Stochastic Analysis of a Nonlinear Aeroelastic Model Using the Response Surface Method

Abstract

An efficient method is presented for quantifying the effect of parametric uncertainty on the response of a nonlinear aeroelastic system. The proposal 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). 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 2 to 3 order of magnitude gain in computational efficiency.

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