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Uncertainty Quantifi cation and Polynomial Chaos Expansion It is increasingly being felt among the aeroelastic community that aeroelastic analysis should include the effect of parametric uncertainties. This can potentially revolutionize the present design concepts with higher rated performance and can also reshape the certifi cation criteria. Nonlinear dynamical systems are known to be sensitive to physical uncertainties, since they often amplify the random variability with time. Hence, quantifying the effect of system uncertainties on the aeroelastic stability boundary is crucial. Flutter, a dynamic aeroelastic instability involves a Hopf bifurcation where a damped (stable response) oscillation changes to a periodic oscillatory response at a critical wind velocity. In a linear system the post fl utter response can grow in an unbounded fashion [22]. System parametric uncertainties can signifi cantly affect the onset and properties of bifurcation points. The importance of stochastic modeling of these uncertainties is that they quantify the effect of the uncertainties on fl utter and bifurcation in a probabilistic sense and gives the response statistics in a systematic manner. The original homogeneous polynomial chaos expansion [4] is based on the homogeneous chaos theory of Wiener [6,25]. This is based on a spectral representation of the uncertainty in terms of orthogonal polynomials. In its original form, it employs Hermite polynomials as basis from the generalized Askey scheme and Gaussian random variables. Spectral polynomial chaos-based approaches with other basis functions have also been used in the recent past in various unsteady fl ow and fl ow-structure interaction problems of practical interest [8,26,27].