Multiobjective-Multipoint Rotor Blade Optimization in Forward Flight Conditions Using Surrogate-Assisted Memetic Algorithms

摘要

A multi-objective and multi-point optimization framework for helicopter rotor performance is presented. This framework is based on a multi-objective surrogate-assisted memetic algorithm which is coupled with two aerodynamic solvers for rotor performance prediction: a lifting-line comprehensive tool and a more advanced three-dimensional panel method coupled with a constant vorticity contour free-wake vortex model. The purpose is to improve aerodynamic performance of helicopter main rotors in multipoint forward flight operations by searching for optimal blade shape. The optimization procedure and the memetic algorithm are first described. Afterwards, they are applied to optimization of several features of a blade, like twist, chord and sweep and the outcomes from those optimizations are discussed from an aerodynamic viewpoint. The advantages of the proposed optimization procedure are finally illustrated and compared to more traditional techniques.