FLU-DYNNANAAOCBSep 24, 2015

Biofilm growth in porous media: experiments, computational modeling at the porescale, and upscaling

arXiv:1510.0121899 citations
Originality Synthesis-oriented
AI Analysis

For researchers studying biofilm effects in porous media, this work provides a validated modeling framework, though it is incremental as it combines existing methods.

This study combines imaging, experiments, and numerical simulations to model biofilm growth in porous media, showing that the computational model reproduces observed morphologies and upscaled conductivities match experimental hydraulic properties.

Biofilm growth changes many physical properties of porous media such as porosity, permeability and mass transport parameters. The growth depends on various environmental conditions, and in particular, on flow rates. Modeling the evolution of such properties is difficult both at the porescale where the phase morphology can be distinguished, as well as during upscaling to the corescale effective properties. Experimental data on biofilm growth is also limited because its collection can interfere with the growth, while imaging itself presents challenges. In this paper we combine insight from imaging, experiments, and numerical simulations and visualization. The experimental dataset is based on glass beads domain inoculated by biomass which is subjected to various flow conditions promoting the growth of biomass and the appearance of a biofilm phase. The domain is imaged and the imaging data is used directly by a computational model for flow and transport. The results of the computational flow model are upscaled to produce conductivities which compare well with the experimentally obtained hydraulic properties of the medium. The flow model is also coupled to a newly developed biomass--nutrient growth model, and the model reproduces morphologies qualitatively similar to those observed in the experiment.

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