Summary
This study introduces a probabilistic approach to assess the stability of aeroelastic limit cycle oscillations. Utilising the Hill/Koopman method, data-driven models are trained to capture eigenvalue behaviour. The stability likelihood of the limit cycle oscillations is evaluated by analysing the percentage of stable responses in Monte Carlo experiments. The effectiveness of the method is demonstrated using a nonlinear aerofoil test case, revealing that it provides accurate stability information compared to experimental data. Ongoing efforts will focus on conducting a more thorough analysis of the method, considering both accuracy and computational efficiency.
