Fluid Flow Control in a Billet Tundish during Steel Filling Operations
Bibliographic record
Abstract
The startup of casting sequences in continuous casting of steel using three different turbulence inhibitors were modeled and simulated through the multiphase volume of fluid model (VOF) in a four-strand tundish. In the actual caster, one of the inhibitors released the liquid steel with a superheat high enough to avoid freezing problems in the outer strands. A second inhibitor improved the flow, yet it yielded steel freezing in these strands. A two-phase air–water system was used to model the liquid steel–air system and the interfaces were tracked by a donor–acceptor principle applied in the computational mesh. These activities led to the design of a third inhibitor. Experimental outcomes and the mathematical simulations agreed remarkably well regarding the velocity of the stream front in the tundish floor and the mass of steel reaching the outer strands. A larger steel mass and a faster stream front helped to completely prevent the steel from freezing in the outer strands. Finally, flow fields during the filling of the tundish using two of these inhibitors were simulated and the results explain the different performances observed experimentally.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".