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Record W2262620462 · doi:10.4271/2002-01-0604

Factors Affecting the Tensile Strength of Linear Vibration Welds of Dissimilar Nylons

2002· article· en· W2262620462 on OpenAlexaff
Liying Qi, D.F. Watt, Bobbye Baylis

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2002
Typearticle
Languageen
FieldEngineering
TopicMaterial Properties and Processing
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsUltimate tensile strengthMaterials scienceVibrationStructural engineeringComposite materialEngineeringAcousticsPhysics

Abstract

fetched live from OpenAlex

Three different pairs of high melting temperature and low melting temperature nylons have been welded together using three different design of experiment welding process parameter matrices. An unorthodox analysis of these has revealed that there is a general increase in strength as the total welding sliding distance of the two surfaces increases. This is not surprising. The analysis also reveals that, for a given sliding distance, the vibration amplitude should be large, which shortens the welding time. This strategy produces shorter cycle times and stronger welds, according to the data obtained in these test sets.

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 score0.006

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 head0.021
GPT teacher head0.225
Teacher spread0.204 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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