The paper deals with the digital simulation of wind velocity samples by Fractional Spectral Momentfunction. It is shown that such a function represents a third useful way to characterize a stationaryGaussian stochastic process, alongside the power spectral density and the correlation function. Themethod is applied to wind velocity fields whose power spectra is given by the Kaimal’s, theDavenport’s and the Solari’s representation. It is shown that by constructing a digital filter whosecoefficients are the fractional spectral moments, it is possible to simulate samples of the target process as superposition of Riesz fractional derivatives of Gaussian white noise processes.
|Numero di pagine||7|
|Stato di pubblicazione||Published - 2010|