A Bioinspired Airfoil Optimization Technique Using Nash Genetic Algorithm

Hamid Isakhani, C. Xiong, Shigang Yue, Wenbin Chen
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引用次数: 3

Abstract

Natural fliers glide and minimize wing articulation to conserve energy for endured and long range flights. Elucidating the underlying physiology of such capability could potentially address numerous challenging problems in flight engineering. However, primitive nature of the bioinspired research impedes such achievements, hence to bypass these limitations, this study introduces a bioinspired non-cooperative multiple objective optimization methodology based on a novel fusion of PARSEC, Nash strategy, and genetic algorithms to achieve insect-level aerodynamic efficiencies. The proposed technique is validated on a conventional airfoil as well as the wing crosssection of a desert locust (Schistocerca gregaria) at low Reynolds number, and we have recorded a 77% improvement in its gliding ratio.
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基于纳什遗传算法的仿生翼型优化技术
天生的飞行者滑翔,并尽量减少机翼关节,以保存能量,为持久和远程飞行。阐明这种能力的潜在生理学可能潜在地解决飞行工程中许多具有挑战性的问题。然而,生物启发研究的原始性质阻碍了这些成就,因此,为了绕过这些限制,本研究引入了一种基于PARSEC、纳什策略和遗传算法的生物启发非合作多目标优化方法,以实现昆虫级的空气动力学效率。所提出的技术在传统翼型以及低雷诺数的沙漠蝗虫(Schistocerca gregaria)的机翼横截面上进行了验证,我们记录了其滑翔比提高77%。
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