Effect of Dynamic Transformation on the Mean Flow Stress
Bibliographic record
Abstract
Abstract Flow curves were determined in torsion at a series of temperatures on four plain C steels and a Nb microalloyed steel of increasing C concentration. The mean flow stresses (MFSs) pertaining to each experimental condition were calculated from the flow curves by integration. These are plotted against inverse absolute temperature in the form of Boratto diagrams. The stress drop temperatures, normally defined as the upper critical temperature $A_{{\rm r3}}^{{\rm *}} $ , were determined from these diagrams. These are shown to be about 40°C above the paraequilibrium and about 20°C above the orthoequilibrium temperatures. This type of behavior is ascribed to the occurrence of dynamic transformation (DT) during deformation. The general characteristics of the DT of austenite to ferrite are reviewed. It is suggested that some of the unexpected load drops that have been reported to take place above the A e3 temperature in strip mills may be attributable to this phenomenon.
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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 | 0.000 | 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) | 0.002 | 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".