Investigation on the Multi-Objective Optimization of Supercritical Airfoil Based on Nondominated Sorting Genetic Algorithm

Abstract:

This paper aimed to investigate the multi-objective optimization method of supercritical airfoil. To achieve the optimal design of supercritical airfoil Rae2822, an improved NSGA-2 (Nondominated Sorting Genetic Algorithm) method was utilized, while the cross-operator and adaptive-variation operator were introduced to improve the convergence speed of the algorithm. During the optimization, the airfoil parametric modeling was achieved based on the Bezier-Bernstein method, and the objective function was obtained through solving the N-S equations. Considering the parallel computation characteristics of the algorithm, the computation was conducted in large-scale Linux computer system to reduce the solving time. Optimization results showed that the undominate solution with high quality obtained through the NSGA-2 method distributed evenly, which provided the designer a wider choosing space. It was also showed that the multi-objective optimization method presented in this paper was feasible and reliable.

• Periodical: Applied Mechanics and Materials (Volumes 444-445)
• Pages: 357-362
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.444-445.357
• Online since: October 2013
• Authors: Da Wei Liu, Xin Peng, Xin Xu, De Hua Chen
• Keywords: Adaptive-Variation, Cross-Operator, Multi-Objective Optimization (MOP), N-S Equations, NSGA-2

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