Year: 2026
Type: article
Abstract: Microbially Induced Calcite Precipitation (MICP) is a soil improvement technique that enhances strength through the precipitation of inter-grain calcite bonds, which resist grain displacement under external loading. Understanding the failure mechanisms of these bonds is crucial for accurately estimating the mechanical behavior of MICP-treated soil. However, existing studies remain limited due to the challenges associated with micro-scale experimental observation. To address this, we developed a novel numerical approach based on a coupled Material Point Method and Discrete Element Method (MP-DEM) formulation to simulate the tensile failure of calcite bonds. To explicitly capture both internal and interfacial failure patterns, we enhanced the MP-DEM framework in three key aspects: ( i ) an anisotropic continuum damage mechanics model that accurately simulates the calcite bond’s transition from brittle damage to failure; ( ii ) a coupled damage model to capture the growth of interfacial detachment between the grain and calcite; and ( iii ) a cementation duality condition to enforce consistency between these damage models. The model is rigorously validated against existing experimental measurements, demonstrating its capability to accurately reproduce the tensile strengths and failure patterns of calcite-bonded grains. Furthermore, our simulations reveal the underlying mechanisms of different failure modes through a process of spatially distinct damage growth. Finally, numerical tests considering in-situ effective stress conditions indicate that tensile strength varies significantly with confinement, highlighting the necessity of redefining the optimal cementation degree for MICP treatments.
Source: Computers and Geotechnics
Authors: Tirtho Sarathi Saha, Yang Xiao, Yupeng Jiang
Institution: Chongqing University
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,640
Funder: Deutsche Forschungsgemeinschaft
Award: G8124717078
OpenAlex ID: W7171563208