Effect of Inclination Angle and Flow Rate on the Heat Transfer During Bottom Jet Cooling of a Steel Plate
Bibliographic record
Abstract
The heat transfer that occurs during bottom water jet impingement on a hot steel plate has been investigated in terms of the effect inclination angle and flow rate. This research was carried out to develop quantitative knowledge of the heat transfer, which occurs on the runout table, a crucial component in the hot rolling production of advanced high strength steels. Industrially produced hot-rolled steel samples were instrumented with numerous subsurface thermocouples installed close to the quench surface. The experimental measurements were used in conjunction with an inverse heat conduction (IHC) model to quantify boiling characteristics as well as heat extraction histories for the different nozzle inclination angles and flow rates. It was found that, as nozzle inclination angle increased, the degree of asymmetry of the cooled region on the surface of the sample was increased and the overall rate of heat extraction decreased. The angle of inclination had a significant effect on overall heat extraction; a vertical nozzle was the most efficient from a perspective of heat transfer under the nozzle. As expected, as flow rates increased, the amount of heat energy extracted increased for all the conditions studied, regardless of the nozzle inclination.
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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 | 0.002 |
| 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 | 0.001 | 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".