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Record W2124324764 · doi:10.1139/t04-036

Design and laboratory verification of a physical model of sloping capillary barrier

2004· article· en· W2124324764 on OpenAlexvenueno aff
Denny Tami, Harianto Rahardjo, Eng‐Choon Leong, D. G. Fredlund

Bibliographic record

VenueCanadian Geotechnical Journal · 2004
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsCapillary actionGeotechnical engineeringComputer simulationCapillary pressureInfiltration (HVAC)Numerical analysisNumerical modelsSoil waterPore water pressureGeologyMechanicsMaterials sciencePorous mediumSoil scienceMathematicsPorosityComposite material

Abstract

fetched live from OpenAlex

A physical model was designed and constructed to study the mechanisms associated with capillary barriers for slope stabilization purposes. Prior to construction of the model, various numerical analyses were conducted to determine the optimum dimensions and appropriate soil types for the materials of the capillary barrier model. This paper is divided into three sections: the first two sections are related to the design of the model and are to obtain the optimum dimensions of the model and to investigate the range of soil properties that are most suitable for experimental studies in the laboratory; and the last section is laboratory verification of the numerical analysis where the numerical simulation results are compared with the experimental data. Based on the numerical simulation results, the physical capillary barrier model was constructed using two different combinations of soils, namely silty sand over gravelly sand and fine sand over gravelly sand. From the comparison of the numerical results and experimental data, it was found that the numerical analysis was able to simulate the experiment on the physical capillary barrier model reasonably well.Key words: physical capillary barrier model, unsaturated water flow, numerical simulation, pore-water pressure, volumetric water content, slope stability, infiltration.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.011
GPT teacher head0.193
Teacher spread0.182 · 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.

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

Citations76
Published2004
Admission routes1
Has abstractyes

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