Genetic Algorithm Optimization of Lift Distribution in Subsonic Low-Range Designs
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Rubén Ferrero-Guillén [1] ; Rubén Álvarez [1] ; Javier Díez-González [1] ; Álvaro Sánchez-Fernández [1] ; Hilde Pérez [1]
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[1] Universidad de León
Universidad de León
León, España
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- Localización: 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020 / coord. por Álvaro Herrero Cosío, Carlos Cambra Baseca, Daniel Urda Muñoz, Javier Sedano Franco, Héctor Quintián Pardo, Emilio Santiago Corchado Rodríguez, 2021, ISBN 978-3-030-57802-2, págs. 520-529
- Idioma: inglés
- Texto completo no disponible (Saber más ...)
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Resumen
The optimization of the lift distribution is an essential análisis in the wing design segment of every aircraft project. Although it has been demonstrated that the optimal solution follows an elliptic distribution, there is no known relation between the parameters that define this distribution and its similarity to the elliptical one. Therefore, there is no direct approach for obtaining an exact solution, existing methodologies such as CFD simulations which require of a considerable amount of time and resources to offer accurate results. The methodology followed throughout this paper involves the application of metaheuristic techniques, such as genetic algorithms, in order to optimize the lift distribution obtained through the Prandtl lifting-line theory. Results show that the genetic algorithm proposed is able to obtain a satisfactory solution within a reasonable time.
