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Record W2054872278 · doi:10.1179/174328409x453271

Microstructure evolution model for hot strip rolling of Nb–Mo microalloyed complex phase steel

2009· article· en· W2054872278 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMaterials Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceMicrostructureBainiteAusteniteMetallurgyFerrite (magnet)Microalloyed steelMartensiteSofteningContinuous cooling transformationComposite material

Abstract

fetched live from OpenAlex

A microstructure model for hot strip rolling of an Nb–Mo microalloyed complex phase steel has been proposed. The constitutive behaviour of austenite is described by the Kocks–Mecking model. The static softening kinetics is simulated by a combined recovery recrystallisation model using the law of mixtures. Ferrite transformation start is modelled with an approach that considers the early growth of corner nucleated ferrite. Bainite start is related to a critical driving pressure. Both ferrite and bainite reactions are described using the Johnson–Mehl–Avrami–Kolmogorov (JMAK) approach in combination with the additivity rule. The martensite fraction is empirically related to the carbon enrichment in austenite and is, thus, a function of the ferrite fraction formed in the final microstructure. Precipitation strengthening during coiling is simulated with a modified Shercliff–Ashby model. The microstructure models for these metallurgical phenomena have been validated with experimental studies of laboratory simulated hot strip rolling conditions and run-out table cooling strategies.

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.

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 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 score0.061
Threshold uncertainty score0.504

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)0.0000.000

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 head0.016
GPT teacher head0.241
Teacher spread0.225 · 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