Hot deformation characteristics of non-oriented electrical steels with and without phase transformation during thermomechanical processing
Bibliographic record
Abstract
Hot rolling plays a critical role in determining the final microstructure, texture, and magnetic properties of non-oriented electrical steels (NOES). Especially, NOES with and without phase transformation not only show different flow behaviors during hot rolling but also result in different final microstructures and textures. However, detailed investigations on such different behaviors of NOES have rarely been seen in the literature. In this study, the hot deformation characteristics of two non-oriented electrical steels containing (weight percentage) 1.3 % Si (with phase transformation) and 3.2 % Si (without phase transformation) were investigated by uniaxial compression in a temperature range of 850–1050 °C and a strain rate range of 0.01–1.0 s −1 , to evaluate the differences in deformation behavior and microstructure. The stress-strain curves were modeled using Zener-Hollomon constitutive equations and the material parameters were obtained. It is demonstrated that the difference in deformation behavior between the two steels is due to the presence/absence of austenite-ferrite phase transformations, and to the difference in activation energy and the amount of precipitate-forming elements, which influence the work hardening and softening mechanisms.
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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) | 0.001 | 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".