Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
A methodology of airfoil and wing optimization using genetic algorithms
Submission Author:
Giovana Weffort Fernandes , SP
Co-Authors:
Giovana Weffort Fernandes, Manuel Barcelos Júnior
Presenter: Giovana Weffort Fernandes
doi://10.26678/ABCM.COBEM2023.COB2023-0204
Abstract
The present paper aims to present a methodology of optimization of airfoils and wings through genetic algorithms. The plan was to develop accessible and in-depth algorithms which may be configured and adapted according to the user's preference. The optimization algorithms allow for the configuration of the objective functions and constraints in terms of four distinct aerodynamic coefficients (lift coefficient, drag coefficient, L/D ratio and pitch moment coefficient), in various possible combinations, and they employ the CST as the airfoil parametrization method. The main version of the codes was written in GNU Octave, using XFOIL as the flow solver in the airfoil algorithm, and using APAME as the solver in the wing algorithm. The genetic algorithm is evaluated via standard test functions, and case studies are defined aiming to optimize specific geometries in given flight conditions established by a Reynolds number and an angle of attack. The results were successful within the stipulated objectives and allow for discussion of the behavior of the optimization process, and how the modified geometries compare to their original versions. In conclusion, the main advantages of this methodology are its reliability and ease of adaptations. Every element of the optimization process may be changed to suit the needs of the user, which include the object of study, the geometric parametrizations, the objective functions, constraints, the optimization algorithm itself, and other aspects. A basic demonstration of this is given at the end of the paper, where a given result from the Python version of the wing optimization algorithm, using VSPAERO as the solver, is shown.
Keywords
airfoils, Wings, Genetic Algorithms, cst
