The Critical Strain for Dynamic Transformation in Hot Deformed Austenite
Bibliographic record
Abstract
The 63 flow curves published previously in ISIJ Int. (2012) are re-analyzed for the presence of departures from simple work hardening (dynamic recovery) behavior. These curves were determined on a 0.019%C plain C, a 0.11%C Nb microalloyed, and a 1.56%Mn-1.56%Si Nb-modified TRIP steel by means of hot compression tests carried out from 900 to 1150°C and at strain rates up to 1 s–1. Two sets of second derivative minima are shown to be associated with all 63 curves, in contrast to the single minima reported earlier. It is shown that double minima can only be obtained when the polynomial order of the fitting procedure on the whole flow curve is 11 or higher. By contrast, when only the ascending portion of the flow curve is fitted, double minima are found as long as the polynomial order is at least 8. The first set of minima corresponds to the initiation of dynamic transformation (DT), as shown in an earlier analysis of torsion flow curves. The second set of minima is associated with the nucleation of dynamic recrystallization (DRX); these were the only minima reported earlier. The temperature dependences of the two sets of minima intersect at higher temperatures, indicating that the only softening mechanism operating at high austenite deformation temperatures (in addition to dynamic recovery) is DRX.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".