A Bioinspired Airfoil Optimization Technique Using Nash Genetic Algorithm

Isakhani, Hamid, Xiong, Caihua, Yue, Shigang and Chen, Wenbin (2020) A Bioinspired Airfoil Optimization Technique Using Nash Genetic Algorithm. In: 2020 17th International Conference on Ubiquitous Robots (UR), 22-26 June 2020, Kyoto, Japan.

Full content URL: https://doi.org/10.1109/UR49135.2020.9144868

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive

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.

Keywords:Automotive components, Aerodynamics, Genetic algorithms, Optimization, Insects, Two dimensional displays, Nash equilibrium
Subjects:H Engineering > H141 Fluid Mechanics
G Mathematical and Computer Sciences > G140 Numerical Analysis
H Engineering > H440 Aerodynamics
H Engineering > H130 Computer-Aided Engineering
H Engineering > H410 Aeronautical Engineering
Divisions:College of Science > School of Computer Science
ID Code:43819
Deposited On:19 Feb 2021 12:39

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