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Record W1963140787 · doi:10.1139/t10-097

Intrinsic permeability of materials ranging from sand to rock-fill using natural air convection tests

2011· article· en· W1963140787 on OpenAlexafffundvenueabout
Jean Côté, Marie-Hélène Fillion, Jean‐Marie Konrad

Bibliographic record

VenueCanadian Geotechnical Journal · 2011
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEnclosureNatural convectionPermeability (electromagnetism)Geotechnical engineeringRangingConvectionAirflowGeologyAir permeability specific surfaceMaterials scienceMechanicsComposite materialThermodynamicsChemistryEngineering

Abstract

fetched live from OpenAlex

Air convection within coarse rock-fills enhances winter-time heat extraction from underlying soils. Modeling this phenomenon requires the knowledge of intrinsic permeability. This study focuses on the measurement of intrinsic permeability using natural air convection within a 1 m3 test cell. Upward heat flow conditions are applied to various specimens. Test results are analyzed using a theoretical solution of natural convection in a square enclosure. Four materials were studied, with effective particle sizes (d10) ranging from 90 to 150 mm and porosities ranging from 0.37 to 0.41. The results showed that intrinsic permeability increases with increasing d10. The experimental results were adequately predicted by the Kozeny–Carman and Chapuis equations. Only slight deviations were observed, which is considered acceptable given that these equations were developed for materials with much smaller values of d10. The experimental results of this study confirm the value of intrinsic permeability recently used in a study of natural convection within a rock-fill dam in northern Quebec, Canada.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.995
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.205
Teacher spread0.189 · 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 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

Citations35
Published2011
Admission routes4
Has abstractyes

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