Dynamic Recrystallization Kinetics of As-Cast Fe-Cr-Al-La Stainless Steel during Hot Deformation
Bibliographic record
Abstract
To investigate the dynamic recrystallization (DRX) behavior of as-cast Fe-20Cr-5.5Al-0.64La stainless steel, a series of compression tests were carried out on a Gleeble-3500 thermal simulator in the temperature range of 1000~1150 °C and the strain rate range of 0.001~1 s−1. The true stress-true strain curves were obtained and their characteristics were analyzed. Using regression analysis, the apparent activation energy for the Fe-20Cr-5.5Al-0.64La stainless steel was estimated to be 300.19 kJ/mol, and the constitutive equation was developed successfully with a hyperbolic sine equation as: <!-- MathType@Translator@5@5@MathML2 (no namespace).tdl@MathML 2.0 (no namespace)@ --> ε˙=e21.91sinh0.035σ3.18exp−300190RT <!-- MathType@End@5@5@ -->. The critical strain, the peak strain and the strain for the maximum softening rate were identified based on the work hardening rate curves and expressed as a function of the Zener−Hollomon parameter. The kinetic model of DRX was established using the stress−strain data. According to the analysis of the kinetics model and microstructure evolution, the evolution of DRX volume could be described as follows: the volume fraction of DRX grains increased with an increase in strain; at a fixed deformation temperature, the DRX volume fraction was larger at a lower strain rate for the same strain; and the size of DRX grains increased with an increase in temperature or a decrease in strain rate.
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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 | 0.000 | 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".