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Record W3034552264 · doi:10.3390/technologies8020034

Influence of WC-Based Pin Tool Profile on Microstructure and Mechanical Properties of AA1100 FSW Welds

2020· article· en· W3034552264 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

VenueTechnologies · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsMaterials scienceWeldingTungsten carbideScanning electron microscopeMicrostructureFriction stir weldingUltimate tensile strengthEnergy-dispersive X-ray spectroscopyComposite materialTungstenOptical microscopeMetallurgy

Abstract

fetched live from OpenAlex

The effect of various tungsten carbide (WC) pin tools and operating parameters on the material structure and properties of an AA1100 friction stir welding (FSW) weld were evaluated. Three different pin shapes were employed (conical, square and threaded). For each tool shape, welds were generated for a set of tool (revolutions per minute, RPM) (710, 1120 and 1400) and advancing speeds (150, 250 and 400 mm/min). Weld samples were tested for mechanical strength by tensile testing. Morphology was examined using optical microscopy, and weld composition with scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD). No weld contamination from the tools was observed. However, a number of structural defects, inherent to the FSW process, were observed (including tunnel voids, kissing bonds and swirling lines). These defects, associated with the stirring action, could not be eliminated. The results show how the operating parameters may be optimized to produce stronger welds.

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)0.000
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 score0.026
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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