Evaluation of Spatial Distribution of Hydraulic Conductivity Using Effective Porosity Data

Ahuja, L. R.; Cassel, D. K.; Bruce, R. R.; Barnes, Brian B.

doi:10.1097/00010694-198912000-00002

Cited by 174 publications

(106 citation statements)

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“…Only in specialized cases, such as the Kozeny equation are the associated coefficients dimensionless. Similar functions to predict permeability having coefficients with dimensions are already present in the literature [Katz and Thompson, 1986;Ahuja et al, 1989;Rodriguez et al, 2004;Costa, 2006].…”

Section: Discussionsupporting

confidence: 52%

“…Lemaitre and Adler [1990] indicate that permeability behaves like a power of porosity near the percolation limit (the value of porosity below which there are no continuous pore channels through one of their realizations) of the random porous media they construct. Other variants of the Kozeny equation that depend solely on porosity have been proposed by Nielsen et al [1984] and Ahuja et al [1989].…”

Section: Alternatives To Kozeny Equationmentioning

confidence: 99%

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Pedotransfer functions for permeability: A computational study at pore scales

Hyman

Smolarkiewicz

Winter

2013

Water Resources Research

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[1] Three phenomenological power law models for the permeability of porous media are derived from computational experiments with flow through explicit pore spaces. The pore spaces are represented by three-dimensional pore networks in 63 virtual porous media along with 15 physical pore networks. The power laws relate permeability to (i) porosity, (ii) squared mean hydraulic radius of pores, and (iii) their product. Their performance is compared to estimates derived via the Kozeny equation, which also uses the product of porosity with squared mean hydraulic pore radius to estimate permeability. The power laws provide tighter estimates than the Kozeny equation even after adjusting for the extra parameter they each require. The best fit is with the power law based on the Kozeny predictor, that is, the product of porosity with the square of mean hydraulic pore radius.Citation: Hyman, J. D., P. K. Smolarkiewicz, and C. L. Winter (2013), Pedotransfer functions for permeability: A computational study at pore scales, Water Resour.

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Section: Discussionsupporting

confidence: 52%

Section: Alternatives To Kozeny Equationmentioning

confidence: 99%

Pedotransfer functions for permeability: A computational study at pore scales

Hyman

Smolarkiewicz

Winter

2013

Water Resources Research

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“…However, Carman (1939) expected that t would only have a narrow range of values. The relationship between soil porosity and hydraulic conductivity is often described by an empirical power law (Ahuja et al, 1989;Aminrun et al, 2004;Green et al, 2003):…”

Section: Introductionmentioning

confidence: 99%

“…In fact the functional relationship is different to the one described by Carman (1939). Typically n is assumed have a value between 4 and 5, and B may vary with soil type (Ahuja et al, 1989). The approach recognises that the hydraulic conductivity of saturated soil depends mainly on the larger voids (i.e.…”

Section: Introductionmentioning

confidence: 99%

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The effect of compaction and shear deformation of saturated soil on hydraulic conductivity

Whalley

Matthews

Ferraris

2012

Soil and Tillage Research

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Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

et al. 2018

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We image synthetic porous rocks of varied porosity and pore size by micro–computed tomography with pore‐scale finite element modeling representing the pore space for single‐phase fluid flow. The simulations quantify the key features of microscale flow behavior in the synthetic cores. The smaller the permeability, the greater the critical pressure gradient required for the onset of non‐Darcy fluid flows, and the easier the emergence of nonlinear seepage within the tested cores. The relationship between permeability and porosity from different methods shows a power law correlation with pressure. Structural heterogeneity and anisotropy of the pore systems are shown to have a significant impact on transport through the three‐dimensional pore model—exhibiting irregular flow fields. The simulated permeabilities of the tested cores vary by a factor of 2–5 depending on the fluid flow directions. With the increase of flow seepage velocity, the flow regime deviates from Darcy linear relationship and non‐Darcy behavior (inertia) leads to a reduction in the effective permeability of the core. Both experiments and modeling demonstrate that the larger the porosity and permeability, the stronger the non‐linear phenomenon of the seepage within the pore space. A method is proposed to estimate the non‐Darcy coefficient β based on simulation results, which provides a good prediction for all the tested cores. A new equation is established to predict the transition of flow patterns as a function of the apparent permeability K* and Reynolds number Re. The K*‐Re model provides a theoretical approach to dynamically describe the transition from Darcy to Forchheimer flow.

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Evaluation of Spatial Distribution of Hydraulic Conductivity Using Effective Porosity Data

Cited by 174 publications

References 0 publications

Pedotransfer functions for permeability: A computational study at pore scales

Pedotransfer functions for permeability: A computational study at pore scales

The effect of compaction and shear deformation of saturated soil on hydraulic conductivity

Pore‐Scale Reconstruction and Simulation of Non‐Darcy Flow in Synthetic Porous Rocks

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