低矮房屋风压时程的概率分布

对一低坡度的低矮房屋进行刚性模型测压试验,首先对其屋面的偏度分布进行了分析,进而利用概率图相关系数(PPCC)方法,对不同区域的测点风压系数时程和面积平均后的风压系数时程概率分布用Gamma分布、广义极值(GEV)分布及对数正态(Lognorm)分布进行拟合比较.试验结果表明:屋面在斜风向下各区域的偏度差别较大,其锥形涡的涡轴上偏度较小,小于0.50,而两翼偏度均大于1.50,最大的已超过3.00;偏度较小(小于0.80)的时程与对数正态分布吻合得最好,偏度较大(大于0.80)的时程与广义极值分布吻合得最好；随着偏度的增大(达到1.50以后),这三种分布和原始时程的概率分布误差越来越大；面积平均后的时程偏度都在0.50～1.50,和三种分布吻合得都很好.

Probability Density Distribution of Wind Pressure Time Series of Low rise Buildings

The rigid model measurement experiment of low rise buildings with low pitch was conducted. First, the skewness distribution of the roof was analyzed, then the probability distribution of pressure coefficient time series of the single tap and area average of several taps in different regions was compared among the Gamma, generalized extreme value(GEV) and Lognorm probability density distributions by probability plot correlation coefficient(PPCC) method. The results show that when the wind blows oblique to the roof, the skewness of each region is different. The skewness of the conical vortex aixs is small while that of the two wings exceeds 1.50, where the largest value is up to 3.00. The time series with small skewness (less than 0.80) is fitted best with the Lognorm distribution. The time series with large skewness (larger than 0.80) is fitted best with the GEV distribution. And when the skewness is larger than 1.50, the deviation between the original probability distribution of the time series and any of the distribution is getting more large. The skewnesse of the area average time series is between 0.50 and 1.50, and the probability distribution is fitted well with any of the three kinds of distribution.