Peak distributions and peak factors of wind-induced pressure processes on tall buildings

M. F. Huang, Wenjuan Lou, C. M. Chan, Ning Lin, Xiaotao Pan

Research output: Contribution to journalArticlepeer-review

84 Scopus citations


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.Anew 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.

Original languageEnglish (US)
Pages (from-to)1744-1756
Number of pages13
JournalJournal of Engineering Mechanics
Issue number12
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering


  • Extreme value
  • Non-gaussian process
  • Peak distribution
  • Peak factor
  • Tall building
  • Wind pressure


Dive into the research topics of 'Peak distributions and peak factors of wind-induced pressure processes on tall buildings'. Together they form a unique fingerprint.

Cite this