Application of biopolymers to improve the mechanical properties of soils has been extensively reported. However, a comprehensive understanding of various engineering applications is necessary to enhance their effectiveness. While numerous experimental studies have investigated the use of biopolymers as injection materials, a detailed understanding of their injection behavior in soil through numerical analyses is lacking. This study aimed to address this gap by employing pore network modeling techniques to analyze the injection characteristics of biopolymer solutions in soil. A pore network was constructed from computed tomography images of Ottawa 20-30 sand. Fluid flow simulations incorporated power-law parameters and governing equations to account for the viscosity characteristics of biopolymers. Agar gum was selected as the biopolymer for analysis, and its injection characteristics were evaluated in terms of concentration and pore-size distribution. Results indicate that the viscosity properties of biopolymer solutions significantly influence the injection characteristics, particularly concerning concentration and injection pressure. Furthermore, notable trends in injection characteristics were observed based on pore size and distribution. Importantly, in contrast to previous studies, meaningful correlations were established between the viscosity of the injected fluid, injection pressure, and injection distance. Thus, this study introduces a novel methodology for integrating pore network construction and fluid flow characteristics into biopolymer injections, with potential applications in optimizing field injections such as permeation grouting.

Loess is widely distributed in China and it is commonly considered as the problematic soil due to its collapsibility subjected to the water invasion. The microstructure plays an important role in the mechanical properties of the loess soil. In this note, the microstructures of intact loess samples and the inundated loess sample were investigated by using both mercury intrusion porosimetry (MIP) and nuclear magnetic resonance cryoporometry (NMRC). It is observed from the results of both MIP and NMRC tests that the intact loess has a multi-model pore size distribution function while the inundated loess has a unimodal pore size distribution function. As the coefficient of collapsibility (delta s) is a key parameter commonly used for the evaluation of the engineering properties of the loess, the delta s of the specimens tested under different conditions was measured. Subsequently, a new multi-variable linear model was proposed for the estimation of delta s from the index properties based on the results of factor analyses. The estimated results of delta s from the proposed model show good agreements with the measured data.