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Habilitation À Diriger Des Recherches Year : 2022

Computational Microfluidics for Geosciences

Microfluidique numérique pour les géosciences


Computational microfluidics for geosciences is an emerging scientific discipline for investigating complex mechanisms in geological porous media. It allows for a finescale description of the coupled processes that occur in the soils and the subsurface employing advanced modelling tools (e.g. Computational Fluid Dynamics, Reactive Transport Modelling). In a scientific strategy relying on a cascade of scales nested within each other, computational microfluidics is, therefore, an essential tool to bridge the gap between spatial scales and guide the derivation of field-scale models rooted in a correct description of the elementary physical principles. It is a natural companion of lab-scale experiments in well-controlled environments by providing high-resolution mapping of pressure and velocity profiles, solute concentration, and mineral distribution that are not easily measurable experimentally. Computational microfluidics is also a powerful tool to perform sensitivity analysis for identifying the key parameters of the underlying processes or to explore ranges of conditions including pressure and temperature that are difficult to reach in the laboratory without dedicated equipment. In this thesis, we review the state-of-the-art computational microfluidics as well as the author’s contributions. They include pore-scale modelling of immiscible twophase flow, mass transfer across interfaces, and geochemical processes (e.g. mineral dissolution/precipitation). We also introduce the concept of micro-continuum approaches for solving coupled processes in computational microfluidics and its usage for image-based simulations. The thesis outlines the open challenges, the current trends, and future directions in the field.
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Dates and versions

tel-03840078 , version 1 (04-11-2022)


  • HAL Id : tel-03840078 , version 1


Cyprien Soulaine. Computational Microfluidics for Geosciences. Geophysics [physics.geo-ph]. Université d'Orléans, 2022. ⟨tel-03840078⟩
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