An Efficient Methodology for Using a Multi-Objective Evolutionary Algorithm for Winglet Design

Abstract

Winglets are designed for the Janus B sailplane through the coupling of an aircraft design code that uses a high-order potential-flow solver with single-objective and multi-objective evolutionary algorithm optimization methods. The use of the single- objective optimizer, Covariance Matrix Adaptation Evolutionary Strategy (CMA-ES), serves as a stepping stone to employing a multi-objective optimizer, the epsilon-dominance Multi-Objective Evolutionary Algorithm (e -MOEA). The multi-objective evolutionary algorithm proves to be successful in designing several winglets with favorable changes in performance. For example, one winglet generated in a two-objective study was able to achieve a 0.1% cruise drag reduction and a 4.5% thermal drag reduction; this results in a peak cross-country speed improvement of 5.5% during weak weather conditions with maximum thermal core strengths of 2 m/s and 0.6% during strong weather conditions with maximum core strengths of 8 m/s. While the design methodology is far from being fully matured, it provides a solid foundation for future research.