Preprints
https://doi.org/10.5194/egusphere-2022-1016
https://doi.org/10.5194/egusphere-2022-1016
 
04 Oct 2022
04 Oct 2022
Status: this preprint is open for discussion.

CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics

Heewon Jung1,2, Hyun-Seob Song3, and Christof Meile1 Heewon Jung et al.
  • 1Department of Marine Sciences, University of Georgia, Athens, GA 30602, USA
  • 2Department of Geological Sciences, Chungnam National University, Daejeon 34134, South Korea
  • 3Department of Biological Systems Engineering, Department of Food Science and Technology, Nebraska Food for Health Center, University of Nebraska-Lincoln, Lincoln, NE 68583, USA

Abstract. Microbial activity and chemical reactions in porous media depend on the local conditions at the pore scale and can involve complex feedback with fluid flow and mass transport. We present a modeling framework that quantitatively accounts for the interactions between the bio(geo)chemical and physical processes, and that can integrate genome-scale microbial metabolic information into a dynamically changing, spatially explicit representation of environmental conditions. The model couples a Lattice-Boltzmann implementation of Navier-Stokes (flow) and advection-diffusion-reaction (mass conservation) equations. Reaction formulations can include both kinetic rate expressions and flux balance analyses, thereby integrating reactive transport modeling and systems biology. We also show that the use of surrogate models such as neural network representations of in silico cell models can speed up computations significantly, facilitating applications to complex environmental systems. Parallelization enables simulations that resolve heterogeneity at multiple scales, and a cellular automata module provides additional capabilities to simulate biofilm dynamics. The code thus constitutes a platform suitable for a range of environmental, engineering and – potentially – medical applications, in particular ones that involve the simulation of microbial dynamics.

Heewon Jung et al.

Status: open (until 29 Nov 2022)

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  • RC1: 'Comment on egusphere-2022-1016', Anonymous Referee #1, 09 Nov 2022 reply

Heewon Jung et al.

Model code and software

CompLaB v1.0 Heewon Jung and Christof Meile https://doi.org/10.5281/zenodo.7095756

Heewon Jung et al.

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Short summary
Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modelling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.