A Mathematical Model and Analytical Solution for the Fixation of Bacteria in Biogrout

Wijngaarden, W. K. van; Vermolen, F.J.; Meurs, G. A. M. van; Vuik, C.

doi:10.1007/s11242-011-9937-0

Cited by 31 publications

(10 citation statements)

References 21 publications

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“…In van Wijngaarden (2013), it has been shown that small deviations in the flow equations have a minor effect on the final calcium carbonate content.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

A Reactive Transport Model for Biogrout Compared to Experimental Data

et al. 2015

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Biogrout is a method for reinforcement of granular soil. In the Biogrout process, calcium carbonate is produced. This solid connects the grains, and therefore the strength of the soil is increased. The calcium carbonate is formed with the use of micro-organisms. Experiments and numerical simulations have been performed to demonstrate the process under various conditions. In this paper, it has been examined whether a reactive transport model can be used to describe a Biogrout experiment that was performed in a column with a length of 5 m. Four different models for the course of the reaction rate are considered. The concentration of micro-organisms and the reaction rate are fine-tuned in order to find a description of the experiment that is a best fit for the particular model. This is done by minimizing the error between the experimental and numerical results for the concentration of calcium carbonate and the by-product of the reaction. List of symbolsInjected concentration of micro-organisms (normalized) (1) S bac Ratio of micro-organisms that is fixated (with respect to the injected concentration) (1)

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“…In van Wijngaarden (2013), it has been shown that small deviations in the flow equations have a minor effect on the final calcium carbonate content.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

A Reactive Transport Model for Biogrout Compared to Experimental Data

et al. 2015

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“… The downward infiltration of cementation solution has little dispersion and diffusion through the column (Van Wijngaarden et al 2012).…”

Section: Assumptions Of Mathematical Modelmentioning

confidence: 99%

Upscaling Effects of Soil Improvement by Microbially Induced Calcite Precipitation by Surface Percolation

Cheng

Cord‐Ruwisch

2014

Geomicrobiology Journal

170

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This study has contributed to the technology of soil stabilization via biocementation based on microbially induced calcite precipitation. The newly described method of insitu soil stabilization by surface percolation to dry soil under free draining environment is tested for its up-scaling potential. 2 m columns of one-dimensional trials indicated that repeated treatments of fine sand (< 0.3 mm) could lead to clogging closed at the injection end, resulting in limited cementation depth of less than 1 m. This clogging problem was not observed in 2 m coarse (> 0.5 mm) sand columns, allowing strength varying between 850 to 2067 kPa along the entire 2 m depth. Three-dimensional fine sand cementation trials indicated that relatively homogenous cementation in the horizontal direction could be achieved with 80% of cemented sand cementing to a strength between 2 to 2.5 MPa and to a depth of 20 cm.A simple mathematical model elucidated that the cementation depth was dependent on the infiltration rate of the cementation solution and the in-situ urease activity. The model also correctly predicted that repeated treatments would enhance clogging close to the injection point. Both experimental and simulated results suggested that the surface percolation technology was more applicable for coarse sand.

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“…These models describe bacterial growth and predict the changes in the characteristics of the porous media like the permeability and porosity [22]. Among bacterial growth models in porous media, there are the Darcy continuum models [24,29], bacterially based models [16], Lattice Boltzmann-based simulations [9,17], and pore network models (PNM) [6,8,18,21,23,26,28]. The secretion of extracellular polymeric substances (EPS) by bacterial population causes the formation and growth of biofilm on the walls of the porous media.…”

Section: Introductionmentioning

confidence: 99%

Conditions for upscalability of bioclogging in pore network models

2018

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In this work, we model the biofilm growth at the microscale using a rectangular pore network model in 2D and a cubic network in 3D. For the 2D network, we study the effects of bioclogging on porosity and permeability when we change parameters like the number of nodes in the network, the network size, and the concentration of nutrients at the inlet. We use a 3D cubic network to study the influence of the number of nodes in the z direction on the biofilm growth and on upscalability. We show that the biofilm can grow uniformly or heterogeneously through the network. Using these results, we determine the conditions for upscalability of bioclogging for rectangular and cubic networks. If there is uniform biofilm growth, there is a unique relation between permeability and porosity, K ∼ φ 2 , this relation does not depend on the volume of the network, therefore the system is upscalable. However, if there is preferential biofilm growth, the porosity-permeability relation is not uniquely defined, hence upscalability is not possible. The Damköhler number is used to determine when upscalability is possible. If the Damköhler number is less than 10 1 , the biofilm grows uniformly and therefore the system is upscalable. However, if the Damköhler number is greater than 10 3 , the biofilm growth exhibits a deviation from uniform biofilm growth and heterogeneous growth is observed, therefore upscalability is not possible. There is a transition from uniform growth to preferential growth if the Damköhler number is between 10 1 and 10 3 .

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A Mathematical Model and Analytical Solution for the Fixation of Bacteria in Biogrout

Cited by 31 publications

References 21 publications

A Reactive Transport Model for Biogrout Compared to Experimental Data

A Reactive Transport Model for Biogrout Compared to Experimental Data

Upscaling Effects of Soil Improvement by Microbially Induced Calcite Precipitation by Surface Percolation

Conditions for upscalability of bioclogging in pore network models

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