Effect of Advanced Cooling Front (ACF) Phenomena on Film Boiling and Transition Boiling Regimes in the Secondary Cooling Zone during the Direct-Chill Casting of Aluminium Alloys
Bibliographic record
Abstract
Accurate knowledge of the boundary conditions is essential when modeling the Direct-Chill (DC) casting process. Determining the surface heat flux in the secondary cooling zone, where the greater part of the heat removal takes place, is therefore of critical importance. Boiling water heat transfer phenomena are quantified with boiling curves which express the heat flux density as a function of the surface temperature. Compilations of boiling curves for the DC casting of aluminum alloys present a good agreement at low surface temperatures but a very poor agreement at higher surface temperatures, in the transition boiling and film boiling modes. Secondary cooling was simulated by spraying instrumented samples with jets of cooling water. Quenching tests were conducted first with a stationary sample, and then with a sample moving at a constant “casting speed” in order to better simulate the DC casting process. The ejection of the water film in quenching tests with a stationary sample and the relative motion between the sample and the water jets both lead to an Advanced Cooling Front (ACF) effect, in which cooling occurs through axial conduction within the sample rather than through boiling water heat transfer at the surface. The heat flux density and surface temperature were evaluated using the measured thermal history data in conjunction with a two-dimensional inverse heat conduction (IHC) model. The IHC model developed at the University of British Columbia was able to take into account the advanced cooling front effect. The effect of various parameters (initial sample temperature, casting speed, water flow rate) on the rate of heat removal in the film boiling and transition boiling regimes was investigated.
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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) | 0.001 | 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 | 0.001 |
| 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".