MétaCan
Menu
Back to cohort
Record W2045890980 · doi:10.1177/0892705711428657

Optimization of thermoplastic composites resistance welding parameters based on transient heat transfer finite element modeling

2011· article· en· W2045890980 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 Thermoplastic Composite Materials · 2011
Typearticle
Languageen
FieldMaterials Science
TopicThermal properties of materials
Canadian institutionsNational Research Council CanadaÉcole de Technologie SupérieureMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceComposite materialWeldingFinite element methodClampingHeat transferOverheating (electricity)Thermal resistanceThermal conductionElectric resistance weldingThermoplasticStructural engineeringMechanical engineeringMechanics

Abstract

fetched live from OpenAlex

The use of resistance welding technology to join thermoplastic composite aerospace structures is still contingent upon a better understanding of the heat transfer mechanisms occurring during welding, which govern the joint quality and mechanical performance. In this study, two-dimensional (2D) and three-dimensional (3D) transient heat transfer finite element models were developed to simulate resistance welding of thermoplastic composites. The 2D model was used to investigate the effect of the length of the exposed areas of the heating element to air (clamping distance) on the local overheating at the edges and the effects of the input power level on the thermal behavior of the welds. It is shown that controlling the clamping distance improves the thermal uniformity of the weld. The 3D model shows that heat conduction along the length of the laminates influences the thermal uniformity of the weld interface. An optimization chart is developed in order to minimize the undesirable edge effect and to define the conditions required to obtain a complete weld. The results of the 3D model are compared with experimental data.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.217
Teacher spread0.185 · 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