Peak Distributions and Peak Factors of Wind-Induced Pressure Processes on Tall Buildings

Abstract

The emergence of performance-based wind engineering calls for improved probabilistic modeling of wind effects on buildings. This paper focuses on the development of probabilistic models of the peak distribution and peak factor for non-Gaussian processes and explores the applications of this development in wind engineering. The closed-form expressions for the mean, SD, and fractile levels of extremes are derived for a random process whose peaks are modeled by the parametric Weibull distribution. A new translated-peak-process method is then developed for the estimation of the peak distribution, peak factor, and variability of extremes, based on the Weibull distribution and point-to-point mapping procedure. The proposed translated-peak-process method is validated by wind-tunnel pressure measurements on a standard tall building and is shown to be more robust and practical than many existing methods in analyzing non-Gaussian wind pressure data.