Modeling of Microstructure Evolution during Hot Strip Rolling of Dual Phase Steels
Bibliographic record
Abstract
Microstructure models for hot strip rolling of CMnSi and CMnMo dual-phase steels have been proposed. The constitutive behaviour of austenite prior to the onset of dynamic recrystallization has been described by the physically based Kocks–Mecking model. The static recrystallization kinetics has been simulated by the Johnson–Mehl–Avrami–Kolmogorov (JMAK) theory. The recrystallized austenite grain size is described using an empirical equation considering the effect of strain, prior austenite grain size and deformation temperature. Ferrite transformation start is modeled with an approach that considers early growth of corner nucleated ferrite. The fraction of ferrite transformed from austenite during continuous and/or stepped cooling is described using the JMAK approach in combination with the additivity rule. The ferrite grain size is quantified as a function of the transformation start temperature. The critical conditions for the onset of bainite and martensite transformations in the remaining austenite have been empirically evaluated as a function of ferrite fraction transformed. The microstructure models for these metallurgical phenomena have been validated with experimental studies in the laboratory emphasizing industrially relevant hot strip rolling conditions and run-out table cooling strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".