Estimation of extreme wind speed based on upcrossing rate of mean wind speeds with Weibull distribution

The estimation of the extreme mean wind speed has a pivotal role in the structural wind-resistance design. For yearly maximum mean wind speed samples usually not enough, it is necessary to estimate the extreme mean wind speed from short-term mean wind speed records, such as about a few years. The upcrossing rate method, which relies on the distribution of the mean wind speed, is one of the popular extreme estimation methods. It is widely recognized that the mean wind speed follows the Weibull distribution usually and the Rayleigh distribution at some areas. The upcrossing rate method for mean wind speed time series following Rayleigh distribution was proposed by Harris. The upcrossing rate method for mean wind speed time series following the Weibull distribution is studied in the present paper, by translating the Weibull process to the Rayleigh process based on the theory of cumulative distribution function mapping. The uncertainty of the extreme mean wind speed estimated by the proposed method is investigated to consider the sampling error from short-term mean wind speed records. The effectiveness of the proposed upcrossing rate method and uncertainty analysis are verified by the numerically generated mean wind speeds based on the spectral representation method with Von der Hoven wind speed spectrum.

Automated summary

The estimation of extreme mean wind speed is crucial in structural wind-resistance design. This study focuses on estimating extreme mean wind speed from short-term records using the upcrossing rate method. The method is based on the distribution of mean wind speed, typically Weibull or Rayleigh. The paper investigates the upcrossing rate method for mean wind speed following Weibull distribution and considers sampling error for uncertainty analysis.