Speaker
Description
Particle transport and retention in porous media are governed by a complex interplay between fluid dynamics, particle properties, and pore geometry, leading to inherently stochastic clogging behaviors. In particular, hydrodynamic particle bridging---where suspended particles form stable arches that block pore constrictions---remains poorly captured by conventional pore-network models. In this work, we combine high-fidelity numerical simulations, stochastic modeling, and pore-network upscaling to investigate particle bridging from the single pore to the network scale. At the scale of a single pore, a coupled CFD–DEM approach is employed to analyze particle transport through constricted channels, systematically varying constriction angle, particle-to-constriction size ratio, flow rate, concentration, and geometric smoothness [1,2]. The simulations reveal that clogging is governed by the discrete formation of particle arches, characterized by the average number of particles escaping a constriction before blockage. This number decreases with increasing particle concentration and constriction angle, is weakly dependent on flow rate within the Stokes regime, and exhibits step-wise variations closely linked to the particle-to-constriction size ratio. Sharper constrictions promote more frequent and stable bridging events than smoother geometries. Based on these findings, a stochastic probability law for hydrodynamic bridging is developed and embedded into a probabilistic pore-network model [3]. The model is calibrated using the CFD–DEM results and validated against microfluidic experiments conducted in heterogeneous micromodels representative of porous rock structures. Our framework successfully reproduces experimental trends in clogging dynamics and permeability decline across a wide range of operating conditions. This multiscale approach extends the predictive capability of pore-network models by explicitly accounting for hydrodynamic bridging alongside sieving and aggregation mechanisms.
| References | 10.1016/j.jcp.2024.113540; 10.1016/j.advwatres.2025.105158 |
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| Country | France |
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