An application of HODMD to predict flutter using NeoCASS

Abstract

We present a method based on higher order dynamic mode decomposition (HODMD) to predict aeroelas-tic modes in signals representing fluid-structure interactions. For such aim, some data are generated using an open source solver called NeoCASS (Next generation Conceptual Aero-Structural Sizing Suite), which reproduces real flight test conditions. Symmetric and anti-symmetric aeroelastic modes have been excited in two different numerical experiments. The HODMD-based method is able to detect the frequencies, damping rates and modal shapes of the leading aeroelastic modes with high accuracy. The good performance of this method provides a new and efficient tool, which can be extended to predict flutter in flight test in real time.