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Record W2128006615 · doi:10.1139/t07-065

A capillary-tube model for two-phase transient flow through bentonite materials

2007· article· en· W2128006615 on OpenAlexafffundvenue
Greg Siemens, James Blatz, Douglas Ruth

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsRoyal Military College of CanadaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaAtomic Energy of Canada Limited
KeywordsHydraulic conductivityCapillary actionGeotechnical engineeringBentoniteMechanicsMaterials scienceInfiltration (HVAC)Tube (container)Flow (mathematics)SwellPorous mediumPlasticityPorosityGeologySoil waterSoil scienceComposite materialPhysics

Abstract

fetched live from OpenAlex

Swelling mechanisms occurring on the pore scale or at the molecular level of high plasticity, unsaturated soils often control macroscopic behaviour. In this paper, a new capillary tube model is proposed. The model is used to represent laboratory-scale infiltration tests on a bentonite-rich soil. The goal is to develop a greater understanding of bulk behaviour by closely examining microscopic behaviour. A decrease in hydraulic conductivity with increasing water content has been observed in laboratory studies on flow through shrink–swell materials. The proposed mechanism causing a decrease in conductivity is a change in pore-size distribution. The unique feature of the new capillary-tube model is that, as water flows down the tube, the tube’s cross-sectional area contracts to restrict flow, thus representing the change in pore-size distribution observed in the physical tests. Flow data from the capillary tube are used to model the laboratory results, and new insight is gained into bulk flow behaviour. Finally, a comparison with a three-dimensional network model for bentonite-coated sand mixtures is presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.012
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.276
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations3
Published2007
Admission routes3
Has abstractyes

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