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Record W2052757722 · doi:10.1139/t02-088

A model for strain-induced permeability anisotropy in deformable granular media

2003· article· en· W2052757722 on OpenAlexvenueno aff
Ron CK Wong

Bibliographic record

VenueCanadian Geotechnical Journal · 2003
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
FundersU.S. Department of Energy
KeywordsTortuosityPermeability (electromagnetism)AnisotropyPorous mediumMechanicsShearing (physics)Materials scienceGeotechnical engineeringPorosityLateral strainGeologyPhysicsOpticsChemistry

Abstract

fetched live from OpenAlex

In a deformable granular medium, shear deformation results in a change in pore volume, thereby causing a change in permeability. In previous studies, it is assumed that the change in absolute permeability is a function of porosity or volumetric strain, which in turn is a function of the mean or minimum effective stress. In such semi-empirical correlations, the changes in permeability are equal in all directions, even though the changes in strains are different in each direction. This paper proposes a new model accounting for permeability anisotropy induced by strains in deformable porous media. This model is derived from the well-known phenomenological Kozeny–Carman equation with some modifications. It was proven that tensor parameters embedded in the Kozeny–Carman equation (hydraulic radius and tortuosity of flow channels) can be expressed in terms of principal strains for granular assemblies of idealized packings. This approach allows one to formulate the evolution of changes in permeability in three directions under continuous shearing. The model explicitly states that the permeability changes are anisotropic, dependent on the induced strains. A comparison between experimental data and predicted results is presented to show the validity of the proposed model.Key words: strain-induced anisotropy, permeability, shear dilation, principal strain, tortuosity, tensor.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.208
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations46
Published2003
Admission routes1
Has abstractyes

Explore more

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