Probabilistic turbulence modeling and uncertain gust buffeting

Literature on turbulence modeling is rich in empirical, semi-empirical and theoretical spectral equations whose parameters assume deterministic values. Starting from a critical review of the state of the art, a unitary model of the 3-D atmospheric turbulence was proposed where all parameters are defined by first and second order statistical moments derived from a wide selection of experimental measurements. Preliminary analyses based on Monte Carlo simulations of the model parameters show that the propagation of turbulence uncertainties over the gust-excited response of structures gives rise to a relevant scatter. The passage from Monte Carlo simulations to Taylor series expansions provides systematic rules to deal with the gust buffeting problem in a full probabilistic environment.