Multi-Objective Optimization of Helicopter Airfoils Using Surrogate-Assisted Memetic Algorithms

摘要

An effective strategy for airfoil numerical optimizations is presented that deals with multi-objective and multipoint problems and is specifically designed for helicopter applications. This technique is tested on several realistic problems of airfoil optimization with the aim of improving their aerodynamic performance by searching for optimal shape. The procedure is based on a multi-objective surrogate-assisted memetic algorithm coupled to a Navier-Stokes solver. First, the peculiar features of the algorithm are described with particular attention to its advantages when compared with more traditional evolutionary or gradient-based algorithms. Finally, the results of the optimizations carried out using different operating conditions are presented; starting from the optimal Pareto fronts, several solutions are selected and compared in terms of shapes and performance.