Influence of Severe Accumulative Rolling in a Low Carbon Microalloyed Steel
Bibliographic record
Abstract
Effect of the severe deformation by multi-pass rolling on microstructure and tensile properties was analyzed in terms of rolling temperature, plate thickness, and cooling rate for a modified API X65 steel containing B. The plates, 80 and 50 mm thickness, were rolled six times by 20%/pass (total 75%) to 20 and 12 mm, at 1023 K of unrecrystallized γ region or 973 K of intercritical (α+γ) region, and then quenched in water or oil. All specimens except one oil-quenched condition showed relatively high UTS 700-830 MPa and the continuous yielding(YR～0.6), typical mode of the (ferrite + martensite (bainite)) dual phase microstructure. In contrast, one oil-quenched specimen with the 973 K-20 mm condition, exhibited the discontinuous yielding (YR～0.8), indicating that the microstructure basically consists of ferrite plus pearlite, as well as a relatively low UTS 660 MPa. The degree of deformation really occurring within materials, i.e., strain hardening seems to be enhanced with a decrease in deformation temperature. As the degree of deformation increases, the remaining austenite, not dynamically transformed to fine ferrite, becomes increasingly unstable. A lower hardenability of this remaining austenite thus would lead to a higher possibility to transform into the (ferrite + pearlite) structure of lower strength rather than the (ferrite + martensite (bainite)) of higher strength.
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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".