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Data-Driven Forecasting of Postflutter Responses of Geometrically Nonlinear Wings

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Ensuring adequate flutter margins is a critical step in aircraft design. However, in the presence of nonlinear effects, subcritical limit-cycle oscillations can arise even before flutter occurs. When nonlinear effects are anticipated, postflutter analyses have to be integrated into aircraft design in addition to flutter computations for preventing this undesirable subcritical behavior. Therefore, there is a need for computationally fast postflutter analysis methods suitable for design applications. This paper investigates a data-driven method to forecast the bifurcation behavior of a geometrically nonlinear wing, demonstrating its suitability to analyze realistic nonlinear aeroelastic systems. The method efficiently forecasts postflutter responses using only a few system transient computations in the preflutter regime. First, the accuracy of forecasted bifurcation diagrams is verified against time-marching results. Next, wing design parameters are varied to investigate their impact on postflutter responses and show the method suitability to parametric studies.