The Strain Dependence of Post-Deformation Softening during the Hot Compression of 304H Stainless Steel
Bibliographic record
Abstract
Experiments were carried out in which the dependence of the fractional softening on temperature, time and strain rate was determined in a 304H stainless steel. Three prestrain ranges were identified pertaining to three different post-deformation softening behaviors: 1) prestraining to below the DRX critical strain: strongly strain dependent softening by SRX alone with softening kinetics controlled by growth rate of the nuclei; 2) prestraining to above the DRX critical strain: SRX + MDRX softening with weaker strain dependence of the kinetics but still controlled by grain growth; 3) at a prestrain of ε* and beyond: nucleation-controlled MDRX softening with the full inhibition of SRX. The transition prestrain ε* can exceed the peak strain if the DRX grain refinement ratio g = D0/DDRX > 4. The transition to MDRX-dominated softening can be attributed to a constant value of the normalized strain hardening rate independent of the preloading temperature and strain rate. The softening data from the compression tests show that at ε*, the time for half softening t50 exhibits a minimum. These data differ somewhat from observations obtained in the torsion testing of solid bars, in which no strain dependence of t50 was detected at ε* and beyond. Whether or not the strain dependence of t50 vanishes in the MDRX range is sensitive to the test method employed to study the post-deformation softening.
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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".