基于核磁共振T_(2)时间分布快速预测不同干密度土体的渗透系数

Rapid prediction of the permeability coefficient for soil of different dry densities with NMR T2 distribution

不同干密度土体因孔隙结构的差异导致其渗透系数不同。同一工程不同位置土体的孔隙结构差异较大,为获得不同位置土体的渗透系数需要对每个位置的土样做变水头试验,这是一个耗时的过程。因此,提出一种快速预测土体不同孔隙结构条件下的渗透系数具有重要的理论和实践意义。基于核磁共振能快速测定孔径分布的优点,建立了一个基于土体T_(2)时间分布快速预测土体渗透系数的毛细管模型。该模型能够利用某一干密度土体的渗透系数,结合土体任意干密度条件下的T_(2)时间分布曲线预测该干密度条件下的渗透系数。研究结果表明:该毛细管模型在预测其他干密度土体渗透系数时,不需要计算横向表面弛豫强度ρ_(2),进而提高计算渗透系数的效率;核磁共振的每个T_(2)时间概率分布和对应孔隙直径的概率分布相同,将T_(2)时间代入毛细管模型就能直接计算渗透系数;预测的渗透系数和实测值较为一致,说明该方法具有快捷、可靠且不受人为因素干扰的优点。

Because of changes in pore structure,the permeability coefficient of soil with different dry densities varies.In the same site,the pore structures of soil at different positions are quite different.In order to obtain the permeability coefficient of soil at different positions,it is necessary to do the falling head permeability test on soil samples from different positions,which is a time-consuming process.Therefore,it is crucial to propose a model for quickly estimating the permeability coefficient of soil with different pore structures.In this paper,a capillary model for rapid prediction of the permeability coefficient of soil using T_(2) distribution is developed based on the advantages of nuclear magnetic resonance(NMR)in quickly determining pore size distribution.With the permeability coefficient of a certain dry density soil and the T_(2) distribution curves of different dry density soils,the model is able to estimate the permeability coefficient of soil under any dry density condition.The research results show that the capillary model is highly efficient for estimating the permeability coefficient of soil at different dry densities since it does not need to calculate the transverse surface relaxation strength ρ_(2);The probability of each T_(2) time value is the same as that of the corresponding pore volumetric probability,and the permeability coefficient can be calculated directly by substituting the T_(2) time into the capillary model.The predicted results of the model are basically consistent with the measured values,indicating that the method is fast,reliable and unaffected by human behaviors.