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Record W2174558545 · doi:10.1179/136217104225021562

Improving vibration weld joint strength through process and equipment modifications

2004· article· en· W2174558545 on OpenAlexaff
B. Tucker, P. J. Bates, R. F. Tucker, V. Sidiropolous

Bibliographic record

VenueScience and Technology of Welding & Joining · 2004
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsWeldingMaterials scienceComposite materialPerpendicularThermoplasticVibrationJoint (building)Butt weldingGlass fiberStructural engineering

Abstract

fetched live from OpenAlex

Vibration welding is a process used to join thermoplastic components. Currently, under optimised low pressure welding, the weld strength of butt joints of unreinforced polymer can be equivalent to the strength of unwelded material. However, in short glass fibre reinforced polymer, the optimised weld strength is significantly lower than that of unwelded material and is closer to the strength of the resin matrix. This lower strength is attributable to the unfavourable orientation of the short glass fibres in the weld zone. The fibres tend to align parallel and in the plane of the weld zone and thus provide no reinforcement in the direction perpendicular to the weld zone. In the present work the impact of various modifications to the existing vibration welding technology was examined, with the objective of increasing the current achievable weld strength of glass reinforced nylon. The introduction of a secondary vibratory motion perpendicular to the weld plane during welding resulted in strengths 20% higher than those of samples welded using the standard vibration welding process.

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: 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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.018
GPT teacher head0.254
Teacher spread0.236 · 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

Citations17
Published2004
Admission routes1
Has abstractyes

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