The effect of non-uniform skelp temperature on X70 steel coil cooling
Bibliographic record
Abstract
This study explored the effect of varying steel skelp temperature (500 °C–600 °C) on the subsequent temperature-time ( T- t) profile during and after coiling of low C (0.05 wt. %) X70 microalloyed steels. Three industrially produced steel coils with similar rough rolling temperatures (∼1050 °C) and finish rolling temperatures (∼850 °C) but different coiling temperatures (500 °C–600 °C) and different skelp thicknesses (19 mm and 25 mm) were studied. The surface temperature of each coil was measured using an infrared video camera. A three-dimensional heat transfer model was developed to predict the T- t profiles. A lower (∼60 °C) initial skelp temperature near the head and tail of the skelp led to a reduced coil temperature. A higher (∼50 °C) temperature near the head and tail region of the skelp resulted in a more uniform coil temperature (a difference of ∼10 °C instead of ∼50 °C).
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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) | 0.001 | 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".