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http://dx.doi.org/10.12989/sss.2016.17.6.1067

Stationary and nonstationary analysis on the wind characteristics of a tropical storm  

Tao, Tianyou (Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education)
Wang, Hao (Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education)
Li, Aiqun (Key Laboratory of Concrete and Prestressed Concrete Structures of Ministry of Education)
Publication Information
Smart Structures and Systems / v.17, no.6, 2016 , pp. 1067-1085 More about this Journal
Abstract
Nonstationary features existing in tropical storms have been frequently captured in recent field measurements, and the applicability of the stationary theory to the analysis of wind characteristics needs to be discussed. In this study, a tropical storm called Nakri measured at Taizhou Bridge site based on structural health monitoring (SHM) system in 2014 is analyzed to give a comparison of the stationary and nonstationary characteristics. The stationarity of the wind records in the view of mean and variance is first evaluated with the run test method. Then the wind data are respectively analyzed with the traditional stationary model and the wavelet-based nonstationary model. The obtained wind characteristics such as the mean wind velocity, turbulence intensity, turbulence integral scale and power spectral density (PSD) are compared accordingly. Also, the stationary and nonstationary PSDs are fitted to present the turbulence energy distribution in frequency domain, among which a modulating function is included in the nonstationary PSD to revise the non-monotonicity. The modulated nonstationary PSD can be utilized to unconditionally simulate the turbulence presented by the nonstationary wind model. The results of this study recommend a transition from stationarity to nonstationarity in the analysis of wind characteristics, and further in the accurate prediction of wind-induced vibrations for engineering structures.
Keywords
tropical storm; wind characteristics; stationarity; nonstationarity; structural health monitoring;
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