Preprints
https://doi.org/10.5194/egusphere-2022-1016
https://doi.org/10.5194/egusphere-2022-1016
04 Oct 2022
 | 04 Oct 2022

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

Heewon Jung, Hyun-Seob Song, and Christof Meile

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.

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Journal article(s) based on this preprint

27 Mar 2023
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023,https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Heewon Jung, Hyun-Seob Song, and Christof Meile

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1016', Anonymous Referee #1, 09 Nov 2022
  • RC2: 'Comment on egusphere-2022-1016', Maria De La Fuente Ruiz, 19 Dec 2022
  • AC1: 'Comment on egusphere-2022-1016', Christof Meile, 14 Jan 2023

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-1016', Anonymous Referee #1, 09 Nov 2022
  • RC2: 'Comment on egusphere-2022-1016', Maria De La Fuente Ruiz, 19 Dec 2022
  • AC1: 'Comment on egusphere-2022-1016', Christof Meile, 14 Jan 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Christof Meile on behalf of the Authors (14 Jan 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (23 Feb 2023) by Sandra Arndt
AR by Christof Meile on behalf of the Authors (02 Mar 2023)  Manuscript 

Journal article(s) based on this preprint

27 Mar 2023
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023,https://doi.org/10.5194/gmd-16-1683-2023, 2023
Short summary
Heewon Jung, Hyun-Seob Song, and Christof Meile

Model code and software

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

Heewon Jung, Hyun-Seob Song, and Christof Meile

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Latest update: 04 Sep 2024
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

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.