Effective Analysis of Nonlinear Aeroelasticity Based on Parameter Adaptive Reduced Order Model

A parameter adaptive reduced order model was developed to calculate the aerodynamics of aircraft structures and to be applied to the transonic flutter boundary prediction. To get the mode information adapted to the flow condition variation, an interpolation based on Grassmann manifold was employed. For the calculation of the mode coefficients during the variation of the flow condition, a local linear neuro-fuzzy model was similarly employed with adding an extra input of the varying parameter. Based on this, the calculation of aerodynamic for a 3D LANN wing was arranged to validate the developed method and then to be applied in transonic flutter boundary prediction successfully. The results show that the computational efficient of the present reduced order can increase 3 times, compared with the time domain analysis method, and its calculation speed can improve 3.5 times, while the parameter adaptive reduced order model can increase 10 times when investigating of a multi flow conditions aeroelastic problem.