Otimização multiobjetivo de aerofólios não convencionais para aplicações em baixos números de Reynolds

Abstract

With the emergence of Micro Air Vehicle (MAVs) and the growing interest in aerial vehicles for Mars exploration, the search for efficient aerodynamic profiles for these applications has intensified. These applications operate in a range of Reynolds numbers (104 < Re < 105) significantly lower than those commonly found in conventional low Reynolds regimes, such as commercial drones. This study highlights the pronounced aerodynamic challenges in this low Reynolds number range, such as Kelvin-Helmholtz instability and Laminar Separation Bubble (LSB). The main objective of this research is to identify more efficient shapes for airfoils by optimizing them through a multi-objective process to maximize the lift coefficient and minimize the drag coefficient. To achieve this goal, two unconventional airfoil models were optimized using Generalized Differential Evolution 3 (GDE3), a differential evolution algorithm. The obtention of aerodynamic coefficients, crucial for evaluating the performance of the evolutionary algorithm, was carried out through simulations using Computational Fluid Dynamics (CFD). The method applied to describe the aerodynamic behavior of the structures proved consistent with experimental data. Finally, the evolutionary algorithm resulted in aerodynamic profiles that exhibited interesting characteristics for these applications.