Application of “flat’ closed-bottom submerged nuzzles for decreasing rejections of slabs because of longitudinal cracks
Bibliographic record
Abstract
In the process of steel continuous casting it was discovered, that due to relatively small distance between a submerged nuzzle and a mold walls, formation of “scull crust” takes place in the area of small and big radius of the billet. It resulted in deterioration of heat-away in mold, conditions are formed for origination of longitudinal cracks following its further opening in the CCM secondary cooling zone. To decrease the number of rejections continuously casted slab billets due to existence of longitudinal cracks, it was proposed to use “flat” closed-bottom submerged nuzzles. It was shown, that in contrast to cylindrical form of a series closed-bottom submerged nuzzle, the proposed one has rectangular section with chamfered butt facet in the are of nuzzle submerging into the mold melt, which enables to ensure better fluidity of slag-forming mixture between the nuzzle and the mold walls. This effect results in onsiderable improving evenness of heat-away. To confirm the effectiveness of the pilot submerged nuzzles application, in 2019 their pilot-industrial tests were accomplished in the campaign of casting of carbon and peritectic steels to produce 200 mm thick slabs at CCM No. 4. In the process of the tests when casting various steels, the same slag-forming mixtures were used. As a result of the tests the decrease of rejections of continuously casted slabs due to longitudinal cracks formation was confirmed.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".