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Record W4210858285 · doi:10.1680/jgein.21.00027a

Stress crack resistance of unaged high-density polyethylene geomembrane fusion seams

2022· article· en· W4210858285 on OpenAlexaff
W. Francey, R. Kerry Rowe

Bibliographic record

VenueGeosynthetics International · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsHigh-density polyethyleneWeldingMaterials scienceGeotechnical engineeringCrackingGeologyGeomembranePolyethyleneMining engineeringComposite material

Abstract

fetched live from OpenAlex

The stress crack resistance (SCR) of high density polyethylene (HDPE) geomembrane (GMB) fusion seams is examined for two 1.5 mm HDPE GMBs and a range of welding parameters. Results are reported for both unnotched and notched seams as well as their corresponding sheet material. Unnotched seam SCR specimens are shown to preferentially initiate craze formation at the terminating edge of the squeeze-out bead, while incorporating potentially degraded areas, such as the seams heat-affected zone (HAZ), within the slow crack growth region of the specimen. In the short-term, little variation was observed between the majority of seams for the nine welding parameter combinations examined, with an average normalized seam SCR value (normalized with respect to the unnotched sheet SCR) of 0.3 ± 0.1, or about 30% of the SCR of the unnotched sheet. It is shown that squeeze-out geometry plays an important role in the SCR of fusion seams. Seams with weld track rippling, a known qualitative indication of overheating, were found to have average unnotched SCR values 45% lower than smooth weld track seams. Deleterious squeeze-out geometries are identified to provide a framework through which CQA engineers and researchers can more readily identify ‘higher risk’ seams with respect to stress cracking.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations17
Published2022
Admission routes1
Has abstractyes

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