Mathematical modeling of heat transfer in the meniscus region of the continuous slab casting mould
Bibliographic record
Abstract
The objective of this investigation was to characteristize the heat transfer phenomena related to the Submerged Entry Nozzle (SEN) and its role on the heat transfer of the liquid steel in the meniscus region of the mould broad face. The investigation has been conducted based on a previous plant trial at Stelco’s Lake Erie. A mathematical model, which includes the SEN and the liquid steel, was formulated. The heat transfer in the SEN was examined by performing a two - dimensional finite difference model with the Alternating Direction Implicit (ADI) method. The influences of the SEN on the steel heat transfer in the meniscus region was studied under various conditions. The heat transfer of the liquid steel was investigated (i) by a plug flow model for the liquid steel flowing through the SEN tube and (ii) by a one-dimensional finite difference model for the liquid steel in the meniscus region. The modeling results revealed that the SEN absorbs heat from the liquid steel both inside the SEN tube and in the meniscus region, and loses heat to the atmosphere through its exposed surface above the meniscus; the liquid steel falling through the SEN tube has a temperature drop of about 2.4°C from the SEN entrance to exit for a SEN length of 0.7 m; about 30% of the superheat extracted of the liquid steel in the meniscus region is absorbed by the SEN. Many factors, such as the thermal properties of the SEN sleeve and body materials and the mould flux insulation depth and performance, have influences on the heat transfer of the SEN and then on the heat transfer of the liquid steel in the meniscus. The distance between the mould broad face and the SEN is also an important factor which influences the severity of the cooling effect of the liquid steel in the meniscus caused by the SEN heat transfer. With the shorter distance between the mould broad face and the SEN, the cooling effect of the liquid steel is more pronounced. The SEN tube length, especially the length above the meniscus, has an effect on the temperature drop of the liquid steel inside the SEN. The results of this work showed the importance of the heat transfer of the SEN regarding to the casting process and provided guidelines for improvements on slab surface quality and operating 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".