Physical and mathematical modeling of a metal delivery system for a single belt caster
Bibliographic record
Abstract
In order to design the metal delivery system for the single belt caster in the MMPC (McGill Metals Processing Centre) foundry, water modeling and mathematical modeling were carried out for a newly devised three-chamber type tundish. Water flow in the acrylic tundish was visualized using dye injection. Flow velocities were also measured using a Dual Nd-YAG PIV (Particle Image Velocimetry) system. A commercial FEM code, FEMLAB 2.3 was adopted to predict the velocity field and temperature profile within the tundish, especially in the output chamber. Calculated results were validated with the PIV measurements. A full-scale water model was built for the single belt caster to simulate the casting operation and to validate the optimized delivery system. Temperature profiles for the tundish wall were also predicted to choose a suitable method of preheating and to determine refractory wall specifications. A three-chamber type tundish comprising an entry chamber, a head control chamber and an output chamber was designed to provide clean metal and strips of uniform thickness across the width of the belt. An output chamber proved to be essential for removing the bubbles and for obtaining a uniform film of water on the substrate by preventing strong hydraulic jump. The output chamber had to be completely closed for rapid bubble removal. For rapid filling of the output chamber at start up, the starting stopper proved to be essential. The 3-hole type nozzle, proved to be more effective for removing the bubbles, was found to have problems in terms of strongly impinging jet flow and non-uniform lateral velocities. Using mathematical modeling and full scale water modeling, including PIV measurements, the "FD" type nozzle, which had a multi channel flow modifier in the output chamber and a slot type inlet nozzle, was found to be the best in terms of rapid bubble removal and uniform distribution of flow. This was achieved by a dramatic reduction in the strength of the vertically impinging flow towards the belt. However, this "FD" type nozzle generated a dead zone near the triple point within the output chamber. To remove the dead zone, a gently sloped shape insulator was inserted between the tundish back wall and the belt.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".