Study of the Effect of Hellenic Diasporic Bauxite Addition on Blast Furnace Operations
Bibliographic record
Abstract
The blast furnace (BF) operation, as well as the steel‐shop downstream, can derive benefits from adjusting the slag alumina content with the proper addition of bauxite flux to its burden. Additions of 5‐15 kg of bauxite/t hot metal lead to a raise of the alumina content of the resultant BF‐slag from 10% to the level of about 12%. In Hellas extensive deposits of diasporic bauxite exist which, however, are under‐utilized by the alumina refineries due to their rather low solubility during the Bayer‐process. The above BF application, therefore, as an alternative use of the diasporic bauxite, is of great interest to the bauxite producers of Hellas. The influence of the bauxite additions on the metal/slag reactions under BF‐conditions was simulated in the laboratory by smelting BF‐slag with diasporic bauxite additions in a graphite crucible. It was achieved the production of BF‐slags with higher alumina contents under the condition of constant slag basicity. The results show the beneficial effect of the bauxite addition to the quality of the produced hot metal. In accordance to its desulphurization and desiliconization as well as the increase of BF‐slag sulphur capacity and fluidity, a thermodynamic evaluation of the metal/slag reaction in respect of SiO2 reduction and S‐transfer to the slag in relation to its Al2O3 content was carried out. This evaluation led to simple algebraic functions and graphs easily applicable by the BF operators. The attained metallurgical results were verified in comparison to industrial test heats with bauxite additions in the BF‐burden in USA, Canada and Europe.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".