Industrial Direct Chill Slab Caster of Tin Bronze (C903) Using a Porous Filter in the Hot-Top
Bibliographic record
Abstract
A 3D computational fluid dynamics (CFD) modeling study has been carried out for the tin bronze (C903) slab of industrial size in a vertical direct chill caster. The melt is delivered from the top across the entire cross section of the caster. An insulated hot-top is considered above the 80-mm mold to control the melt level in the mold. A porous filter is considered in the hot-top region of the mold to arrest the incoming inclusions and homogenize the flow into the mold. The melt flow through the porous filter is modeled on the basis of the Brinkmann–Forchheimer-extended non-Darcy model. Results are obtained for four casting speeds varying from 40 to 100 mm/min. The metal–mold contact region, as well as the convective heat transfer coefficient at the mold wall, is also varied. In addition to the above, the Darcy number for the porous media is also changed. All parametric studies are performed for a fixed inlet melt superheat of 62 °C. The results are presented pictorially in the form of temperature and velocity fields. The sump depth, mushy region thickness, solid shell thickness (ST) at the exit of the mold, and axial temperature profiles are also presented and correlated with the casting speed through regression analysis.
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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) | 0.001 | 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) | 0.002 | 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".