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Record W2605899939 · doi:10.1680/jgein.17.00011

Effect of welding parameters on properties of HDPE geomembrane seams

2017· article· en· W2605899939 on OpenAlexaff
L. Zhang, Abdelmalek Bouazza, R. Kerry Rowe, John Scheirs

Bibliographic record

VenueGeosynthetics International · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsWeldingGeomembraneHigh-density polyethyleneMaterials scienceComposite materialHeat-affected zoneElectric resistance weldingPolyethyleneMetallurgy

Abstract

fetched live from OpenAlex

The effect of various welding parameters of a dual-wedge welding technique on the physical, mechanical and chemical properties of high-density polyethylene (HDPE) geomembrane seam specimens is examined. These seams were welded with sufficient heat, insufficient heat and excessive heat at specific speeds and nip pressures. The thickness of the fusion area and the width of the air channel provided an acceptable indication of the quality of the welding. Investigation of the seam specimens' mechanical properties showed that physical ageing had occurred. The impact of welding on antioxidants was evaluated using the standard oxidative induction time (Std-OIT) test method. The Std-OIT results showed that the outer edge of squeeze-out was greatly affected by the thermal welding. Scanning electron microscopy analysis confirmed that the morphology of the outer edge of squeeze-out was altered after welding. However, the Std-OIT test on other locations of the seam specimens indicated that welding had an insignificant impact on the Std-OIT values for the particular geomembrane and welding parameters considered.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score0.509

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 head0.016
GPT teacher head0.258
Teacher spread0.243 · 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 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

Citations29
Published2017
Admission routes1
Has abstractyes

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