Multi-output autoregressive aeroelastic system identification and flutter prediction

The paper presents a methodology for reduced-order modeling of aeroelastic systems identification and flutter prediction. The aeroelastic system is modeled as a Multi-Output Autoregressive process and the model parameters are identified based on aeroelastic responses simulated in a CFD code. The aeroelastic system is identified at a few sub-critical (pre-flutter) dynamic pressure values. Flutter onset is determined from stability parameters that which are computed for the two dominant aeroelastic modes. The methodology is demonstrated on three test cases - a linear 2D airfoil, transonic 2D flutter with reference to wind tunnel test, and a generic transport aircraft model. The paper compares the Multi-Output Autoregressive to Single-Output Autoregressive model and shows that the former is more straightforward to implement, robust, and requires shorter identification data. Overall the methodology is simple to implement as it only requires an aeroelastic simulation capability and basic processing. It is computationally efficient and therefore suitable for CFD-based flutter prediction.