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Record W3084242143 · doi:10.1177/0021998320957055

Modelling resistance welding of thermoplastic composites with a nanocomposite heating element

2020· article· en· W3084242143 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Composite Materials · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsÉcole de Technologie SupérieurePolytechnique Montréal
FundersCentre de Recherche sur les Systèmes Polymères et Composites à Haute Performance
KeywordsMaterials scienceComposite materialNanocompositeWeldingFinite element methodBrittlenessThermoplasticElectric resistance weldingFractographyUltimate tensile strengthStructural engineering

Abstract

fetched live from OpenAlex

Electrically conductive nanocomposite heating elements are being developed as a complement to traditional carbon fibre or stainless steel heating elements in resistance welding of thermoplastic composites. Here we present the development of a finite element model of the resistance welding process with these new heating elements, from which we establish a process window for high quality welded joints. The finite element model results were validated experimentally and a lap shear strength improvement of 28% is reported relative to previously published results. Fractography analysis of the broken joints revealed a thin-layer cohesive failure mode due to the brittleness of the nanocomposite heating elements.

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.

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 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 score0.180
Threshold uncertainty score0.621

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.202
Teacher spread0.190 · 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