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Record W2995033330 · doi:10.1115/appc2019-7604

Measurement of Environmental Stress Cracking Resistance of Polyethylene Pipe: A Review

2019· review· en· W2995033330 on OpenAlexaff
Yi Zhang, P.‐Y. Ben Jar, Shifeng Xue, Limei Han, Lin Li

Bibliographic record

Venuenot available
Typereview
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEnvironmental stress crackingMaterials scienceCrackingBrittlenessStress corrosion crackingStress (linguistics)PolyethyleneDeformation (meteorology)Composite materialFracture mechanicsCharacterization (materials science)Fracture (geology)Forensic engineeringCorrosionStructural engineeringEngineeringNanotechnology

Abstract

fetched live from OpenAlex

Abstract Use of polyethylene (PE) for water and natural gas transportation has increased rapidly due to its good physical and mechanical properties, especially its excellent corrosion resistance property. However, when immersed in adverse environment and subjected to applied stress, PE will suffer from accelerated crack growth in a phenomenon known as environmental stress cracking (ESC). ESC occurs in a brittle manner without little pre-fracture deformation, thus can cause catastrophic, unexpected failure for PE pipe. A number of different test methods have been developed for characterizing ESC resistance (ESCR) of PE materials. Within this paper, a state-of-the-art review is given on the current ESCR characterization methods, including the working principle and limitations of each method.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.242
Teacher spread0.219 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2019
Admission routes1
Has abstractyes

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