Modelling of transport phenomena in a delta-shaped, four-strand tundish
Bibliographic record
Abstract
A full-scale physical model of a delta-shaped, four-strand tundish was constructed at McGill University to find optimal operating conditions for the tundish. The objective of this work was to determine how best to increase steel production rates by 14% over current tundish operating conditions, these being 12 tons/min with four 15.0 mm outlet nozzles for a 500 mm depth of liquid steel while maintaining steel quality levels. Two options were suggested: the normal head option uses 16.0 mm outlet nozzles and maintains the 500 mm tundish level, while the high head option uses 14.8 mm outlet nozzles and raises the depth of liquid steel within the tundish to 800 mm. The important effects of flow control devices on the hydrodynamic performance of the tundish were also tested, using two different types of flow modifiers: Impact Pad and Turbo-Stop. For a proper comparison between the two options, three aspects were investigated; vortex formation phenomena during tundish draining between ladle changes, Residence Time Distribution (RTD), and Inclusion Separation Ratios (ISR). Inclusion removal rates were studied experimentally with the aid of the aqueous" Liquid Metal Cleanliness Analyzer (LiMCA) system. Particle Image Velocimetry (PIV) was used to visualize the actual instantaneous, or momentary, flows, thereby providing the data needed for time averaged velocity fields and turbulent kinetic energies. A mathematical model based on METFLO was developed to simulate these tundish operations numerically. The Renormalization Group turbulence model (RNG) as well as the standard high Reynolds number k-s turbulence model (STD) was implemented in order to simulate the turbulent flows within the tundish. The validity of METFLO was confirmed by PIV measurements and the numerical predictions of the RTD, and RRI matched the results of physical modelling.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".