Extreme wind pressure estimation based on the r largest order statistics mode

This paper presents a procedure for statisticalestimation of extreme wind pressures using the r largest order statistics(r-LOS) model, which includes a joint generalized extreme value (GEV) modeland joint Gumbel model. Methods are devised to extract r-LOS vectors ofindependent peaks from individual time histories, choose optimum r, anddiscriminate between the r-LOS GEV model and r-LOS Gumbel model, respectively.The procedure is applied to analyze the pressure data obtained on the rigidmodel of a low-rise industrial building. When multiple pressure timehistories are used to estimate the extreme pressure coefficients, ther-LOS Gumbel model is superior to the r-LOS GEV model and the classical Gumbelmodel. When a single time history is used, the r-LOS Gumbel model usuallyestimates the extreme pressure coefficients more accurately than the peakfactor method based on the Modified Hermite Model and Sadek-Simiu procedure,and it is applicable when the wind pressure is non-Gaussian; furthermore,the r-LOS Gumbel model gives an analytical solution to the quantiles ofextreme pressure coefficients. The paper concludes that the procedure basedon the r-LOS Gumbel model is an effective alternative for the estimation ofextreme wind pressures when either multiple pressure time histories or asingle time history is available.