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Growth Rate and Phase Composition of Oxide Scales during Hot Rolling of Low Carbon Steel

2004· article· en· W2028431457 on OpenAlexaff
Vladimir V. Basabe, Jerzy A. Szpunar

Bibliographic record

VenueISIJ International · 2004
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsMcGill University
Fundersnot available
KeywordsWüstiteHematiteMagnetiteOxideIron oxideMaterials scienceAtmospheric temperature rangeMetallurgyOxidizing agentCarbon steelPhase (matter)Analytical Chemistry (journal)MineralogyChemistryThermodynamicsCorrosionChromatography

Abstract

fetched live from OpenAlex

The rate of scale growth on low carbon steel in air over the temperature range 600-1200°C and the phase composition changes that occur between 750-1200°C were investigated. The low carbon steel was oxidized with the air velocity of 4.2 cm/s in order to approximate the formation of secondary and tertiary scales in hot rolling. In addition, some experiments were performed with a lower air velocity of 0.14 cm/s. Above 1000°C, with the air velocity of 4.2 cm/s, a transition from a parabolic rate of oxidation to a linear rate of oxidation was observed as the temperature increased. This transition in oxidizing mechanisms was related to the porosity of the oxide scale. The phase composition of the oxide scales changed with temperature and time. For the initial 30 s of oxidation, wustite was the predominant phase in the temperature range 800-1200°C and as oxidation proceeded, the percentages of magnetite and hematite increased. The homogeneity of the oxide decreased as the oxidation temperature increased. At 850°C, with the air velocity of 4.2 cm/s, the oxide was homogeneous, and for the first 120 s of oxidation, the oxide had a high percentage of wustite and a low percentage of hematite. This indicates that 850°C is the ideal temperature for the finishing strip mill in order to reduce work roll wear and surface defects.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.217
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

Citations60
Published2004
Admission routes1
Has abstractyes

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