MétaCan
Menu
Back to cohort
Record W3206513800 · doi:10.3390/met11101592

Submerged Dissimilar Friction Stir Welding of AA6061 and AA7075 Aluminum Alloys: Microstructure Characterization and Mechanical Property

2021· article· en· W3206513800 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceMicrostructureVickers hardness testFriction stir weldingWeldingIndentation hardnessGrain sizeMetallurgyAlloyAluminiumJoint (building)Composite materialOptical microscopeScanning electron microscopeStructural engineering

Abstract

fetched live from OpenAlex

The possibility of underwater dissimilar friction stir welding of AA6061 and AA7075 aluminum alloy was explored to overcome the problem of hardness loss in different microstructural zones. Optical microscopy and electron backscattered diffraction were employed to characterize the microstructure of the joint. Vickers hardness measurements were conducted on the cross-section of the joint to evaluate the mechanical strengths. The results showed that the microstructure of the AA7075 side had undergone the same mechanisms as those occurring during conventional friction stir welding. In the case of the AA6061 side, in addition to typical restoration mechanisms, the grain subdivision was observed. The AA7075 side had finer grains compared to the AA6061 side, which may be related to the different morphology and size of precipitates. Moreover, friction stir welding caused a reduction in the hardness values in all the microstructural areas compared to those of corresponding base materials. For example, it caused a reduction in the hardness of a thermomechanically affected zone from 105 HV to 93 HV in the AA6061 side, and from 187 HV to 172 HV in the AA7075 side. The underwater media improved the overall hardness values in thermo-mechanically affected zones (13% reduction in hardness) compared to those reported in literature (57% reduction in hardness).

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 score0.175
Threshold uncertainty score0.437

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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