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Wind and Structures Volume 33, Number 6, December 2021 , pages 423-435 DOI: https://doi.org/10.12989/was.2021.33.6.423 |
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Design wind speed prediction suitable for different parent sample distributions |
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Lin Zhao, Xiaonong Hu and Yaojun Ge
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| Abstract | ||
| Although existing algorithms can predict wind speed using historical observation data, for engineering feasibility, most use moment methods and probability density functions to estimate fitted parameters. However, extreme wind speed prediction accuracy for long-term return periods is not always dependent on how the optimized frequency distribution curves are obtained; long-term return periods emphasize general distribution effects rather than marginal distributions, which are closely related to potential extreme values. Moreover, there are different wind speed parent sample types; how to theoretically select the proper extreme value distribution is uncertain. The influence of different sampling time intervals has not been evaluated in the fitting process. To overcome these shortcomings, updated steps are introduced, involving parameter sensitivity analysis for different sampling time intervals. The extreme value prediction accuracy of unknown parent samples is also discussed. Probability analysis of mean wind is combined with estimation of the probability plot correlation coefficient and the maximum likelihood method; an iterative estimation algorithm is proposed. With the updated steps and comparison using a Monte Carlo simulation, a fitting policy suitable for different parent distributions is proposed; its feasibility is demonstrated in extreme wind speed evaluations at Longhua and Chuansha meteorological stations in Shanghai, China. | ||
| Key Words | ||
| distribution of extreme value; maximum likelihood estimation; mean wind; Monte Carlo simulation; parent sample distribution; probability plot correlation coefficient | ||
| Address | ||
| Lin Zhao:State Key Lab of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China/ Key Laboratory of Transport Industry of Wind Resistant Technology for Bridge Structures, Tongji University, Shanghai 200092, China Xiaonong Hu:State Key Lab of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China Yaojun Ge:State Key Lab of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China/ Key Laboratory of Transport Industry of Wind Resistant Technology for Bridge Structures, Tongji University, Shanghai 200092, China | ||