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A Microstructure Evolution Model for Intercritical Annealing of a Low-carbon Dual-phase Steel

2014· article· en· W1987555103 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueISIJ International · 2014
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaArcelorMittal
KeywordsAusteniteRecrystallization (geology)Dual-phase steelMicrostructureMaterials scienceMetallurgyAnnealing (glass)Carbon steelFerrite (magnet)Composite materialMartensite

Abstract

fetched live from OpenAlex

A model was developed to describe the microstructure evolution during intercritical annealing of a low-carbon steel suitable for industrial production of DP600 grade dual-phase steel on a hot-dip galvanizing line. The microstructure evolution model consists of individual submodels for ferrite recrystallization, austenite formation and decomposition constructed using the Johnson-Mehl-Avrami-Kolmogorov approach and the additivity principle. The submodels for recrystallization and austenite formation are adopted from a previous study. The present paper provides a detailed analysis of the model development for the decomposition of intercritical austenite. The overall microstructure evolution model is validated using simulated industrial thermal paths for intercritical annealing. Model validation is expedited by in-situ measurements of the recrystallization completion temperature using laser ultrasonics and the intercritical austenite formation and decomposition using dilatometry.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.511

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 head0.010
GPT teacher head0.247
Teacher spread0.236 · 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