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Wind and Structures Volume 38, Number 4, April 2024 (Special Issue) pages 309-323 DOI: https://doi.org/10.12989/was.2024.38.4.309 |
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Probabilistic analysis of gust factors and turbulence intensities of measured tropical cyclones |
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Tianyou Tao, Zao Jin and Hao Wang
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| Abstract | ||
| The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cablestayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications. | ||
| Key Words | ||
| field measurement; gust factor; probabilistic analysis; tropical cyclone; turbulence intensity | ||
| Address | ||
| Tianyou Tao:1)Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China 2)School of Civil Engineering, Southeast University, Nanjing 211189, China Zao Jin:School of Civil Engineering, Southeast University, Nanjing 211189, China Hao Wang:1)Key Laboratory of C&PC Structures of Ministry of Education, Southeast University, Nanjing 211189, China 2)School of Civil Engineering, Southeast University, Nanjing 211189, China | ||