Speaker
Description
Fluid flows in porous media play a crucial role in both natural and industrial processes, such as underground hydrogen storage for renewable energy and water-gas management in fuel cells. Intricate pore geometries drive complex, multi-scale dynamics in phenomena such as multiphase and viscoelastic flows. Accurate modeling of these flows is challenging however, as numerical simulations are computationally intensive and limited by physical uncertainties. Particle velocimetry methods, particularly Lagrangian particle tracking (LPT), enable direct measurement of complex flow patterns near pore walls using representative tracer particles, but require transparent geometries for conventional optical methods.
The penetrating power of X-rays, combined with computed tomography methods, enables non-invasive probing of internal dynamics in opaque materials. By acquiring X-ray projection images from many viewing angles, high-resolution 3D reconstructions of a sample’s interior can be generated over time, enabling the direct tracking of tracer microparticles. This approach was first demonstrated for creeping flows in opaque porous media using silver-coated hollow glass tracers (Bultreys et al., 2022) and has since provided new insights into complex 3D phenomena, such as Haines jumps in multiphase flow (Bultreys et al., 2024). Despite these advancements, the temporal resolution of 3D tomography remains constrained by long acquisition times relative to the timescales of many pore-scale flow dynamics (commonly ms to s). Consequently, artifacts produced by particle motion degrade tracking capabilities for velocities exceeding 1 µm/s, confining the method to slower and less complex flow regimes.
We address this limitation through the development of a novel tomographic reconstruction algorithm, adapting elements of current state-of-the-art LPT methods (Schanz et al., 2016). Additionally, we optimize data processing workflows and experimental setups by refining hardware, imaging settings and tracer particle selection. Our goal is to improve particle tracking time resolution while maintaining micrometer-scale measurement capabilities. We present proof-of-concept results applied to both simulated and experimentally measured datasets on slow, simple flows. These developments aim at extending the method’s applicability to fast, unsteady 3D flows, requiring increasingly complex validation to ensure robust performance.
| References | Bultreys, T. et al., 2022. X-ray tomographic micro-particle velocimetry in porous media. Physics of Fluids, 34(4), 042008. https://doi.org/10.1063/5.0088000 Bultreys, T. et al., 2024. 4D microvelocimetry reveals multiphase flow field perturbations in porous media. Proceedings of the National Academy of Sciences, 121(12), e2316723121. https://doi.org/10.1073/pnas.2316723121 Schanz, D. et al., 2016. Shake-The-Box: Lagrangian particle tracking at high particle image densities. Experiments in Fluids, 57, 70. https://doi.org/10.1007/s00348-016-2157-1 |
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| Country | Belgium |
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