Multi-Output Autoregressive Aeroelastic System Identification and Flutter Prediction

Matan Argaman
Work towards MSc degree under the supervision of Assoc. Prof. Daniella Raveh
Department of Aerospace Engineering
Technion – Israel Institute of Technology

Flutter analysis in the production environment is typically based on linear models, where the structure is modeled via a finite-element model, and the aerodynamics via a linear panel code. The main deficiency of linear panel codes is their inability to estimate the unsteady aerodynamic forces accurately, and consequently the flutter onset, in the transonic regime. Computational Fluid Dynamics (CFD) codes can accurately predict the flow field about complex, realistic configurations in all flight regimes, but a direct transient-response simulation is computationally expensive and therefore not a valid tool for flutter prediction.

The current study presents CFD-based flutter prediction methodology via reduced-order modeling of the aeroelastic system. 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 then determined from stability parameters that 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 wind tunnel test data, and a generic transport aircraft model.

The talk will be given in Hebrew

Mon, 16-04-2018, 16:30 (Gathering at 16:00)

Classroom 165, ground floor, Library, Aerospace Eng.

Light refreshments will be served before the lecture

Multi-Output Autoregressive Aeroelastic System Identification and Flutter Prediction