Statistical discrete gust analysis of tower-based atmospheric turbulence data for aircraft response studies

Turbulence modelling for aircraft response studies requires adequate representation of atmospheric turbulence to provide for realistic reproduction of turbulence loads on an airframe. The power spectral density method, the traditional tool based on Fourier analysis that has been extensively used, does not account for coherent structures or the gusts so predominant in atmospheric turbulence. The statistical discrete gust (SDG) model was developed to overcome this problem, and the coherent structures are introduced in the form of discrete ramp-gusts. The model defines the associated probability distributions in terms of the amplitude and scale of such discrete gusts with refinements to take care of deviation of real turbulence from self-similar behaviour and scale-dependent intermittency, and provides a more realistic basis for predicting aircraft response to atmospheric turbulence. In the present work, the possibility of using tower-derived atmospheric turbulence data, instead of the commonly used aircraft measured data, for SDG analysis is investigated. The discrete gusts in the data have been detected using two methods, namely the wavelet transform method and the smoothing-differencing method, and the associated amplitudes and scales are extracted. The SDG analysis carried out by varying both the similarity parameter and the fractal dimension of turbulence to account for, respectively, the deviation of atmospheric turbulence from selfsimilarity and scale-dependent intermittency shows that tower-based data are highly useful to determine the model parameters. The values of the similarity parameter estimated from the data (from both the power spectra and wavelet transform) indicate the need for the incorporation of deviation of atmospheric turbulence from self-similarity and scale-dependent intermittency in the SDG model. The intermittency and intensity parameters involved in the SDG model are estimated from the tower data and show good comparison with those derived from aircraft measured data. The variation of the parameters with height and time is discussed and the relation between the intensity of fluctuations in the data and their intermittency with the corresponding model parameters is elucidated.