Demystifying Underlying Fluid Mechanics of Gas Stirred Ladle Systems with Top Slag Layer Using Physical Modeling and Mathematical Modeling
Bibliographic record
Abstract
Effects of slag layer thickness on the fluid dynamics of liquid steel in gas-stirred ladles by bottom injection of argon was studied through water modeling experiments and numerical simulations. Mixing times increase considerably with thicker slag layers and decrease of gas flow rates. The physical properties of the system have a smaller influence on mixing time. Slag Eye Opening (SEO) area is increased under thin slag layers, increase of gas flow rates, and denser and less viscous slags. The planes close to the metal-slag interface, under the presence of thick slag layers for a given gas flow rate, are split in subregions of small velocities with different orientations making the lower fluid to come close to a stagnant condition. The presence of, either, thick or thin slag layers does not influence the axial velocity along the plume height for a fixed flow rate of gas. The SEO area follows a linear relationship with the square root of the densiometric Froude number based on the slag layer thickness.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".