Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Comparative Study of the Wind Characteristics of a Strong Wind Event Based on Stationary and Nonstationary Models
Inherent time-varying trends of wind records are frequently captured in recent field measurements of tropical cyclones. These observations indicate a nonstationary process that deviates from the traditional stationary assumption. In this study, a strong wind event from a landfall typhoon recorded at Sutong Bridge site (Jiangsu Province, China) in 2008 is selected for the investigation of stationary and nonstationary wind characteristics. Since the extraction of the underlying trend is usually determined by experience, a self-adaptive method is presented to automatically isolate the time-varying mean based on the signal stationarity. Once the trend is removed, the residual turbulence will naturally be stationary. Accordingly, two categories of fluctuating wind speeds are then obtained by subtracting constant or time-varying means from original wind samples. Based on the traditional stationary model and two recent nonstationary models, stationary and nonstationary turbulent wind characteristics, e.g., turbulence intensity, gust factor, peak factor, turbulence integral scale, and power spectral density (PSD), are comparatively investigated and compared with the recommendations from relevant building codes and standards. The results highlight the importance of the nonstationary considerations. In addition, the evolutionary power spectral density (EPSD) of fluctuating wind is discussed to examine the short-term stationary assumption in the calculation of time-frequency turbulence spectrum. A general empirical EPSD is derived and demonstrated effective and efficient in engineering applications.
Comparative Study of the Wind Characteristics of a Strong Wind Event Based on Stationary and Nonstationary Models
Inherent time-varying trends of wind records are frequently captured in recent field measurements of tropical cyclones. These observations indicate a nonstationary process that deviates from the traditional stationary assumption. In this study, a strong wind event from a landfall typhoon recorded at Sutong Bridge site (Jiangsu Province, China) in 2008 is selected for the investigation of stationary and nonstationary wind characteristics. Since the extraction of the underlying trend is usually determined by experience, a self-adaptive method is presented to automatically isolate the time-varying mean based on the signal stationarity. Once the trend is removed, the residual turbulence will naturally be stationary. Accordingly, two categories of fluctuating wind speeds are then obtained by subtracting constant or time-varying means from original wind samples. Based on the traditional stationary model and two recent nonstationary models, stationary and nonstationary turbulent wind characteristics, e.g., turbulence intensity, gust factor, peak factor, turbulence integral scale, and power spectral density (PSD), are comparatively investigated and compared with the recommendations from relevant building codes and standards. The results highlight the importance of the nonstationary considerations. In addition, the evolutionary power spectral density (EPSD) of fluctuating wind is discussed to examine the short-term stationary assumption in the calculation of time-frequency turbulence spectrum. A general empirical EPSD is derived and demonstrated effective and efficient in engineering applications.
Comparative Study of the Wind Characteristics of a Strong Wind Event Based on Stationary and Nonstationary Models
Tao, Tianyou (Autor:in) / Wang, Hao (Autor:in) / Wu, Teng (Autor:in)
08.12.2016
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Investigation of stationary and nonstationary wind data using classical Box Jenkins models
| British Library Conference Proceedings | 1993
Investigation of stationary and nonstationary wind data using classical Box-Jenkins models
| Online Contents | 1994
| British Library Conference Proceedings | 1994
| Wiley | 2021