Ferrite Formation above the Ae<sub>3</sub> Temperature during the Torsion Simulation of Strip Rolling
Bibliographic record
Abstract
Torsion simulations of 7-pass strip rolling were carried out on a 0.06%C-0.3%Mn-0.01%Si and a 0.11%C-1.0%Mn-0.11%Si-0.03%Al-0.034%Nb steel using pass strains of 0.4 applied at 1 s−1. The deformations were imposed isothermally at 910°C and 930°C for the C–Mn and the Nb microalloyed steel, respectively. The flow curve levels decreased from pass to pass as a result of softening by both dynamic transformation (DT) and dynamic recrystallization (DRX). The application of double differentiation to the stress-strain curves led to average critical strains for the initiation of DT and DRX of about 0.06 and 0.11, respectively. Optical microscopy revealed that the volume fraction of DT ferrite increased continuously right up to the last pass. The fraction of DT ferrite formed and retained was significantly higher when short interpass times were used. Comparison of the behaviors of the C–Mn and Nb steels indicates that Nb addition retards both the forward as well as the reverse transformation.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".