fluid Mechanics ( IF 6.1 ) Pub Date : 2021-01-28 , DOI: 10.1080/19942060.2020.1856723
Yu Lu 1 , Ziying Li 1 , Xin Chang 1 , Zhenju Chuang 1 , Junhua Xing 2
Affiliation  

The aim of the paper is to propose a groundbreaking method for the aerodynamic optimization design of the bioinspired wing with leading-edge tubercles. An emphasis on the optimization design of the spanwise waviness in the leading edge for delaying stall and increasing lift from the aerodynamic performance perspective has been laid in this study. For the conversion of the wavy configuration, the form parameterized approach using F-spline curves has been used to produce more variants of the leading-edge tubercles. Numerical investigations of flow characteristics which are performed using CFD computations have been used to validate the numerical scheme with experimental data. The combination of Non-dominated Sorting Genetic Algorithm II and Response Surface Method based Kriging Model has been adopted as the aerodynamic optimization strategy. As consequence, the three main components of the optimization process are incorporated into the establishment of the aerodynamic optimization design system for the bio-inspired airfoil with leading-edge tubercles. The four optimal airfoils respectively which increases the stall angle as well as the lift have been obtained in contrast to the smooth wing. The optimized bio-inspired design of this kind can be applied to flow-controlled devices for improving the efficiency of a particular operating mechanism.



中文翻译:

尖端结节的生物启发翼型的气动优化设计研究

本文的目的是提出一种突破性的方法,用于具有前缘结节的生物启发机翼的空气动力学优化设计。从空气动力学性能的角度出发,重点放在前翼翼展波纹度的优化设计上,以延迟失速和增加升力。对于波形配置的转换,已使用使用F样条曲线的形式参数化方法来生成前沿结节的更多变体。使用CFD计算进行的流动特性数值研究已用于验证具有实验数据的数值方案。采用了非支配排序遗传算法II和基于响应面法的克里格模型相结合的气动优化策略。结果,优化过程的三个主要组成部分被并入了针对具有前缘结节的生物启发型翼型的空气动力学优化设计系统的建立。与光滑机翼相比,已经获得了分别增加失速角和升力的四个最佳翼型。这种经过优化的具有生物启发性的设计可以应用于流量控制设备,以提高特定操​​作机构的效率。

更新日期:2021-01-28
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