The full-scale value of the Reynolds number associated with wind loads on structures is of the order of 10^7. This is further complicated by the high levels of turbulence fluctuations associated with strong winds. On the other hand, numerical and wind tunnel simulations are usually carried out at smaller values of Re. Consequently, the validation of these simulations should only be based on physical phenomena derived with tools capable of their identification. In this work, two physical aspects related to extreme wind loads on low-rise structures are examined. The first includes the statistical properties and prediction of pressure peaks. The second involves the identification of linear and nonlinear relations between pressure peaks and associated velocity fluctuations. The first part of this thesis is concerned with the statistical properties of surface pressure time series and their variations under different incident flow conditions. Various statistical tools, including space-time correlation, conditional sampling, the probability plot and the probability plot correlation coefficient, are used to characterize pressure peaks measured on the top surface of a surface-mounted prism. The results show that the Gamma distribution provides generally the best statistical description for the pressure time series, and that the method of moments is sufficient for determining its parameters. Additionally, the shape parameter of the Gamma distribution can be directly related to the incident flow conditions. As for prediction of pressure peaks, the results show that the probability of non-exceedence can best be derived from the Gumbel distribution. Two approaches for peak prediction, based on analysis of the parent pressure time series and of observed peaks, are presented. The prediction based on the parent time series yields more conservative estimates of the probability of non-exceedence. The second part of this thesis is concerned with determining the linear and nonlinear relations between pressure peaks and the velocity field. Validated by analytical test signals, the wavelet-based analysis is proven to be effective and accurate in detecting intermittent linear and nonlinear relations between the pressure and velocity fluctuations. In particular, intermittent linear and nonlinear velocity pressure relations are observed over the nondimensional frequency range fH/U<0.32. These results provide the basis for flow parameters and characteristics required in the simulation of the wind loads on structures.

Ph. D.