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Record W2549493143

Effect of vertical stresses on GCL thermal conductivity

2014· article· en· W2549493143 on OpenAlexaff
Mohammad Ali, Rao Martand Singh, Abdelmalek Bouazza, Will P. Gates, R. Kerry Rowe

Bibliographic record

Venue7th International Congress on Environmental Geotechnics : iceg2014 · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeomembraneGeosynthetic clay linerThermal conductivityMoistureGeotechnical engineeringMaterials scienceComposite numberThermalWater contentComposite materialEnvironmental scienceHydraulic conductivityGeologySoil scienceSoil waterMeteorology
DOInot available

Abstract

fetched live from OpenAlex

Geomembrane (GMB) and geosynthetic clay liner (GCL) are frequently used together to form composite liners in waste containment facilities. Biodegradation of organic compounds, hydration of ash, various ore extraction processes and entrapped solar radiation, amongst others, have been reported to generate heat in these types of facilities. This creates a thermal gradient across the lining system which can potentially impact the long-term lining system performance. Heat flow across a composite lining system is controlled by the thermal conductivities of its components. This paper explores the effect of vertical stress on the thermal conductivity of a GCL at two different moisture contents. It has been observed that for both moisture contents, the increase in vertical stress gives rise to thermal conductivity which can be attributed to improved contact between solids and raised volumetric moisture content.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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Same venue7th International Congress on Environmental Geotechnics : iceg2014Same topicLandfill Environmental Impact StudiesFrench-language works237,207