SIMULATING ATMOSPHERIC-TURBULENCE BY SYNTHETIC REALIZATION OF TIME-SERIES IN RELATION TO POWER SPECTRA

A novel and-direct procedure is presented for the realization of atmos pheric turbulence by an appropriately estimated autoregressive model. Straightforward identification of the model parameters is based upon t he Yule-Walker equation, which expresses the autocorrelation in terms of the model parameters. These are adjusted as part of a hill climbing process until a given target autocorrelation is achieved. The target function is obtained directly through Fourier transformation of the sp ectral density function representing the desired atmospheric turbulenc e characteristics. For this study the Kaimal spectrum for turbulence i n the lower boundary layer has been adopted. Validation of the procedu re is presented in which a time series generated from the model is Fou rier transformed for comparison with the target spectral density. For a fourth order autoregressive model, good agreement was found for the frequency range of interest (0.001-1.0 Hz). The approach outlined is s traightforward to implement, requiring minimal computational effort on ce the model parameters have been identified. It is well suited to app lication on a PC and should find wide applicability in such fields as meteorology, wind energy and structural engineering.