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Record W2143250913 · doi:10.1139/t09-050

Analyses of water diversion along inclined covers with capillary barrier effects

2009· article· en· W2143250913 on OpenAlexafffundvenue
Michel Aubertin, E. Cifuentes, Sénami Aurore Apithy, Bruno Bussière, John Molson, Robert P. Chapuis

Bibliographic record

VenueCanadian Geotechnical Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversité LavalPolytechnique MontréalUniversité du Québec en Abitibi-Témiscamingue
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCapillary actionGeotechnical engineeringInfiltration (HVAC)Water diversionGroundwater rechargeEnvironmental scienceCover (algebra)GeologyMaterials scienceEngineeringGroundwaterComposite material

Abstract

fetched live from OpenAlex

Various types of cover systems can be used to control water infiltration into waste disposal sites. One promising option is to combine different types of soil to create a layered cover with capillary barrier effects (CCBE). A CCBE basically involves the placement of a relatively fine-grained soil, which acts as a water-retention layer, over a coarser capillary break material. On slopes, a CCBE promotes lateral water diversion. Inclined CCBEs, however, are relatively complex, as their behaviour is influenced by numerous factors. In this paper, the authors present the key results obtained from a numerical investigation into the response of steeply inclined CCBEs. The study evaluates the behaviour of covers under dry and humid climatic conditions. After a review of the physical processes and background studies, the paper presents simulation results that demonstrate the effect of key factors on the diversion length of covers, including layer thicknesses, material properties, and recharge rates. The results shown here indicate that increasing the thickness of the cover may improve its efficiency, but only up to a certain maximum beyond which the gain becomes minimal. These results should be of help to those involved in the design of inclined CCBEs.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score0.382

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 head0.007
GPT teacher head0.207
Teacher spread0.200 · 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 designBench or experimental
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

Citations120
Published2009
Admission routes3
Has abstractyes

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