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Record W2895949998 · doi:10.2351/1.5059437

A new method of laser lap welding of zinc-coated steel sheet

2000· article· en· W2895949998 on OpenAlexaff
Hongping Gu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWelding Techniques and Residual Stresses
Canadian institutionsMiller Group (Canada)
Fundersnot available
KeywordsWeldingMaterials scienceElectric resistance weldingLaser beam weldingSheet metalMetallurgyZincButt weldingCorrosionJoint (building)Heat-affected zoneComposite materialStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Laser beam welding has been very successfully applied to butt joining of zinc-coated steel sheet and does not harm the property of corrosion resistance of the steel sheet. However, when this technology is applied to lap joint of these sheets, good quality welds are not easily obtained. Special techniques must be employed to vent the zinc vapor generated at the interface of the sheets; otherwise the vapor will expel the liquid metal out of the melt pool leaving porosity. Many efforts have been attempted with some success and most of the processes need additional procedure, which add cost to entire welding process. A new welding technique has been developed in ATC for lap joint of zinc coated steel sheets without maintaining a gap. This technology uses a high-quality tilted CO2 laser beam. Experimental results are presented and a possible explanation of zinc vapor venting mechanism for this welding technique is discussed in this paper.

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)0.000
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.267
Teacher spread0.254 · 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

Citations7
Published2000
Admission routes1
Has abstractyes

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