Dynamic Stall Alleviation of a Helicopter Blade Section in Forward Flight Condition Using an Optimized Combination of Active Nose Droop and Active Gurney Flap

This study investigates the potential of an optimized combination of active nose droop and active Gurney flap (CADAG) in a new flow control strategy to manage dynamic stall over a pitching blade section under variable Mach number flow. The optimization method employs the genetic algorithm coupled with a computational fluid dynamic (CFD) solver and artificial neural network. The base blade section belongs to a section positioned at $\mathrm{r}/\mathrm{R}=0.865$ of the rotor blade of the UH-60A helicopter in forward flight condition. A high relative angle of attack on the retreating side makes the flow susceptible to dynamic stall. A nose droop is employed to control the dynamic stall of the blade section, and a Gurney flap is used to maintain the balance of the generated lift of the blade during 360° of rotation. A comprehensive investigation is performed to determine the most significant parameters affecting the performance of the present combined active flow control. The ratio of the total generated lift to the drag is chosen as the objective function of the optimization. Results show that this ratio and the total generated lift in one rotation cycle increase by 193% and 13%, respectively, at the optimum condition of the present combined active flow control, while the ratio of the generated lift over the advancing side to the retreating side is equal to that of the base blade section. In addition, the dynamic stall hysteresis loop reduces significantly, and the maximum value of the drag coefficient and the negative aerodynamic damping decrease up to 87% and 83% compared to the base blade section, respectively. In general, the proposed innovative combined active flow control is an adjustable method to alleviate dynamic stall and improve the aerodynamic performance of rotary wings in different operation conditions.

The rotary blades are extensively used in rotorcraft, turbo engines, and wind turbines. Despite their massive use, they suffer from some essential issues, of which the most important one is the so-called dynamic stall. Dynamic stall is a complex phenomenon that limits the performance of the rotary blades. Due to the physics governing a rotary wing, such as a helicopter rotor blade, dynamic stall and flow separation are very common. Understanding dynamic stall physics and providing solutions to prevent it is still one of the main challenges of aerodynamic scientists. The present study introduces a novel adjustable method for practically alleviating the dynamic stall on helicopter blade section in forward flight conditions to improve its aerodynamic performance in different operational conditions. A comprehensive investigation is carried out to determine the key parameters affecting the proposed method. These findings can serve as a valuable tool for other researchers to develop various active flow control strategies. This article applies an optimization process using artificial neural networks, genetic algorithms, and CFD tools, which forms a comprehensive framework that can be easily extended to other applications.