Aerodynamic Analysis and Optimization of Gliding Locust Wing Using Nash Genetic Algorithm

Fuente: Zenodo
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Isakhani, Hamid, Yue, Shigang, Xiong, Caihua, Chen, Wenbin
Format: Recurso digital
Langue:anglais
Publié: Zenodo 2025
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866902239390466048
author Isakhani, Hamid
Yue, Shigang
Xiong, Caihua
Chen, Wenbin
author_facet Isakhani, Hamid
Yue, Shigang
Xiong, Caihua
Chen, Wenbin
contents <p>Natural fliers glide and minimize wing articulation to conserve energy for endured and long-range flights. Elucidating the underlying physiology of such a capability could potentially address numerous challenging problems in flight engineering. This study investigates the aerodynamic characteristics of an insect species called desert locust (<em>Schistocerca gregaria</em>) with extraordinary gliding skills at low Reynolds numbers. Here, locust tandem wings are subjected to a computational fluid dynamics (CFD) simulation using two-dimensional and three-dimensional (3-D) Navier–Stokes equations, revealing fore–hindwing interactions and the influence of their corrugations on aerodynamic performance. Furthermore, the obtained CFD results are mathematically parameterized using the PARSEC method and optimized based on a novel fusion of genetic algorithms and Nash game theory to achieve Nash equilibrium. It was concluded that the lift–drag (gliding) ratio of the optimized profiles were improved by at least 77% and 150% compared to the original wing and the published literature, respectively. Ultimately, the profiles are integrated and analyzed using 3-D CFD simulations that demonstrated a 14% performance improvement, validating the proposed wing models for further fabrication and rapid prototyping presented in a future study.</p>
format Recurso digital
id zenodo_https___doi_org_10_2514_1_J060298
institution Zenodo
language eng
publishDate 2025
publisher Zenodo
record_format zenodo
spellingShingle Aerodynamic Analysis and Optimization of Gliding Locust Wing Using Nash Genetic Algorithm
Isakhani, Hamid
Yue, Shigang
Xiong, Caihua
Chen, Wenbin
gliding wings, locust, aerodynamic analysis, optimisation, Nash genetic algorithm
<p>Natural fliers glide and minimize wing articulation to conserve energy for endured and long-range flights. Elucidating the underlying physiology of such a capability could potentially address numerous challenging problems in flight engineering. This study investigates the aerodynamic characteristics of an insect species called desert locust (<em>Schistocerca gregaria</em>) with extraordinary gliding skills at low Reynolds numbers. Here, locust tandem wings are subjected to a computational fluid dynamics (CFD) simulation using two-dimensional and three-dimensional (3-D) Navier–Stokes equations, revealing fore–hindwing interactions and the influence of their corrugations on aerodynamic performance. Furthermore, the obtained CFD results are mathematically parameterized using the PARSEC method and optimized based on a novel fusion of genetic algorithms and Nash game theory to achieve Nash equilibrium. It was concluded that the lift–drag (gliding) ratio of the optimized profiles were improved by at least 77% and 150% compared to the original wing and the published literature, respectively. Ultimately, the profiles are integrated and analyzed using 3-D CFD simulations that demonstrated a 14% performance improvement, validating the proposed wing models for further fabrication and rapid prototyping presented in a future study.</p>
title Aerodynamic Analysis and Optimization of Gliding Locust Wing Using Nash Genetic Algorithm
topic gliding wings, locust, aerodynamic analysis, optimisation, Nash genetic algorithm
url https://doi.org/10.2514/1.J060298