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Record W2481301456

Tensile Strength of Friction Stir Spot Welded Dissimilar AA5754-to-AZ31B Alloys

2012· article· en· W2481301456 on OpenAlexvenueno aff
X. Cao

Bibliographic record

VenueNPARC · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsUltimate tensile strengthMaterials scienceMetallurgyWeldingFriction stir weldingComposite materialSpot welding
DOInot available

Abstract

fetched live from OpenAlex

Friction stir welding (FSW) is a relatively new joining process. As a solid-state joining technique, FSW provides good potential for dissimilar materials, even for those considered to be "difficult" and "unweldable". As a variant, friction stir spot welding (FSSW) can have significant potential to replace riveting or resistant spot welding for aerospace and automotive applications. To date, limited work has been carried out on the FSSW of dissimilar material combinations. In this work, the tensile shear strength obtained is reported for a dissimilar 2-mm thick AA5754-to-AZ31 alloy system. The main process parameters investigated include tool rotation speed, tool plunge rate, dwell time and work-piece placement (i.e. either Al or Mg alloy on the top of the lap spot welds). The tensile shear strength is also compared with that obtained for similar AA5754-to-AA5754 and AZ31-to-AZ31 welds. Furthermore, the tensile shear strength is correlated with the joint geometrical dimensions and welding defects. Copyright © 2013 ASM International® All rights reserved.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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Same venueNPARCSame topicAdvanced Welding Techniques AnalysisFrench-language works237,207