A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models.
This paper deals with the computational modeling of biological dynamics in soil using an exact micro-scale pore space description from 3D Computed Tomography (CT) images. Within this context, computational costs and storage requirements constitute critical factors for running simulations on large da...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0313853 |
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| author | Mouad Klai Olivier Monga Mohamed Soufiane Jouini Valérie Pot |
| author_facet | Mouad Klai Olivier Monga Mohamed Soufiane Jouini Valérie Pot |
| author_sort | Mouad Klai |
| collection | DOAJ |
| description | This paper deals with the computational modeling of biological dynamics in soil using an exact micro-scale pore space description from 3D Computed Tomography (CT) images. Within this context, computational costs and storage requirements constitute critical factors for running simulations on large datasets over extended periods. In this research, we represent the pore space by a graph of voxels (Voxel Graph-Based Approach, VGA) and model transport in fully saturated conditions (two-phase system) using Fick's law and coupled diffusion with biodegradation processes to simulate microbial decomposition in soil. To significantly decrease the computational time of our approach, the diffusion model is solved by means of Euler discretization schemes, along with parallelization strategies. We also tested several numerical strategies, including implicit, explicit, synchronous, and asynchronous schemes. To validate our VGA, we compare it with LBioS, a 3D model that integrates diffusion (via the Lattice Boltzmann method) with biodegradation, and Mosaic, a Pore Network Geometrical Modelling (PNGM) which represents the pore space using geometrical primitives. Our method yields result similar to those of LBioS in a quarter of the computing time. While slower than Mosaic, it is more accurate and requires no calibration. Additionally, we show that our approach can improve PNGM-based simulations by using a machine-learning approach to approximate diffusional conductance coefficients. |
| format | Article |
| id | doaj-art-b61883cbbc7f4ed7a3fa14683caeaf06 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-b61883cbbc7f4ed7a3fa14683caeaf062025-08-20T01:50:30ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01203e031385310.1371/journal.pone.0313853A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models.Mouad KlaiOlivier MongaMohamed Soufiane JouiniValérie PotThis paper deals with the computational modeling of biological dynamics in soil using an exact micro-scale pore space description from 3D Computed Tomography (CT) images. Within this context, computational costs and storage requirements constitute critical factors for running simulations on large datasets over extended periods. In this research, we represent the pore space by a graph of voxels (Voxel Graph-Based Approach, VGA) and model transport in fully saturated conditions (two-phase system) using Fick's law and coupled diffusion with biodegradation processes to simulate microbial decomposition in soil. To significantly decrease the computational time of our approach, the diffusion model is solved by means of Euler discretization schemes, along with parallelization strategies. We also tested several numerical strategies, including implicit, explicit, synchronous, and asynchronous schemes. To validate our VGA, we compare it with LBioS, a 3D model that integrates diffusion (via the Lattice Boltzmann method) with biodegradation, and Mosaic, a Pore Network Geometrical Modelling (PNGM) which represents the pore space using geometrical primitives. Our method yields result similar to those of LBioS in a quarter of the computing time. While slower than Mosaic, it is more accurate and requires no calibration. Additionally, we show that our approach can improve PNGM-based simulations by using a machine-learning approach to approximate diffusional conductance coefficients.https://doi.org/10.1371/journal.pone.0313853 |
| spellingShingle | Mouad Klai Olivier Monga Mohamed Soufiane Jouini Valérie Pot A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. PLoS ONE |
| title | A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. |
| title_full | A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. |
| title_fullStr | A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. |
| title_full_unstemmed | A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. |
| title_short | A voxel-based approach for simulating microbial decomposition in soil: Comparison with LBM and improvement of morphological models. |
| title_sort | voxel based approach for simulating microbial decomposition in soil comparison with lbm and improvement of morphological models |
| url | https://doi.org/10.1371/journal.pone.0313853 |
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