Bioinspired genetic-algorithm optimized ground-effect wing design: flight performance benefits and aircraft stability effects

This paper presents a bioinspired, genetic-algorithm evolutionary process for Ground-Effect vehicle wing design. The study made use of a rapid aerodynamic model generation and results evaluation computational fluid dynamics vortex lattice method software, supervised by a genetic algorithm optimization Python script. The design space for the aircraft wing parametric features drew inspiration from seabirds, under the assumption of their wings being naturally evolved and partially optimized for proximity flight over water surfaces. A case study was based on the A-90 Orlyonok Russian Ekranoplan, where alternative bioinspired wing variations were proposed. The study objective was to investigate the possible increased flight aircraft performance when using bioinspired wings, as well as verify the static and dynamic aircraft stability compliance for Ground-Effect flight. The methodology presented herein along with the study results, provided an incremental step towards advancing Ground-Effect aircraft conceptual designs using computational fluid dynamics.