A simple model for predicting the hydraulic conductivity of MICP-treated sand

In this research paper, we introduce a novel and sustainable approach for forecasting the hydraulic conductivity of sand layers subjected to microbial-induced carbonate precipitation (MICP) to mitigate the diffusion of toxic pollutants. The proposed model uniquely integrates the impact of varying CaCO₃ contents on the void ratio and estimates the average particle size of CaCO₃ crystals through scanning electron microscopy (SEM) analysis. By incorporating these parameters into the K-C equation, a simplified predictive model is formulated for assessing the hydraulic conductivity of MICP-treated sand layers. The model's effectiveness is validated through comparison with experimental data and alternative models. The outcomes demonstrate a substantial reduction in hydraulic conductivity, with a decrease ranging between 93 and 97% in the initial assessment and a decrease between 67 and 92% in the follow-up assessment, both at 10% CaCO₃ content. Notably, the hydraulic conductivity shows an initial sharp decrease followed by stabilization. These findings provide valuable insights into improving the prediction of hydraulic conductivity in MICP-treated sand layers, promoting a sustainable method for preventing pollution dispersion.