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Record W3190129017 · doi:10.22099/ijmf.2021.39914.1177

Textural Evolution of 6061 Aluminum Alloy Processed by Accumulative Roll-Bonding Process

2021· article· en· W3190129017 on OpenAlexaff
Mohammad Reza Rezaei, Mohammad Reza Toroghinejad, F. Ashrafizadeh, Hamed Asgari, Jerzy A. Szpunar

Bibliographic record

VenueIranian Journal of Materials Forming · 2021
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAccumulative roll bondingMaterials scienceMetallurgyTexture (cosmology)Shear (geology)AlloyAluminiumCopperDeformation (meteorology)Magnesium alloyComposite materialArtificial intelligence

Abstract

fetched live from OpenAlex

A commercial Al-Mg-Si alloy (AA 6061) was deformed by using the accumulative roll bonding (ARB) process for up to five cycles at ambient temperature. The evolution of texture in this process was studied by the X-ray diffraction (XRD) method. Experimental results indicate that the combination of the shear texture composed of Rotated cube {001} component and the rolling textures that included Copper {112} and Dillamore {4, 4, 11} components developed after the first cycle. During the first cycle, the shear texture was developed as a result of shear deformation induced by high level of friction between the rolls and the sheet. By increasing the number of cycles, the shear texture strength diminished and changed to the rolling texture. After the fifth cycle, a remarkable increase in the rolling texture intensity was observed due to homogenous deformation induced by the presence of fine non-shearable particles. Additionally, the presence of magnesium in solid solution influenced the texture evolution during ARB.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.012
GPT teacher head0.264
Teacher spread0.251 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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