复杂体型屋盖表面风压的高阶统计量与非高斯峰值因子

该文研究了某站台结构刚性屋盖风洞实验中风压统计量对于数据时长的敏感性。采用不同时长的数据计算长时距脉动风压数据的偏度和峰度,结果表明高阶统计量具有非平稳特性,峰度的值受数据时长的变化影响显著。根据随机数据的峰度是否大于3,可以将其划分为软响应过程和硬响应过程。通过分析此建筑屋盖表面风压数据,发现屋盖表面存在峰度小于3的硬响应测点。而现有的峰值因子计算方法都没有具体探讨其对于这种峰度小于3的硬响应测点的适用性,该文将不同计算方法得到的软响应和硬响应峰值因子结果与标准统计方法计算值进行对比,进而判断各种方法的优劣性。结果表明非高斯峰值因子计算当中不宜引入峰度这个参数,TPP方法对于计算硬响应过程和软响应过程的非高斯峰值因子都有很好的适用性。

HIGH-ORDER STATISTICS AND NON-GAUSSIAN PEAK FACTORS OF PRESSURE PROCESSES ON A COMPLEX LONG-SPAN ROOF

Based on wind tunnel tests of a rigid model of a railway station building, high-order statistics of long-duration pressure processes were quantified in terms of skewness and kurtosis. It was found that the estimation of kurtosis is sensitive to the duration of wind pressure time-history data. Depending on whether the kurtosis is larger or smaller than three, non-Gaussian random processes can be classified as softening or hardening processes, respectively. Hardening load processes with kurtosis values smaller than three were observed in samples of wind pressure acting on the long-span roof. Non-Gaussian peak factors of wind pressure, particularly for those observed hardening pressure process, were calculated by employing various state-of-the-art methods and compared to the direct statistical analysis of the measured long-duration wind pressure data. The results suggested that kurtosis should not be used in the calculation of non-Gaussian peak factors. The recently proposed translated peak process (TPP) method is able to estimate non-Gaussian peak factors for both hardening and soft pressure processes.