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 CaCO contents on the void ratio and estimates the average particle size of CaCO 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% CaCO 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.