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Record W2113070864 · doi:10.1179/136217109x456960

Joint formation in dissimilar Al alloy/steel and Mg alloy/steel friction stir spot welds

2009· article· en· W2113070864 on OpenAlexafffund
T. Liyanage, J. Kilbourne, A.P. Gerlich, T. H. North

Bibliographic record

VenueScience and Technology of Welding & Joining · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversity of TorontoUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpot weldingMaterials scienceMetallurgyIntermetallicAlloyWeldingCrackingDual-phase steelGalvannealedComposite materialCarbon steelGalvanizationMicrostructureLayer (electronics)MartensiteCorrosion

Abstract

fetched live from OpenAlex

The microstructural features and overlap shear strength properties of friction stir spot welds made between Al 6111 and low carbon steel, and between Mg alloy AM60 and DP600 dual phase steel, are investigated. When Al 6111 is the upper sheet in the dissimilar sandwich, completed spot welds show evidence of intermetallic layer formation and cracking. Increasing tool pin penetration into the lower sheet provided increased mechanical interlocking of the sheets due to clinching. However, increasing penetration also promoted intermetallic formation and cracking in completed welds. However, dissimilar AM60/DP600 steel friction stir spot welds produced with AM60 as the upper sheet in the dissimilar sandwich do not show evidence of intermetallic formation and cracking may be avoided by removing the zinc coating on the DP600 steel before the friction stir spot welding operation.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.011
GPT teacher head0.244
Teacher spread0.233 · 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

Citations182
Published2009
Admission routes2
Has abstractyes

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