A multi-level data-driven Bayesian approach to identify probabilistic stability of aeroelastic limit cycle oscillations

Yuan, Jie and McGurk, Michael (2024) A multi-level data-driven Bayesian approach to identify probabilistic stability of aeroelastic limit cycle oscillations. 11th European Nonlinear Oscillations Conference, , Delft, Netherlands. 17 - 22 Jul 2024. 2 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

This study introduces a probabilistic approach to assess the stability of aeroelastic limit cycle oscillations. This study introduces a multi-level data driven approach to identify the probablistic stability of aeroelastic limit cycle oscillations through limit experimental data. 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 based on parameter estimates obtained through the multilevel data-driven approach. The effectiveness of the method is demonstrated using a nonlinear aerofoil test case, revealing that it provides accurate stability information compared to experimental data.

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