Design of mould fluxes for continuous casting of special steels
Bibliographic record
Abstract
The melting behaviour of mould powder during continuous casting is an important consideration with respect to caster performance, production rate and steel quality. Two important factors, powder composition and carbon addition, are critical to control the properties and melting behaviour of the mould flux. In this study, the effect of different carbonaceous materials on the melting characteristics of mould powders was evaluated. Correlations were established between the structural factors and chemical reactivity of carbon and melting behaviour of mould flux. In addition, two examples are given of the effect of flux composition on casting performance for specific steels. A flux with reasonable basicity and additives was designed for the casting of heat-resistant steel (Incoloy 800) to reduce surface cracks. Another flux was designed for the casting of non-magnetic steel containing high aluminium by partially replacing SiO2 with Al2O3 to limit aluminium oxidation by SiO2.
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How this classification was reachedexpand
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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".