Multi-fidelity concurrent aerodynamic optimization of rotor blades in hover and forward flight

Abstract

Complementary multi-objective strategies adapted to the aerodynamic optimization of helicopter rotor blades in hover and in forward flight are developed. A first competitive strategy is based on Nash Games from game theory, where the objective functions are minimized by virtual players involved in a non-cooperative game. A method is presented to split the design vector into two sub-spaces, defined to be the strategies of the players in charge of the minimization of the primary and the secondary objective functions respectively. This split of territory allows the optimization of the secondary function while causing the least possible degradation of the first one. Alternatively, a cooperative approach based on a generalization of the steepest-descent method to multiple objectives is presented. These methodologies are applied to the optimization of the twist distribution of the model rotor ERATO, with the aim to maximize the Figure of Merit in hover while minimizing the rotor torque coefficient in forward flight. The optimizations are performed in a framework based on high-fidelity evaluations. A multi-fidelity model is proposed and tested, creating a bridge function between the low and high fidelity models. The results demonstrate the potential of these techniques to obtain rotor designs realizing interesting trade-offs.