Characterization of Boiling Phenomena during Laboratory-Scale Forced Convection Quenching
Bibliographic record
Abstract
An experimental investigation was conducted to correlate heat extraction with boiling phenomena at the liquid-probe interface during forced convective quenching of a steel probe in a laboratory-scale facility.A conical-end probe made of AISI 304 stainless steel instrumented with two type-K thermocouples was rapidly cooled from 850 °C in water at 60°C, flowing with a free-stream velocity of 0.2 m/s.Bubble formation, growth and detachment at the probe surface was recorded with a high-speed video camera.Using the experimental cooling curves measured with the sub-surface thermocouple, the surface heat flux was estimated by solving a onedimensional inverse heat conduction problem (IHCP) without phase change.The inverse boiling curve obtained showed that the maximum peak on heat extraction was reached during the nucleate boiling stage and is associated with the time at which the wetting front passed though the thermocouple axial location.From image analysis, two regions can be distinguished as the wetting front travels through the probe: the wetting front, formed by small bubbles that grew rapidly and coalesced due to the large bubble population; and a region trailing the wetting front, where the size, population and dynamic behavior of the bubbles was quite different.These bubbles grew conserving a spheroidal shape until they reached their maximum size; when they were decreasing, a concave deformation was observed at the interface due to condensation caused by the quench media rewetting the surface and, finally, the bubble departed from the probe surface, collapsing in the bulk flow near the probe surface.
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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 | 0.001 |
| 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".