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Record W2067196976 · doi:10.1179/026708304225022313

Experimental simulation of surface pitting of degraded electrodes in resistance spot welding of aluminium alloys

2004· article· en· W2067196976 on OpenAlexaff
Y. Zhou, Satoshi Fukumoto, Jieyang Peng, Chuntao Ji, Lyndon J. Brown

Bibliographic record

VenueMaterials Science and Technology · 2004
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsWestern University
Fundersnot available
KeywordsMaterials scienceSpot weldingElectrodeWeldingAluminiumMetallurgyElectric resistance weldingJoint (building)Composite materialStructural engineering

Abstract

fetched live from OpenAlex

A novel experimental technique, using specially designed electrodes (with machined annular and circular pits, and central cavities), was developed to simulate the effects of pitting morphology of the electrode tip face on weld nugget size and joint strength in resistance spot welding of aluminium alloys. Results of the experimental simulations indicate that the distribution of electrode contact areas and their alignment between top and bottom electrodes both affect weld quality. A complete understanding of the correlation between tip face features and weld nugget formation would require three-dimensional numerical modelling; this work has provided well organised experimental data in support of future modelling work.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.009
GPT teacher head0.256
Teacher spread0.248 · 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 designSimulation or modeling
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

Citations23
Published2004
Admission routes1
Has abstractyes

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