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Record W2563381886 · doi:10.1111/ffe.12563

Fatigue behaviour of dissimilar Al 5052 and Mg AZ31 resistance spot welds with Sn‐coated steel interlayer

2016· article· en· W2563381886 on OpenAlex
Ming Sun, Seyed Behzad Behravesh, Liyan Wu, Y. Zhou, Hamid Jahed

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFatigue & Fracture of Engineering Materials & Structures · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceSpot weldingMetallurgyBrittlenessFracture (geology)AluminiumWeldingAlloyComposite materialFatigue limitBending

Abstract

fetched live from OpenAlex

Abstract The fatigue property of dissimilar spot welds between an aluminium alloy (AA5052) and a magnesium alloy (AZ31) was studied in this research. The AA5052 and AZ31 coupons were resistance spot welded together by using an interlayer of Sn‐coated steel between the two coupons. The fatigue test results revealed that the Mg/Al joints had the same level of fatigue strength as Mg/Mg resistance spot welds. It was found that within the life range of N f < 10 5 cycles, Mg/Al welds degraded faster than Mg/Mg joints. This was attributed to the larger bending moment on the plane of fatigue failure in the Mg/Al welds. Three failure modes were observed under different cyclic loading regimes: Al/steel interfacial failure, Mg coupon failure and Al coupon failure. Fatigue fracture surface of Mg/Al welds consisted of two distinct regions: crack propagation region with brittle morphology and final rupture with ductile morphology.

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 categoriesMeta-epidemiology (narrow)
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 score0.114
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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