延安压实黄土土-水特征曲线的快速预测方法

Rapid prediction method of soil-water characteristic curve of Yan’an compacted loess

传统测试土-水特征曲线(soil-water characteristic curve,简称SWCC)方法耗时较长,开发快速确定非饱和土的SWCC具有重要的实践意义。为了实现压实黄土SWCC快速预测,对不同干密度压实黄土进行了水势和水分测试,并且运用核磁共振(nuclear magnetic resonance,简称NMR)技术对其孔径分布曲线进行了测试。根据测试结果建立了基于孔隙比的延安压实黄土土-水特征曲线快速预测方法,并利用实测数据验证了方法的准确性。结果表明:预测模型中的分形维数D可用孔径分布曲线上两点(峰值点和半幅点)的累计孔隙体积与孔径在双对数坐标中连成直线的斜率确定;基于孔隙比和优势孔径在双对数坐标中的线性关系,D可用孔隙比进行表示。SWCC进气值受大孔隙直径控制;过渡段斜率受中孔隙体积控制;压实黄土存在一个临界孔径,而残余含水率主要受孔径小于临界孔径的孔隙体积控制,并且提出了求取残余体积含水率的经验方法。与传统方法相比,所提出的方法可以在确定SWCC时节省大量时间。

The traditional SWCC test method is time-consuming, and it is of great practical significance to develop a method that can quickly determine the SWCC of unsaturated soil. In order to predict the SWCC of compacted loess rapidly, the water potential and moisture content of compacted loess with different dry densities were tested, and the pore size distribution curve was measured using nuclear magnetic resonance(NMR) technology. Based on the test results, a rapid prediction method of the soil-water characteristic curve of Yan’an compacted loess was established based on the void ratio, and its accuracy was verified by the measured data. The results show that the fractal dimension D in the prediction model can be determined by the cumulative pore volume of two points(peak point and half-width point) on the pore size distribution curve and the slope of the pore size in a double logarithmic coordinate;and it can be expressed by the void ratio based on the linear relationship between void ratio and dominant pore diameter in logarithmic coordinates. The inlet value of SWCC is controlled by the diameter of macropore;the slope of the transition section is controlled by the volume of mesopore. There is a critical pore size in compacted loess, the residual water content is mainly controlled by the pore volume whose pore size is smaller than the critical pore size, and an empirical method is proposed to calculate the residual volume water content. Compared with traditional methods, the proposed method can save a lot of time in determining SWCC.