Modeling the Flow Curve of Hot Deformed Austenite
Bibliographic record
Abstract
A 0.02%C plain carbon and a 0.22%C TRIP steel were tested in compression in the temperature range 900°C to 1150°C and strain rate range 0.05s-1 to 1s-1. Thirty-two experimental flow curves were obtained in this way. The critical conditions for the initiation of dynamic recrystallization were determined by the double differentiation method. Using a dislocation density model to describe the austenite flow stress, the work hardening parameters r and h were derived and are used to model the flow curve in the absence of dynamic recrystallization. The latter was employed to calculate the fractional softening attributable to dynamic recrystallization. The kinetics of dynamic recrystallization are then described using Avrami kinetics. Finally, the dependences of the Avrami and work hardening parameters on Z, the Zener-Hollomon parameter, are used to model compression flow curves at strain rates an order of magnitude greater than the ones employed in the tests.
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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 | 0.001 | 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) | 0.002 | 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".