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Record W2995772111 · doi:10.1139/cgj-2019-0572

An approach to high-density polyethylene (HDPE) geomembrane selection for challenging design requirements

2019· article· en· W2995772111 on OpenAlexafffundvenue
R. Kerry Rowe, F.B. Abdelaal, M. Zafari, M.S. Morsy, D. G. Priyanto

Bibliographic record

VenueCanadian Geotechnical Journal · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsCanadian Nuclear LaboratoriesQueen's University
FundersCanadian Nuclear LaboratoriesQueen's University
KeywordsLeachateGeomembraneHigh-density polyethyleneService lifeEnvironmental scienceGeotechnical engineeringMaterial selectionPolyethyleneMaterials scienceMunicipal solid wasteWaste managementComposite materialEnvironmental engineeringEngineering

Abstract

fetched live from OpenAlex

An approach for selecting a high-density polyethylene (HDPE) geomembrane (GMB) for a long design life is described and illustrated for five 2 mm thick textured GMBs when immersed in a simulated municipal solid waste leachate (L3) and two simulated leachates representative of low-level radioactive waste leachates (L7 and L9) for 9–16 months at a range of temperatures. Although made from the same nominal resin, substantial differences are reported in both the initial properties and the rate of antioxidant depletion for the five GMBs. At an expected operating liner temperature of 10 °C and immersed in L3, the projected time to antioxidant depletion for the five GMBs ranges from 125 to over 2000 years. The antioxidant depletion in leachates L7 and L9 were similar or slower than in leachate L3. There was no evidence of traditional thermal-oxidative degradation reported over the 9–16 months of monitoring; however, there was a significant reduction in stress crack resistance due to physical ageing ranging between 30% and 70% of the initial value. Two GMBs are considered highly likely to have service life well in excess of the required design life of 550 years. It is suggested that the proposed approach could be adopted for selecting GMBs for other projects that require a long design life.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.023
GPT teacher head0.238
Teacher spread0.215 · 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

Citations43
Published2019
Admission routes3
Has abstractyes

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