Simulation of Austenite Flow Curves under Industrial Rolling Conditions Using a Physical Dynamic Recrystallization Model
Bibliographic record
Abstract
Hot compression tests were carried out on three steels: i) a 0.038% Nb-0.11%C microalloyed grade; ii) a Nb-modified TRIP steel; and iii) a Ti-stabilized low carbon steel. The tests were performed at strain rates up to 1 s–1 and over the temperature range 880–1200°C. The initiation of dynamic recrystallization (DRX) was observed under all testing conditions. Two sets of equations were derived from the experimental curves: i) a work hardening relation pertaining to the grains in which DRX has not yet nucleated; and ii) a separate work hardening expression describing the mean flow stress applicable to the grains in which DRX is taking place. With the aid of the temperature and strain rate dependences determined from the data, and using the law of mixtures, extrapolated flow curves were calculated applicable to strain rates up to 100 s–1, i.e. to those involved in strip mill rolling. The simulations show that, once DRX has been initiated, the flow stress is controlled by the kinetics of the softening mechanisms.
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.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".