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Dynamic Transformation of a Low Carbon Steel at Temperatures above the Ae3

2011· article· en· W2090865344 on OpenAlexafffund
Vladimir V. Basabe, John J. Jonas, Hesameddin Mahjoubi

Bibliographic record

VenueISIJ International · 2011
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaArcelorMittal
KeywordsAusteniteMaterials scienceIsothermal processFerrite (magnet)Strain (injury)Isothermal transformation diagramMetallurgySaturation (graph theory)Deformation (meteorology)Strain rateCarbon steelAtmospheric temperature rangeComposite materialThermodynamicsBainiteMicrostructureMathematics

Abstract

fetched live from OpenAlex

The dynamic transformation of austenite was studied in a 0.06%C low carbon steel by deforming to strains of 0.25–5.0 at strain rates of 0.04 and 0.4 s–1 over the temperature range 877–917°C. All these temperatures are at or above the conventional Ae3. Two critical strains were detected, the first (about ε=0.2) was for the formation of strain-induced ferrite; the second (about ε=1.5) was the critical strain for the reverse transformation, which was gradual and only observed in specimens deformed at the lower strain rate. After deformation, the strain-induced ferrite was stable for about 60 s of isothermal holding. However, after this time, the reverse transformation began to take place, approaching saturation in about 240 s. The influence of strain, strain rate and temperature on the dynamic transformation is described. The results indicate that reverse transformation is unlikely to take place in the finishing stands of strip mills due to the high strain rates and short interpass times involved. It is also suggested that conventional phase diagrams do not apply to austenite undergoing deformation in rolling mills.

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 score0.004
Threshold uncertainty score0.009

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 head0.007
GPT teacher head0.189
Teacher spread0.181 · 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

Citations25
Published2011
Admission routes2
Has abstractyes

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