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contributor authorRui Zhou
contributor authorXin Jia
contributor authorJingchao Li
contributor authorDan Li
contributor authorPeng Lu
contributor authorZhouhong Zong
date accessioned2025-04-20T10:10:26Z
date available2025-04-20T10:10:26Z
date copyright9/6/2024 12:00:00 AM
date issued2024
identifier otherJBENF2.BEENG-6775.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4304138
description abstractThe superstrong typhoon Lekima landed twice along the Yellow Sea of China in 2019; its wind characteristics and impact on bridges’ buffeting performance are still unclear. Based on the measured wind and temperature data of a long-span composite girder cable-stayed bridge along the Yellow Sea, this paper studies the wind characteristics and wind–temperature correlation of typhoon Lekima at the bridge site. First, the non-Gaussian and nonstationary tests of the typhoon are carried out at three stages, namely, before, during, and after the landing of the typhoon. Second, the turbulence intensity and gust factor at the three stages are statistically analyzed, and then the power spectra and the turbulence integral scale are compared by using four evaluation methods. Finally, the joint distribution model of the wind speed and structural temperature at the bottom of the composite girder is constructed, and their parameter estimation and the density functions of five copula functions are calculated, respectively. The results indicate that the wind speed has obvious Gaussian and nonstationary characteristics during the typhoon, while it has non-Gaussian and nonstationary characteristics before and after the typhoon. The gust factor is consistent in characterizing the turbulent characteristics of the fluctuating wind and linearly changes with the turbulence intensity. Besides, the power spectrum is consistent with four classical spectra in the low-frequency region before and during the typhoon, and the autocorrelation index method and power spectrum method are not suitable for calculating its turbulence integral scale. By comparing the square Euclidean distances, root mean square error, and the Kendall and Spearman rank correlation coefficients, the Frank-copula function has the best fitting accuracy for the correction between the wind speed and temperature among the five copula functions with a symmetric U-shaped distribution in thick-tails’ location.
publisherAmerican Society of Civil Engineers
titleWind–Temperature Characteristics of a Cable-Stayed Bridge along the Yellow Sea under Superstrong Typhoon Lekima
typeJournal Article
journal volume29
journal issue11
journal titleJournal of Bridge Engineering
identifier doi10.1061/JBENF2.BEENG-6775
journal fristpage04024086-1
journal lastpage04024086-14
page14
treeJournal of Bridge Engineering:;2024:;Volume ( 029 ):;issue: 011
contenttypeFulltext


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