Fractal permeability model for power-law fluids in embedded tree-like branching networks based on the fractional-derivative theory

The investigation of permeability in tree-like branching networks has attracted widespread attention. However, most studies about fractal models for predicting permeability in tree-like branching networks include empirical constants. This paper investigates the flow characteristics of power-law fluids in the dual porosity model of porous media in embedded tree-like branching networks. Considering the inherent properties of power-law fluids, non-Newtonian behavior effects, and fractal properties of porous media, a power-law fluids rheological equation is introduced based on the fractional-derivative theory and fractal theory. Then, an analytical formula for predicting the effective permeability of power-law fluids in dual porous media is derived. This analytical formula indicates the influences of fractal dimensions and structural parameters on permeability. With increasing length ratio, bifurcation series, and bifurcation angle, as well as decreasing power-law exponent and diameter ratio, the effective permeability decreases to varying degrees. The derived analytical model does not include empirical constants and is consistent with the non-Newtonian properties of power-law fluids, indicating that the model is an effective method for describing the flow process of complex non-Newtonian fluids in porous media in natural systems and engineering. Therefore, this study is of great significance to derive analytical solutions for the permeability of power-law fluids in embedded tree-like bifurcation networks.

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Publication Details

Journal
Physics of Fluids
Published
2024-09-01
DOI
https://doi.org/10.1063/5.0231819
Citations
31
Primary Topic
Heat Transfer and Optimization
Type
article
Field-Weighted Citation Impact
6.59
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article

Fractal permeability model for power-law fluids in embedded tree-like branching networks based on the fractional-derivative theory

Boqi Xiao, GONGBO LONG, Lei Chen, JIACHENG ZHANG et al.
31 citations
Physics of Fluids
Heat Transfer and Optimization
6.59
article

Fractal permeability model for power-law fluids in embedded tree-like branching networks based on the fractional-derivative theory

Boqi Xiao, GONGBO LONG, Lei Chen, JIACHENG ZHANG, Jiyin Cao, Huan Zhou, Jun Gao
article en
31 citations

Abstract

The investigation of permeability in tree-like branching networks has attracted widespread attention. However, most studies about fractal models for predicting permeability in tree-like branching networks include empirical constants. This paper investigates the flow characteristics of power-law fluids in the dual porosity model of porous media in embedded tree-like branching networks. Considering the inherent properties of power-law fluids, non-Newtonian behavior effects, and fractal properties of porous media, a power-law fluids rheological equation is introduced based on the fractional-derivative theory and fractal theory. Then, an analytical formula for predicting the effective permeability of power-law fluids in dual porous media is derived. This analytical formula indicates the influences of fractal dimensions and structural parameters on permeability. With increasing length ratio, bifurcation series, and bifurcation angle, as well as decreasing power-law exponent and diameter ratio, the effective permeability decreases to varying degrees. The derived analytical model does not include empirical constants and is consistent with the non-Newtonian properties of power-law fluids, indicating that the model is an effective method for describing the flow process of complex non-Newtonian fluids in porous media in natural systems and engineering. Therefore, this study is of great significance to derive analytical solutions for the permeability of power-law fluids in embedded tree-like bifurcation networks.

Physics of FluidsVol. 36(9)
Wuhan Business University (CN), Wuhan Institute of Technology (CN)
Peace, Justice and strong institutions
Openalex Percentile: Top 2%
Heat Transfer and Optimization
6.59
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