Navigating Aerodynamic Trade-Offs: Multi-Objective Optimization of Helicopter Rotor Blade Using an Evolutionary Algorithm
Muhammad Muneeb Safdar, Apurva Anand, Koushik Marepally, James D. Baeder · 2025
Rotor blade optimization is a key challenge in rotorcraft aerodynamics, requiring the design of blades that maximize efficiency, measured by the Figure of Merit (FM) for hovering rotors and the Lift-to-Drag ratio (L/D) for forward flight. Traditional optimization methods, such as adjoint-based CFD, are computationally expensive and often impractical during the early design stages. This study investigates an efficient approach to a rotor blade optimization problem, using the University of Maryland Advanced Rotorcraft Code (UMARC2) for aerodynamic analyses combined with a Genetic Algorithm (GA) for optimization. The optimization process is demonstrated on a compound helicopter configuration with lift-offset, which involves different thrust trim requirements and aerodynamic conditions in hover and forward flight. The optimization starts with a baseline Hart-II blade and produces optimized blade geometries suited to both flight conditions. The selection of airfoils along the blade span is a key focus of this study and is included in the design space. The results demonstrate that a suitable combination of airfoils for the inboard and outboard regions can significantly enhance both FM in hover and L/D in forward flight. The overall optimization approach shows the potential to achieve significant aerodynamic improvements in rotor designs while balancing computational efficiency and accuracy.