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

Abstract

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 (Schistocerca gregaria) 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.