Numerical Simulation of Melting Kinetics of Metal Particles during Tapping with Argon-Bottom Stirring
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Molten steel is alloyed during tapping from the melting furnace to the argon-bottom stirred ladle. The metallic additions thrown to the ladle during the ladle filling time are at room temperature. The melting rates or kinetics of sinking-metals, like nickel, are simulated through a multiphase Euler–Lagrangian mathematical model during this operation. The melting rate of a metallic particle depends on its trajectory within regions of the melt with high or low turbulence levels, delaying or speeding up their melting process. At low steel levels in the ladle, the melting rates are higher on the opposite side of the plume zone induced by the bottom gas stirring. This effect is due to its deviation after the impact of the impinging jet on the ladle bottom. The higher melting kinetics are located on both sides at high steel levels due to the more extensive recirculation flows formed in taller baths. Making the additions above the eye of the argon plume spout increases the melting rate of nickel particles. The increase of the superheat makes the heat flux more significant from the melt to the particle, increasing its melting rate. At higher superheats, the melting kinetics become less dependent on the fluid dynamics of the melt.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it