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Record W4315433323 · doi:10.1139/cgj-2022-0419

Physical and mechanical performance of an HDPE geomembrane in 10 mining solutions with different pHs

2023· article· en· W4315433323 on OpenAlexafffundvenue
F.B. Abdelaal, R. Kerry Rowe

Bibliographic record

VenueCanadian Geotechnical Journal · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of Canada
KeywordsGeomembraneHeap leachingLeachateLeaching (pedology)High-density polyethyleneGeotechnical engineeringHeap (data structure)Materials scienceEnvironmental scienceChemistryGeologyMetallurgyComposite materialCopperEnvironmental chemistryPolyethyleneSoil scienceMathematics

Abstract

fetched live from OpenAlex

The degradation in physical and mechanical properties of a 1.5 mm thick HDPE geomembrane immersed in seven different low pH and three high pH simulated mining solutions is examined at temperatures between 95 and 40 °C for 3 years. The solutions with pH between 0.5 and 13.5 encompass solutions found in copper, nickel, uranium, gold, and silver heap leach pads. The geomembrane did not exhibit any chemical degradation during the three years of incubation in all the low-pH solutions. However, in the solutions with pH 9.5, 11.5, and 13.5, some of the geomembrane’s physical and mechanical properties are shown to reach nominal failure at 95 and 85 °C. While the geomembrane examined shows superior performance in the acidic environments than in the basic solutions examined, its performance in such extremely basic environments is still better than in neutral reduced municipal solid waste leachate. Using Arrhenius’ modelling, the predicted times for the antioxidant depletion stage of the geomembrane examined in composite liner configuration range between 31 years in pH 13.5 to 51 years in pH 0.5 for pad liners at 50 °C, exceeding a typical leaching period of the ore of around 20 years in different heap leaching operations.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.479
Threshold uncertainty score0.655

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 head0.014
GPT teacher head0.213
Teacher spread0.199 · 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 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

Citations12
Published2023
Admission routes3
Has abstractyes

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