statistical analysis of wind-induced dynamic response of power towers and four-circuit transmission tower-line system

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ID: 220236
2018
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Abstract
Only one wind field model loading the transmission tower or the tower-line system was investigated in the previous studies, while the influence of two different wind field models was not considered. In addition, only one sample of the wind speed random process was used in the past numerical simulations, and the multiple dynamic response statistical analysis should be carried out. In this paper, statistical analysis of the wind-induced dynamic response of single towers and the transmission tower-line system is performed with the improved accuracy. A finite element model of the transmission tower-line system (the tower consisted of both steel tubes and angel steels) is established by ANSYS software. The analysis was performed by three statistical methods. The effects of the length of the time history and of the number of samples were investigated. The frequency histograms of samples follow the Gaussian distribution. The characteristic statistical parameters of samples were random. The displacements and the axial forces of the low tower are larger than those of the high tower. Two wind field models were applied to simulate the wind speed time history. In field 1 model, Davenport wind speed spectrum and Shiotani coherence function were applied, while in field 2 model Kaimal wind speed spectrum and Davenport coherence function were used. The results indicate that wind field 1 is calmer than wind field 2. The displacements and the axial forces of the tower-line system are less than those of single towers, which indicate damping of wind-induced vibrations by the transmission line. An extended dynamic response statistical analysis should be carried out for the transmission tower-line system.
Reference Key
zhang2018shockstatistical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Xiaolei Zhang;Yanzhong Ju;Fuwang Wang
Journal Nano letters
Year 2018
DOI
10.1155/2018/5064930
URL
http://dx.doi.org/10.1155/2018/5064930
Keywords
physics

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