The Ganglion Network Model: Evolving Trapped Phases in Porous Media
Abstract
Partially miscible ganglia trapped within porous media, spanning one or multiple pores and evolving through diffusive mass transfer, are common in subsurface (e.g., CO2 and H2 storage) and manufacturing (e.g., fuel cells) applications. We present the ganglion network model (GNM), a reduced-order method for simulating how a population of such ganglia evolves inside an arbitrary porous microstructure. GNM operates on a tree graph, the ganglion network, extracted from the pore-scale image of a given sample. Each point on the graph encodes a possible ganglion configuration in the void space, without any loss of geometric or topological complexity. The evolution of a population is modeled by representing each ganglion as a particle on the graph and tracking it according to a set of rules formulated herein. The rules capture capillary events such as pore invasion, retraction, snap-off, fragmentation, and merger. Unlike pore-network models, another graph-based modeling tool at the pore scale, GNM solves no system of equations and its cost scales with ganglion count, not domain size. We validate GNM against an image-based pore-network model in 2.5D and 3D domains with populations undergoing ripening, dissolution, and growth. We find good agreement in ganglion statistics, aggregate properties, and spatial configuration. We further argue that the ganglion network is the statistical space needed for extending kinetic theories of Ostwald ripening from single- to multi-pore ganglia, and provide an outline for how to do this. GNM opens the door to modeling other dynamics of trapped phases in porous media.
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BibTeX
@misc{mehmani2026ganglion,
title = {{The Ganglion Network Model: Evolving Trapped Phases in Porous Media}},
author = {Yashar Mehmani},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.39041},
eprint = {2609.39041},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.39041},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - The Ganglion Network Model: Evolving Trapped Phases in Porous Media
AU - Yashar Mehmani
PY - 2026
DA - 2026/09/30
PB - arXiv
DO - 10.48550/arxiv.2609.39041
UR - https://arxiv.org/abs/2609.39041
AB - Partially miscible ganglia trapped within porous media, spanning one or multiple pores and evolving through diffusive mass transfer, are common in subsurface (e.g., CO_2 and H_2 storage) and manufacturing (e.g., fuel cells) applications. We present the ganglion network model (GNM), a reduced-order method for simulating how a population of such ganglia evolves inside an arbitrary porous microstructure. GNM operates on a tree graph, the ganglion network, extracted from the pore-scale image of a given sample. Each point on the graph encodes a possible ganglion configuration in the void space, without any loss of geometric or topological complexity. The evolution of a population is modeled by representing each ganglion as a particle on the graph and tracking it according to a set of rules formulated herein. The rules capture capillary events such as pore invasion, retraction, snap-off, fragmentation, and merger. Unlike pore-network models, another graph-based modeling tool at the pore scale, GNM solves no system of equations and its cost scales with ganglion count, not domain size. We validate GNM against an image-based pore-network model in 2.5D and 3D domains with populations undergoing ripening, dissolution, and growth. We find good agreement in ganglion statistics, aggregate properties, and spatial configuration. We further argue that the ganglion network is the statistical space needed for extending kinetic theories of Ostwald ripening from single- to multi-pore ganglia, and provide an outline for how to do this. GNM opens the door to modeling other dynamics of trapped phases in porous media.
ER -