Regarding a technology of Sulphur removal in acidic induction furnaces
Bibliographic record
Abstract
Sulphurremoval is a rather complicated metallurgical task, which require implementation of new energy-saving technologies, including metal desulphurization in induction furnaces. Results of analysis of different methods of metal desulphurization in the acidic induction furnaces. A technology of hot metal refining with Sulphurremoval by basic slags by extraction mechanism in the acidic induction furnaces proposed, tested and implemented at several plants. The essence of the xtraction mechanism applied to desulphurization method is as follows: particles of calcic slag involved by electromagnetic flows deep into an induction furnace. The surface layer of slag particles deoxidizes by carbon of the metal and silicon, resulting in the Sulphursolubility increases sharply due to its absorption by the metal surface layer of slag particles. Next, the metal flows deliver to the surface the slag particles saturated by Sulphur, the surface contacted with the furnace atmosphere, where the surface layer of slag particles is oxidized by oxygen of the atmosphere. It results in the Sulphursolubility decreasing sharply and after precipitating out of the slag; it oxidizes by oxygen to SO2 and removes into the furnace atmosphere. The process repeats multiply. The mechanism of theSulphur removal in the induction furnaces with acidic lining was studied at OJSC ZSMK foundry shop using IChT-10M furnaces when melting hot metal for melt bases and warmth-keeping jackets. To increase the proposed technology efficiency, the influence of different technological parameters on the rate and degree of metal desulphurization in the acidic induction furnaces of industrial frequency studied. Results of the study allowed to make a conclusion that induction furnaces, traditionally used for smelting of burden materials, convert into active refining melting facilities.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".