Prediction of permeability of sands treated by enzyme-induced calcium precipitation (EICP): Mathematical model

Enzyme-induced carbonate precipitation (EICP) is a potential ground improvement method that can reduce the permeability of sands. However, the traditional mathematical models are hard to accurately predict the permeability of EICP-treated sands. In this study, the mathematical model was established for predicting the permeability of EICP-treated sands based on Kozeny-Carman equation. The effects of calcium carbonate precipitation on the porosity, tortuosity, and specific surface area of the EICP-treated sands were considered in the model. To validate the model, the bio-cemented sand column tests with different grain size distributions (coarse, medium, and fine sands) and treatment numbers (6, 8, and 10 times) were conducted. The calcium carbonate content (CCC) and permeability of EICP-treated sands were measured. The validation of the model was confirmed through a comparative analysis of theoretical and experimental results. Furthermore, the impacts of porosity, particle size, CCC, and specific surface area on the hydraulic conductivity of EICP-treated sands were analyzed. The results showed that the model can reflect the hydraulic conductivity of EICP-treated sands under different particle size distributions and degrees of cementation, demonstrating broad applicability. Parametric analysis indicated the hydraulic conductivity gradually decreases with increasing CCC and specific surface area. Conversely, the hydraulic conductivity gradually increases with increasing porosity (n) and particle size (d50), with porosity exhibiting a significantly higher sensitivity than particle size. In summary, this study contributes theoretical foundations for the practical implementation of EICP technology in reducing soil permeability.