Numerical study of Darcy's law of yield stress fluids on a deep tree-like network

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Autori principali: Munier, Stéphane, Rosso, Alberto
Natura: Preprint
Pubblicazione: 2024
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author Munier, Stéphane
Rosso, Alberto
author_facet Munier, Stéphane
Rosso, Alberto
contents Understanding the flow dynamics of yield stress fluids in porous media presents a substantial challenge. Both experiments and extensive numerical simulations frequently show a non-linear relationship between the flow rate and the pressure gradient, deviating from the traditional Darcy law. In this article, we consider a tree-like porous structure and utilize an exact mapping with the directed polymer (DP) with disordered bond energies on the Cayley tree. Specifically, we adapt an algorithm recently introduced by Brunet et al. [Europhys. Lett. 131, 40002 (2020)] to simulate exactly the tip region of branching random walks with the help of a spinal decomposition, to accurately compute the flow on extensive trees with several thousand generations. Our results confirm the asymptotic predictions proposed by Schimmenti et al. [Phys. Rev. E 108, L023102 (2023)], tested therein only for moderate trees of about 20 generations.
format Preprint
id arxiv_https___arxiv_org_abs_2409_03480
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Numerical study of Darcy's law of yield stress fluids on a deep tree-like network
Munier, Stéphane
Rosso, Alberto
Disordered Systems and Neural Networks
Understanding the flow dynamics of yield stress fluids in porous media presents a substantial challenge. Both experiments and extensive numerical simulations frequently show a non-linear relationship between the flow rate and the pressure gradient, deviating from the traditional Darcy law. In this article, we consider a tree-like porous structure and utilize an exact mapping with the directed polymer (DP) with disordered bond energies on the Cayley tree. Specifically, we adapt an algorithm recently introduced by Brunet et al. [Europhys. Lett. 131, 40002 (2020)] to simulate exactly the tip region of branching random walks with the help of a spinal decomposition, to accurately compute the flow on extensive trees with several thousand generations. Our results confirm the asymptotic predictions proposed by Schimmenti et al. [Phys. Rev. E 108, L023102 (2023)], tested therein only for moderate trees of about 20 generations.
title Numerical study of Darcy's law of yield stress fluids on a deep tree-like network
topic Disordered Systems and Neural Networks
url https://arxiv.org/abs/2409.03480