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http://dx.doi.org/10.12989/was.2021.32.6.587

Research on the probability model of basic wind speed estimation in China  

Xiang, Cheng (Department of Bridge Engineering, Tongji University)
Chen, Airong (Department of Bridge Engineering, Tongji University)
Li, Qiheng (ShangHai Municipal Engineering Design Institute (Group) Co., Ltd.)
Ma, Rujin (Department of Bridge Engineering, Tongji University)
Publication Information
Wind and Structures / v.32, no.6, 2021 , pp. 587-596 More about this Journal
Abstract
Wind speed is one of the most critical parameters in predicting structural performance under wind effects. In most of the current standards and codes, the design reference wind speed is usually determined by fitting a typical probability distribution model based on the historical wind speed data. However, a single distribution model is generally insufficient to reflect the regional differences in wind characteristics. Therefore, in this research, the optimal probability is selected to determine the extreme wind speed in different regions in China based on the fourth-order linear moment method (FLMM). Firstly, several probability models for estimating extreme wind speed distribution are introduced. Then, the optimal model, as well as the relative parameters, are determined by the linear moments (L-moments) method, and the one with the minimum value of the fourth-order linear moment between the probability model and the sample is taken as the optimal distribution. Finally, the extreme wind speed of each meteorological station is estimated according to the obtained optimal distribution, and the results are compared with the recorded extreme wind speed of typical metrological stations as well as that in the previous version of specification (JTG/T D60-01-2004). Compared with the traditional method that adopting a single distribution model-based wind speed estimation, the extreme wind speed obtained by the proposed method possessed higher accuracy.
Keywords
extreme wind speed; probability distribution; fourth-order linear moment method; bridge engineering; wind speed design values;
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