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Record W2556060692 · doi:10.1080/00084433.2016.1252555

Microstructural evolution of a hot-rolled microalloyed complex phase steel

2016· article· en· W2556060692 on OpenAlexafffund
Howard Scott, G. Sidhu, Fateh Fazeli, A.K. Pilkey, J. D. Boyd

Bibliographic record

VenueCanadian Metallurgical Quarterly · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsNatural Resources CanadaQueen's University
FundersAUTO21 Network of Centres of ExcellenceArcelorMittal
KeywordsLathMicrostructureBainiteMaterials scienceAusteniteFerrite (magnet)MetallurgyMicroalloyed steelThermomechanical processingPhase (matter)Acicular ferriteContinuous cooling transformationComposite materialMartensiteChemistry

Abstract

fetched live from OpenAlex

The current study examines a grade of hot-rolled and continuously cooled complex phase sheet steel comprised of polygonal ferrite (PF), granular bainite (GB) and lath bainite (B). The quantity of each constituent phase depends on the thermomechanical processing conditions, which vary between commercially produced sheets. In this study, the effects of cooling rate and austenite grain morphology on microstructure are determined through a series of dilatometry experiments. The resulting CCT diagrams show a progression in the order PF → GB → B with increasing cooling rate, and that a Pancaked (unrecrystallised) austenite condition promotes the formation of PF to higher cooling rates and the formation of GB to higher temperatures. Application of the CCT results to industrially produced sheet provides a useful approach for interpreting the evolution of microstructure during controlled-cooling and coiling. However, direct comparison is limited by the moderate level of austenite pancaking that can be achieved through laboratory dilatometry experiments in comparison to an industrial hot mill. Notable differences in microstructure are observed between the leading and trailing edges of industrially produced sheets due to relatively small variations in cooling schedules.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.999

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)0.0020.000

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 head0.208
Teacher spread0.196 · 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 teacher head, not a consensus.

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

Citations6
Published2016
Admission routes2
Has abstractyes

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