Variable-Fidelity Methodology for the Aerodynamic Optimization of Helicopter Rotors

Abstract

The design of helicopter rotor blades is a challenging task. On the one hand, there are the demanding simulations, which are a multidisciplinary endeavor. On the other hand, tools for parametric studies or optimizations require many simulations, making the design process even more costly. In the rotorcraft community, two routes for the numerical optimization task are observed. The first route is based upon local gradient search algorithms, which exploit low-fidelity tools or adjoint-based computational fluid dynamics (CFD) simulations. The second route is surrogate-based optimization in combination with high-fidelity CFD simulations. These surrogate-based optimizations can be further accelerated, when knowledge from low-fidelity models is used. This paper presents a framework that is developed for the multi-objective aerodynamic optimization of helicopter rotor blades including surrogate models based on different fidelities. The individual components necessary for performing a variable-fidelity, multi-objective optimization are reviewed before being applied. A novel technique to deal with unsuccessful simulations referred to as a failure map is additionally presented. The gain of the variable-fidelity optimizations in contrast to the single-fidelity optimizations is quantified, and a reduction in computational resources of up to 69% is observed. The failure map requires 78% less resources in contrast to the classical failure handling.