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Record W2147188786 · doi:10.1002/pen.23735

Transition of neck appearance in polyethylene and effect of the associated strain rate on the damage generation

2013· article· en· W2147188786 on OpenAlexaff
P.‐Y. Ben Jar

Bibliographic record

VenuePolymer Engineering and Science · 2013
Typearticle
Languageen
FieldMaterials Science
TopicPolymer crystallization and properties
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCrossheadNeckingMaterials scienceComposite materialOpacityPolyethyleneStrain rateDeformation (meteorology)Optics

Abstract

fetched live from OpenAlex

By reducing tensile test speeds over four orders of magnitude, from 5 to 0.001 mm/min (corresponding to the initial strain rate of 4 × 10−3 to 8 × 10−7 s−1), color of polyethylene (PE) specimens remains translucent during the necking process, no longer changing to opaque white. Since changing the color to opaque white indicates the presence of cavities, the unchanged color suggests that such cavitation process is avoided by reducing the crosshead speed. With this discovery, the study proceeds to investigate the mechanical behavior of PE specimen shown at two crosshead speeds, 1 and 0.001 mm/min, before neck is developed; the former crosshead speed leads to opaque white neck but the latter translucent. The results show that at 1 mm/min, a stretch corresponding to a strain smaller than 4% can cause degradation of mechanical properties. Since this level of deformation is close to that allowed in service, the study recommends the consideration of in‐service loading rate for evaluation of the mechanical properties, especially for long‐term applications such as plastic pipes for natural gas transportation. POLYM. ENG. SCI., 54:1871–1878, 2014. © 2013 Society of Plastics Engineers

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 score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.008
GPT teacher head0.188
Teacher spread0.180 · 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

Citations16
Published2013
Admission routes1
Has abstractyes

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