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Record W1971163657 · doi:10.1177/0021998311412986

Metal mesh heating element size effect in resistance welding of thermoplastic composites

2011· article· en· W1971163657 on OpenAlexaff
Martine Dubé, Pascal Hubert, Jan N.A.H. Gallet, Darko Stavrov, H.E.N. Bersee, Ali Yousefpour

Bibliographic record

VenueJournal of Composite Materials · 2011
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsNational Research Council CanadaMcGill UniversityÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceComposite materialThermoplasticWeldingMetalHeating elementMetallurgy

Abstract

fetched live from OpenAlex

The objective of this work is to determine the effects of metal mesh heating element size on resistance welding of thermoplastic composites. The materials to be resistance-welded consisted of carbon fiber/poly-ether-ketone-ketone (CF/PEKK), carbon fiber/poly-ether-imide (CF/PEI) and glass fiber/PEI (GF/PEI). Four different metal mesh sizes were used as heating elements. The samples were welded in a lap shear joint configuration and mechanically tested. Maximum Lap Shear Strengths of 52, 47 and 33 MPa were obtained for the CF/PEKK, CF/PEI and GF/PEI specimens, respectively. The ratio of the heating element’s fraction of open area and wire diameter was shown to be the most important parameter to be considered when selecting an appropriate heating element size.

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)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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

Citations75
Published2011
Admission routes1
Has abstractyes

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