Bibliographic record
Abstract
The formation of accretions or clogging of tundish nozzles in the continuous casting of steel is detrimental both to caster productivity and to eventual inclusion content of the final product.The cause of the clogging is related to a combination of operating criteria including ladle slag practice, tundish refractory, deoxidation methodology and temperature.To assess the effect of various slag components on clogging a mineralogical and rheological study was conducted on both plant and simulated accretion material.Minerals belonging to the lime-alumina-silica system such as hibonite, gehlenite, mullite, spinel and corundum, all having solidification temperatures at or above steelmaking temperatures, were most prevalent.In Mn-rich melts larnite, hibonite and a glassy phase were predominant.The rheological studies confirmed the formation of a significant solids fraction near steelmaking temperatures for basic melts whereas high (>30w/o) Mn melts were glassy.As well, the plate composition of the gating system was also deemed to contribute to the problem, with Zr0 2 being preferable to AljO;,.Results are discussed with a view to designing tundish slags to minimise formation of refractory solids while maintaining reasonable compatibility with refractory and gating system practice.
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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 | 0.001 |
| 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 | 0.000 |
| 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".