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Characterisation of welded joints produced by FSW in AA 1100–B<sub>4</sub>C metal matrix composites

2012· article· en· W2040989524 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 · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsNational Research Council CanadaUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsMaterials scienceComposite materialWeldingMatrix (chemical analysis)MetalMetallurgy

Abstract

fetched live from OpenAlex

The feasibility of friction stir welding for joining AA 1100 based metal matrix composites reinforced with B 4 C particulate is studied for 16 and 30%B 4 C volume concentrations. For both composites, friction stir welding has a significant influence on the particle size distribution and the matrix grain size. For the 16% composite, the average particle size decreases after welding by ∼20% and the grain size from 15 to 5 μm as measured in the weld nugget. Tensile testing of welded joints showed up to 100% joint efficiency for both annealed AA 1100–16%B 4 C and AA 1100–30%B 4 C composite materials. However, if the ultimate tensile strength values of all the studied composites are similar at ∼130 MPa, then the weld ductility is higher for the annealed materials. Furthermore, it was observed that varying the welding speed between 100 and 275 mm min −1 does not influence the tensile properties and the particle size distribution in the nugget.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.238
Teacher spread0.231 · 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