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Record W2918604275 · doi:10.3390/met9030286

Microstructure and Fracture Behavior of Refill Friction Stir Spot Welded Joints of AA2024 Using a Novel Refill Technique

2019· article· en· W2918604275 on OpenAlex
Lipeng Deng, Shuhan Li, Liming Ke, Jinhe Liu, Jidong Kang

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

VenueMetals · 2019
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsNatural Resources Canada
FundersNational Natural Science Foundation of China
KeywordsKeyholeSpot weldingMaterials scienceWeldingComposite materialMicrostructureJoint (building)Fracture (geology)Ultimate tensile strengthShear (geology)MetallurgyStructural engineering

Abstract

fetched live from OpenAlex

Keyhole at the end of a conventional friction stir welded (FSW) joint is one of the major concerns in certain applications. To address this issue, a novel keyhole refilling technique was developed for conventional friction stir spot welding (FSSW) using resistance spot welding (RSW). A three-phase secondary rectifier resistance welder was adapted for the refill of the keyhole in the 1.5 mm + 1.5 mm friction stir spot welded 2024-T4 aluminum alloy joint. The microstructure and tensile shear fracture behavior were compared for both the unfilled and refilled specimens. The results show that the plug and keyhole are dominated by solid state welding with some localized zones by fusion welding. The refill process significantly improved the maximum load capacity in tensile shear testing as the corona ring is enlarged leading to a larger bonding area. Moreover, the tensile shear fracture occurs in the refilled FSSW specimens at the corona bonding zone, while the fracture occurs at the hook zone in the unfilled keyhole.

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 score0.090
Threshold uncertainty score0.734

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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