Author:
Yan Bowen,Chan Pakwai,Li Qiusheng,He Yuncheng,Cai Ying,Shu Zhenru,Chen Yao
Abstract
Accurate information on wind gusts is of critical importance to various practical problems. In this study, observational wind data from high-frequency response (i.e., at a sampling rate of 10 Hz), ultrasonic anemometers instrumented at four different heights (i.e., 10 m, 40 m, 160 m, 320 m) on a weather tower were collected. The observation site featured a typical suburban condition, with no significant obstacles in the immediate proximity. The data were analyzed to identify a total of twelve descriptors of wind gusts, and to find the parent distributions that estimate these parameters well via regression analysis. The results show that the gust parameters in the context of gust magnitude and amplitude with units are best fit by the Weibull model, while non-dimensional parameters in terms of gust factor and peak factor are reasonably assessed by the log-logistic distribution. The uplift time and gust nonsymmetric factor generally exhibit a lognormal distribution, while the Gamma distribution can describe the gust length scale, uplift magnitude and passage time. It is also shown that gust factors increase linearly along with turbulence intensity. Nevertheless, empirical linear formulas given in previous studies tend to over-predict. For the vertical structure of gust descriptors, it is found that the average wind speed, gust amplitude and gust length scale in 10 min monotonically increase with height, whereas the function relationship of gust amplitude, peak factor, gust factor, turbulence intensity, rise amplitude and falling amplitude tends to decrease with height.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
4 articles.
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