Otimização multiobjetivo de perfis aerodinâmicos utilizando algoritmo genético

Abstract

In aviation, a search for more efficient aircraft has grown in the face of concerns from governments and the environment, forcing new aircraft designs to emit less and less CO2 into the atmosphere. All aerodynamic designs have a vital part in common, which is the airfoil. In this work, you can find an optimal airfoil, with a multi-objective approach through a genetic algorithm in Matlab®, which uses XFOIL to obtain aerodynamic characteristics of users. In order to obtain a good diversification of the population, 300 airfoils were made available on the aerofoil data site. For XFOIL, the International Standard Atmosphere was adopted, number of refined from 5.00 to 5, number of males from 0.05, Ncrit from 9, maximum number of iterations from 100 and an attack control range from 0º to 18º. For the genetic algorithm, a probability of crossing of 90%, 5% for mutation was adopted. The optimum airfoils performed better than other optimization jobs, where they had improvements in the order of 32% of 𝑐௟ for flying wings, 67% of 𝑐௟ for empennage and better efficiencies of around 70% for wind turbines. The algorithm also used, airfoils with softer stall characteristics for wings and noise reduction for wind turbines. For future work, it is suggested to research a larger number of Reynolds, and other aerodynamic solvers, in addition to implementing an optimization by the inverse method, using an ideal pressure distribution.