A Numerical Reactive Flow and Transport Model for Cementation Processes in Bio-concrete Production.
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| Title: | A Numerical Reactive Flow and Transport Model for Cementation Processes in Bio-concrete Production. |
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| Authors: | Hommel, Johannes1 (AUTHOR) johannes.hommel@iws.uni-stuttgart.de, Bozkurt, Kerem1 (AUTHOR) kerem.bozkurt@iws.uni-stuttgart.de, Nething, Christoph2 (AUTHOR) christoph.nething@ilek.uni-stuttgart.de, Eppinger, Erik3 (AUTHOR) erik.eppinger@imb.uni-stuttgart.de, Wang, Yue1 (AUTHOR) yue.wang@iws.uni-stuttgart.de, Blandini, Lucio2 (AUTHOR) lucio.blandini@ilek.uni-stuttgart.de, Class, Holger1 (AUTHOR) holger.class@iws.uni-stuttgart.de |
| Source: | Transport in Porous Media. Oct2026, Vol. 153 Issue 7, p1-30. 30p. |
| Subjects: | Reactive flow, Calcium carbonate, Calcite, Computer simulation, Cement, Transport theory, Porosity, Cement composites |
| Abstract: | Concrete is the most widely used construction material worldwide, yet Portland-cement production accounts for approximately 8% of global CO 2 emissions. Bio-cementation processes based on calcium carbonate precipitation offer a promising low-carbon alternative, but their engineering application is limited by a lack of predictive models for coupled transport, reaction, and cementation processes. This study presents a 1D numerical model for bio-concrete production using urease-active calcite powder (UACP). Unlike previous models based on in-situ bacterial growth, urease is initially and homogeneously distributed by mixing UACP with sand, reducing model complexity in terms of the number of degrees of freedom. The model captures the coupled evolution of fluid flow, ureolysis-driven carbonate precipitation, and porosity–permeability reduction, with a novel conceptual formulation to limit the ureolysis rate for agreement with experiments. Parameters are calibrated using a selected quasi-1D experiment and validated against four additional setups. The model predicts whether cementation is complete or incomplete and reproduces final average porosities with errors below 7.5%. The model already captures the dominant processes governing UACP-based bio-cementation and provides a reliable basis for in-silico optimization of injection strategies and process parameters. It also serves as a foundation for further refinement and extension to multidimensional systems, supporting the development and scale-up of bio-cemented materials in geotechnical and construction applications. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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