Design of trailing edge flap based on MFC and prediction of deformation and aerodynamic performance using BP neural network

Abstract

In terms of vibration and noise reduction for helicopter, Active Control Flap (ACF) rotor technology, leveraging smart materials, stands out as a promising and advantageous approach. This paper focuses on the design, modeling, and simulation of a novel structure integrated with trailing-edge flap and composite rotor blade driven by Macro Fiber Composite (MFC) actuators. A 3D model is employed to simulate the deformation response of the flap under different driving voltage levels. The results were validated by experimental data. Additionally, Fluid-Structure Interaction (FSI) analysis is applied to explore the deflections of the trailing-edge flap under various flight conditions and its corresponding aerodynamic characteristics. The findings reveal that the designed trailing-edge flap significantly influences the aerodynamic lift and pitch moment of the airfoil at operational speed and angle of attack of the helicopter blade. Finally, a Back Propagation (BP) Neural Network is introduced to establish a fast predictive model for the intricate nonlinear response characteristics of the ACF rotor. The network is trained and tested with appropriately chosen sample data, demonstrating high prediction accuracy and reliability. This model serves as a theoretical reference for subsequent application of ACF technology in vibration and noise reduction, providing valuable insights for further research and development.