Experimental study and model prediction of the influence of different factors on the mechanical properties of saline clay - Hui Cheng; Lingkai Zhang; Chong Shi; Pei Pei Fan (Scientific Reports)
Abstract Water conveyance channels in cold and arid regions pass through several saline-alkali soil areas. Canal water leakage exacerbates the salt expansion traits of such soil, damaging canal slope lining structures. To investigate the mechanical properties of saline clay, this study conducted indoor tests, including direct shear, compression, and permeation tests, and scanning electron microscopy (SEM) analysis of soil samples from typical sites. This study aims to elucidate the impact of various factors on the mechanical properties of saline clay from a macro–micro perspective and reveal its physical mechanisms. A prediction model is formulated and validated. The findings indicate the following: (1) Cohesion in direct shear tests has a linear negative correlation with water content and a positive correlation with dry density and initially decreases with increasing salt content until 2%, after which it increases. The internal friction angle initially increases and then decreases with increasing water content, reaching a peak at the optimal water content, and then gradually increases with dry density while initially decreasing, followed by an increase in salt content, stabilizing thereafter. Water content, dry density, or salt content chiefly affect cohesion by influencing electrostatic attraction, van der Waals forces, particle cementation, and valence bonds at particle contact points. (2) Compression tests reveal a linear positive correlation between the compression coefficient and water content, a negative correlation with dry density, and a stepwise linear correlation with salt content, peaking at 2%. The compression index decreases with increasing water content and dry density, following a trend similar to that of the compression coefficient with increasing salt content. The rebound index shows a linear negative correlation with water content and dry density, transitioning from a negative to a positive correlation at 2% salt content. Scanning electron microscopy analysis revealed particle flattening and increased aggregation with increasing consolidation pressure, reducing compressibility. Large pores and three-dimensional porosity have the greatest influence on soil compressibility. (3) Permeability tests reveal an exponential negative correlation between the permeability coefficient and dry density. As the dry density increases, the particle arrangement becomes denser, decreasing the pore quantity, with micropores disproportionately impacting the permeability coefficient. An increase in salinity initially increases the permeability coefficient before it decreases. The boundary point of the 2% salt content divides the effect of salt ions from promoting free water flow to blocking seepage channels, with the proportion of micropores being the primary influencing factor. (4) Employing statistical theory and machine learning algorithms, dry density, water content, and salinity are used to predict mechanical index values. The improved particle swarm optimization-support vector regression (PSO-SVR) model has high accuracy and general applicability. These findings offer insights for the construction and upkeep of open channel projects in arid regions.