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Record W4231344172 · doi:10.1002/9781119274803.ch53

Effect of Dynamic Recrystallization on Microstructure Evolution and Texture Weakening during Annealing of High Speed Rolled AZ31 Magnesium Alloy Sheets

2016· other· en· W4231344172 on OpenAlexaff
Jing Su, Abu Syed Humaun Kabir, Mehdi Sanjari, In‐Ho Jung, Stephen Yue

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsMicrostructureAnnealing (glass)Materials scienceRecrystallization (geology)AlloyMetallurgyMagnesium alloyDiffractionMagnesiumDynamic recrystallizationOptical microscopeComposite materialScanning electron microscopeHot workingOpticsGeology

Abstract

fetched live from OpenAlex

Magnesium AZ31 (Mg-3 wt. % Al-1 wt. % Zn) alloy sheets were rolled at a high speed of 1000 m/min at 100 °C to reductions of 30% and 49%. Annealing was then conducted on the as-rolled specimens at temperatures of 200 °C and 350 °C for different times. The microstructure was characterized by optical microscopy and the macrotexture was analyzed by X-ray diffraction. The as-rolled microstructure of the specimen subjected to the reduction of 30% was heavily twinned and shear banded, while a partially dynamically recrystallized and twinned microstructure was observed at the reduction of 49%. Effect of the initial microstructure on static recrystallization behavior and texture evolution during annealing was studied at different temperatures. Texture weakening was found during annealing at both reductions. However, the weaker texture can be achieved in the specimen subjected to the reduction of 30% than that of 49%.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.003
GPT teacher head0.215
Teacher spread0.212 · 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 designBench or experimental
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
Published2016
Admission routes1
Has abstractyes

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