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Application of Deformation to Improve Hot Ductility in the Peritectic Steel

2005· article· en· W2084072029 on OpenAlexaff
Ahmad Rezaeian, Faramarz Zarandi, D. Bai, Steve Yue

Bibliographic record

VenueMaterials science forum · 2005
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMcGill University
Fundersnot available
KeywordsMaterials scienceMetallurgyFlow stressFlatteningMicroalloyed steelDeformation (meteorology)Hot rolledFormabilitySlip (aerodynamics)Ductility (Earth science)Strain rateAusteniteComposite materialMicrostructure

Abstract

fetched live from OpenAlex

The hot strip rolling of advanced microalloyed high strength steels still represents a new task to many mills due to the lack of data on the hot deformation resistance. With the aid of processing data from the Ispat-Inland hot strip mill, the “measured mean flow stresses” are calculated from the mill force using the Sims analysis and taking into account roll flattening, slip ratio and the redundant strain. A modification of the Misaka mean flow stress equation is proposed for C – Mn – Si – Al steels microalloyed with up to 0.02 % Nb. The effects of alloying and microalloying are then estimated. A new fitting parameter shows excellent agreement with the mean flow stress data from industrial processing of advanced high strength microalloyed steels. However, during the second half of the rolling schedule (lower temperature region), indications of austeniteto- ferrite transformation were found.

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)0.001
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 score0.004
Threshold uncertainty score0.194

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.227
Teacher spread0.220 · 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.

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

Citations3
Published2005
Admission routes1
Has abstractyes

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