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Record W4213189187 · doi:10.1680/jgein.21.00023a

Performance of GCLs after long-term wet–dry cycles under a defect in GMB in a landfill

2022· article· en· W4213189187 on OpenAlexaff
R. Kerry Rowe, Seba Hamdan

Bibliographic record

VenueGeosynthetics International · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsGeosynthetic clay linerGeosyntheticsGeotextileLeachateBentoniteHydraulic conductivityGeomembraneGeotechnical engineeringWettingMaterials scienceGeogridComposite materialEnvironmental scienceChemistryGeologySoil waterSoil scienceEnvironmental chemistry

Abstract

fetched live from OpenAlex

Two geosynthetic clay liners (GCLs) with sodium bentonite and three GCLs with polymer-amended bentonite were subjected to wet–dry cycles selected to simulate the conditions to which a GCL on an 18° slope might be subjected: for a GCL below an exposed geomembrane wrinkle with a hole. The wetting involved water flowing over the GCL for 8 h each cycle. Three drying cycles (0.67, 7, and 14 days) were examined. After 12–18 months of wet–dry cycles, the samples were X-rayed to identify representative specimens for testing. The changes in the hydraulic conductivity, k, of the GCLs were obtained when permeated with two synthetic municipal solid waste leachates at an applied head of 0.35 m for a range of effective stresses (3–150 kPa). The results showed an up to four orders of magnitude difference in k depending on applied stress and RMD of the leachate permeant. The effects of the number and the duration of the wet–dry cycles, the GCL mass per unit area, presence/absence of polymer modification, the carrier geotextile, the number and the size of the needle-punched bundles, and the bundle thermal treatment are discussed.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.994

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.009
GPT teacher head0.233
Teacher spread0.224 · 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.

Study designObservational
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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGeosynthetics InternationalSame topicLandfill Environmental Impact StudiesFrench-language works237,207