Abstract
Accurate determination of soil-water characteristic curve (SWCC) is of immense importance for understanding the mechanical behavior of unsaturated soils. Due to the difficulty and long duration of experimental procedures, it is of great significance to estimate the SWCC by indirect methods. To address this issue, in this article an effective fractal method is proposed for predicting the SWCC based on mercury intrusion porosimeter (MIP) data. Only two characteristic parameters, namely the fractal dimension and air-entry value, are needed in the presented approach. Detailed procedures for determining the parameters are clearly elaborated. Due to the influence of sample size difference on the equivalent connected pore size, a sample scale effect coefficient is proposed to predict air-entry values. The concept of “critical pore size” is introduced to obtain the optimal fractal dimension, which can accurately reflect the fractal behaviour of SWCC samples. By comparisons between predicted and experimental SWCCs, the validation of the proposed method is verified. The comparisons reveal the good agreement between the proposed approach and laboratory experiments.
Highlights
Accurate determination of soil-water characteristic curves (SWCCs) is crucial to understand the shear strength, permeability coefficient, volume strain and water distribution of unsaturated soils.Due to the difficulty and long duration of experimental procedures, over the past years, increasing efforts have been focused on indirect estimations of SWCCs.In recent years, various attempts have been made to predict SWCC from the pore size distribution (PSD) [1,2,3,4]
For a given state of soils, it has been reported that PSD has great influence on SWCC [5,6]
mercury intrusion porosimeter (MIP) tests and SWCC is the size of the test samples, which has an influence on the prediction accuracy of SWCC, but this was usually ignored in prior studies
Summary
Accurate determination of soil-water characteristic curves (SWCCs) is crucial to understand the shear strength, permeability coefficient, volume strain and water distribution of unsaturated soils. The approach of predicting SWCC from PSD is mainly in a stage of model research, and an effective method has not been formed yet. In this respect, Tao et al [23] proposed a fractal approach to predict SWCC from. MIP tests and SWCC is the size of the test samples, which has an influence on the prediction accuracy of SWCC, but this was usually ignored in prior studies To solve this issue, a new prediction approach for SWCC is presented in which the MIP technique is employed to determine two parameters, namely fractal dimension and air-entry value. The accuracy of the proposed approach is thoroughly verified through the experimental data from MIP and SWCC tests
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