Aeroelastic-Informed Multi-Objective Optimization Of Helicopter Rotor Blades

Abstract

Rotor blade optimization plays a critical role in improving helicopter performance. This study aims to enhance two key metrics: the Figure of Merit (FM) in hover and the Lift-to-Drag ratio (L/D) in forward flight. Traditional high-fidelity methods are accurate but computationally expensive, making them less practical in early-stage design. To address this, we use low-fidelity aerodynamic and structural tools with global optimization methods to efficiently explore the design space. Building on previous work with rigid blade assumptions, this study includes aeroelastic effects to better capture the blade's dynamic behavior. The optimization uses the University of Maryland's Aeromechanical Rotorcraft Analysis Code (UMARC-II) and Genetic Algorithms, allowing for non-linear twist and chord distributions along with spanwise airfoil selection. Two optimization approaches were investigated: with and without airfoil selection parameters. Results show that combining airfoil selection with twist and chord optimization provides the most significant performance gains. Aeroelastic analysis confirms that the optimized blades are structurally feasible, with acceptable modal behavior and deflections in both hover and forward flight.