Predictive strength model of cement-treated fine-grained soils using key parameters: Consideration of the total water/cement and soil/cement ratios

Abstract

Soil stabilization techniques have been widely used to improve the mechanical and engineering properties of soft ground, such as strength, compressibility, and permeability. Recently, dredged soils that have high water content, high compressibility, and low strength have been mixed with cement and used as filling and landfill materials. The water and cement contents and soil types (clay or silt) in these soil–cement mixtures can be determined according to the purpose of use. To this end, the design of these mixtures requires the accurate prediction of the unconfined compressive strength (qu). Therefore, this paper proposes a predictive model for qu of cement-treated fine-grained soils (CTFSs) for ground improvement and stabilization of dredged soils. Ordinary Portland cement and two types of fine-grained soils (clay and silt) were used as the basic materials in the experiment. Unconfined compression tests were performed in a wide range of experiment conditions: water content (wt: 40–170 %), cement content (c: 5–25 %), and curing time (t: 3–90 d), and the results were correlated by two key parameters, wt/c (total water content/cement ratio) and s/c (soil/cement ratio). The results demonstrated that wt/c and s/c were strongly correlated with the qu development of CTFSs depending on the curing period. Therefore, we established a predictive model for qu by combining the power and exponential functions for (s/c)X and (wt/c)Y. The X and Y values of proposed model could equally be applied for different curing periods for soils of different types with different characteristics. In addition, the proposed model could predict long-term qu by using the time coefficient (ct) normalized by the curing period of 7 d. The mean absolute percentage error and coefficient of determination of the proposed model were lower and higher, respectively, than those of the reported data. Overall, the proposed predictive model is a promising tool for predicting the qu of CTFSs, for instance, for ground improvement and cement-treated dredged soils.