A stochastic analysis of the limit cycle behavior of a nonlinear aeroelastic model using the response surface method
An efficient method is presented for quantifying the effect of parametric uncertainty on the response of a nonlinear aeroelastic system. The proposed stochastic model uses a response surface method to map the random input parameters of the system to the specified system output (in this instance root-mean square wing tip response). In order to handle the bifurcation in the response surface due to aeroelastic self-excited instability, the response surface model is fit using a two-region regression. The results from this model are compared to those from a full Monte Carlo simulation for both a one-dimensional random input parameter model(thickness) and a two-dimensional random input parameter model(thickness and modulus of elasticity). The response surface method results compare favorably with the full model results while achieving a two to three order of magnitude gain in computational efficiency.
