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<p>To study the characteristics of wind speed in mountains, field measurement was carried out at the bridge site of an ultra-high-pier bridge in China. An adaptive method for extracting wind speed from MODWT is established, and the accuracy of extracting time-varying average wind speed by this method is verified. A non-stationary wind speed model is established to analyze the characteristic parameters of turbulent wind speed and compared with the traditional stationary model. The results show that this method can automatically determine the only suitable time-varying average wind speed through relevant parameter. This method is more accurate than DWT and avoids the choice of decomposition layer. The stationary model overestimates the turbulent characteristics of wind, and its turbulent intensity, gust factor, and PSD are higher than those of the non-stationary model. Based on the measured wind speeds, in the along-wind direction, the turbulence intensity of stationary model is 28% higher than that of non-stationary model, and the turbulence intensity of non-stationary model is 67% higher than the standard value, the gust factor of stationary model is 10.1% higher than that of non-stationary model, and the maximum value of PSD of non-stationary model is 207.08, and that of stationary model is 2.54 times that of non-stationary model.</p>

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Non-stationary characteristics of measured wind speed of continuous rigid frame bridge with high piers in mountains

  • 期刊论文

  • 发表日期：

    2025年4月15日

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  • Hu Jun,
  • Zhang Xinqi,
  • Zhang Li,
  • Wu Haibin,
  • Wen Jiajian

摘要

To study the characteristics of wind speed in mountains, field measurement was carried out at the bridge site of an ultra-high-pier bridge in China. An adaptive method for extracting wind speed from MODWT is established, and the accuracy of extracting time-varying average wind speed by this method is verified. A non-stationary wind speed model is established to analyze the characteristic parameters of turbulent wind speed and compared with the traditional stationary model. The results show that this method can automatically determine the only suitable time-varying average wind speed through relevant parameter. This method is more accurate than DWT and avoids the choice of decomposition layer. The stationary model overestimates the turbulent characteristics of wind, and its turbulent intensity, gust factor, and PSD are higher than those of the non-stationary model. Based on the measured wind speeds, in the along-wind direction, the turbulence intensity of stationary model is 28% higher than that of non-stationary model, and the turbulence intensity of non-stationary model is 67% higher than the standard value, the gust factor of stationary model is 10.1% higher than that of non-stationary model, and the maximum value of PSD of non-stationary model is 207.08, and that of stationary model is 2.54 times that of non-stationary model.