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Record W4404350622 · doi:10.1115/pvp2024-123726

Peel Strength of Multilayer Polymer-Based Pipes

2024· article· en· W4404350622 on OpenAlexaff
Mahima Dua, Ahmed Hammami, Pierre Mertiny

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPolymerMaterials scienceComposite materialComputer science

Abstract

fetched live from OpenAlex

Abstract Multilayer polymer composite piping typically comprises a primarily load-bearing structural layer and one or two inner and outer protective layers. The latter aims to protect the structural layer from damage caused during installation and operation. Multilayer pipes are an attractive alternative to conventional single-layer composite piping and are sought for elevated temperatures and pressure operation for oil and gas transportation. Concerns associated with multilayer pipes are fluid permeation, lack of barrier performance, and inadequate adhesion between layers. Rapid gas decompression (RGD) testing replicates the rapid decrease in pressure that may occur in operation. It helps identify defects in the pipe design, materials, and/or fabrication, leading to layer separation and even pipe collapse. However, RGD testing is expensive, requires complex equipment, and may pose safety risks. Therefore, an alternative safe, expedient, and cost-effective procedure is sought. In response to this need, peel testing is investigated according to the DIN 53357 standard, also known as German wheel peel testing. A peel test apparatus has been adapted based on the DIN 53357 standard in the present work. Results from testing five-layer polymer-based pipes are reported in the present study. Baseline tests were performed at room temperature at a 10 mm/minute peel rate on a 10 mm wide and 2.5 mm thick peel strip. The influence of peel rate, peel strip width and thickness, and temperatures were investigated in this work. This contribution concludes with a discussion about the effects of these parameters and the suitability of peel testing for multilayer pipes.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score1.000

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)0.0010.000

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 head0.012
GPT teacher head0.227
Teacher spread0.216 · 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.

Study designSimulation or modeling
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

Citations0
Published2024
Admission routes1
Has abstractyes

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