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Record W2175206215 · doi:10.1179/136217101101538875

Comparative study of small scale and ‘large scale’ resistance spot welding

2001· article· en· W2175206215 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.

Bibliographic record

VenueScience and Technology of Welding & Joining · 2001
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsSpot weldingMaterials scienceElectrodeWeldingFinite element methodComposite materialContact areaContact resistanceMetallurgyUpset weldingHeat-affected zoneGas metal arc weldingStructural engineeringLayer (electronics)

Abstract

fetched live from OpenAlex

An incrementally coupled electrical–thermal–mechanical model is developed to simulate small scale resistance spot welding (SSRSW) using the finite element method. This numerical model is then employed to study the differences between SSRSW and ‘large scale’ resistance spot welding (LSRSW). The variations in contact area, current distribution, and temperature profile at the workpiece/workpiece interfaces are compared. The computation shows that the difference in electrode force could be the essential reason for other differences between SSRSW and LSRSW. Compared with LSRSW, a much lower electrode force (pressure) applied in SSRSW results in a relatively small contact area and hence a much higher current density, which in turn leads to a greater heating rate and higher temperature at the workpiece/workpiece interface. This small contact area also results in a relatively small nugget diameter in SSRSW, which is only about 30% of the electrode tip diameter. In contrast, the nugget diameter in LSRSW is comparable to the electrode tip diameter. The predicted nugget diameters in both SSRSW and LSRSW of mild steel sheets compare well with experimental results.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.467
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.238
Teacher spread0.219 · 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