Helicopter Blade-Vortex Interaction Airload and Noise Prediction Using Coupling CFD/VWM Method
AbstractAs a high resolution airload with accurate rotor wake is pivotal for rotor BVI (Blade-vortex interaction) analysis, a hybrid method with combined Navier-Stokes equation, viscous wake model, and FW-H (Ffowcs Williams-Hawkings) equation is developed for BVI airload and noise in this paper. A comparison with the CFD (Computational Fluid Dynamics)/FW-H method for the AH-1/OLS (Operational Load Survey) rotor demonstrates its capability for favorable accuracy and high computation efficiency. This paper further discusses the mechanisms for the impacts of four flight parameters (i.e., tip-path-plane angle, thrust coefficient, tip Mach number, advance ratio) on BVI noise. Under the BVI condition, several BVI events concurrently occur on the rotor disk. Each interaction has a distinct radiation direction which depends on the interaction azimuth, and its noise intensity is highly associated with the characteristic parameters (e.g., miss-distance, interaction angle, vortex strength). The BVI noise is dominated by the interactions at 30–90° in azimuth on the advancing side, of which the wake angle range is from 180° to 540°. Furthermore, the tip-path-plane angle, thrust coefficient, and tip Mach number change the noise intensity mainly via miss-distance, interaction angle, and vortex strength, but for different advance ratios, the noise intensity and propagation direction are more dependent on the interaction angle and interaction azimuth. View Full-Text
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Zhao, Y.; Shi, Y.; Xu, G. Helicopter Blade-Vortex Interaction Airload and Noise Prediction Using Coupling CFD/VWM Method. Appl. Sci. 2017, 7, 381.
Zhao Y, Shi Y, Xu G. Helicopter Blade-Vortex Interaction Airload and Noise Prediction Using Coupling CFD/VWM Method. Applied Sciences. 2017; 7(4):381.Chicago/Turabian Style
Zhao, Yinyu; Shi, Yongjie; Xu, Guohua. 2017. "Helicopter Blade-Vortex Interaction Airload and Noise Prediction Using Coupling CFD/VWM Method." Appl. Sci. 7, no. 4: 381.
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