| Issue |
E3S Web Conf.
Volume 730, 2026
International Conference on Advances and Innovations in Soft Soil Engineering (Soft Soils 2026)
|
|
|---|---|---|
| Article Number | 03014 | |
| Number of page(s) | 7 | |
| Section | Constitutive, Numerical, and Machine Learning Models | |
| DOI | https://doi.org/10.1051/e3sconf/202673003014 | |
| Published online | 03 August 2026 | |
Bio-chemo-hydro-mechanical finite element modeling of microbially induced calcite precipitation for optimal treatment design
Department of Civil Engineering, Lassonde School of Engineering, York University, Toronto, Ontario, Canada
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Abstract
To overcome the limitations associated with conventional cement-based soil stabilization methods, Microbially Induced Calcite Precipitation (MICP) has emerged as a sustainable alternative for improving soil strength through bio-cementation. Although substantial research has been devoted to understanding, controlling, optimizing, and designing the MICP process, there is still a need for mechanistic yet practical tools that can support the accurate design of treatment strategies and reliably predict treatment performance. This study presents a novel theoretical framework based on a finite element code that couples biological, chemical, hydraulic, and mechanical processes to predict calcium carbonate precipitation and the corresponding improvements observed in both laboratory- and field-scale applications. This study presents a detailed parametric investigation using a fully coupled BCHM finite element model to assess the influence of cyclic treatment on the overall precipitation of calcium carbonate, which is one of the main objectives in sand stabilization. Different cementation solution injection cycles were examined to evaluate how increasing treatment intensity affects calcium carbonate precipitation and its spatial distribution within the column. The results provide valuable information for optimum design of MICP injection strategies.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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