Darcy's law of yield stress fluids on a treelike network

Fuente: arXiv
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Hauptverfasser: Schimmenti, Vincenzo Maria, Lanza, Federico, Hansen, Alex, Franz, Silvio, Rosso, Alberto, Talon, Laurent, De Luca, Andrea
Format: Preprint
Veröffentlicht: 2022
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author Schimmenti, Vincenzo Maria
Lanza, Federico
Hansen, Alex
Franz, Silvio
Rosso, Alberto
Talon, Laurent
De Luca, Andrea
author_facet Schimmenti, Vincenzo Maria
Lanza, Federico
Hansen, Alex
Franz, Silvio
Rosso, Alberto
Talon, Laurent
De Luca, Andrea
contents Understanding the flow of yield stress fluids in porous media is a major challenge. In particular, experiments and extensive numerical simulations report a non-linear Darcy law as a function of the pressure gradient. In this letter, we consider a tree-like porous structure for which the problem of the flow can be resolved exactly thanks to a mapping with the directed polymer (DP) with disordered bond energies on the Cayley tree. Our results confirm the non-linear behavior of the flow and expresses its full pressure-dependence via the density of low-energy paths of DP restricted to vanishing overlap. These universal predictions are confirmed by extensive numerical simulations.
format Preprint
id arxiv_https___arxiv_org_abs_2208_06048
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Darcy's law of yield stress fluids on a treelike network
Schimmenti, Vincenzo Maria
Lanza, Federico
Hansen, Alex
Franz, Silvio
Rosso, Alberto
Talon, Laurent
De Luca, Andrea
Soft Condensed Matter
Disordered Systems and Neural Networks
Understanding the flow of yield stress fluids in porous media is a major challenge. In particular, experiments and extensive numerical simulations report a non-linear Darcy law as a function of the pressure gradient. In this letter, we consider a tree-like porous structure for which the problem of the flow can be resolved exactly thanks to a mapping with the directed polymer (DP) with disordered bond energies on the Cayley tree. Our results confirm the non-linear behavior of the flow and expresses its full pressure-dependence via the density of low-energy paths of DP restricted to vanishing overlap. These universal predictions are confirmed by extensive numerical simulations.
title Darcy's law of yield stress fluids on a treelike network
topic Soft Condensed Matter
Disordered Systems and Neural Networks
url https://arxiv.org/abs/2208.06048