Mathematical and Physical Modelling of Transient Multi-Phase Flows in a Ladle Shroud during Start-Up
Bibliographic record
Abstract
The Ladle Shroud has become an important part of secondary steelmaking, with its role in reducing liquid steel contamination and process improvements. Due to the inherent negative pressure at the lower nozzle–Ladle Shroud joint, it is well known that Ladle Shrouds, protecting steel flows between a Ladle and a tundish below, can suffer from inadvertent ingress of air. Therefore, there is a need to apply inert gas injection at the joint. In the present paper, 3D transient multi-phase simulations of flows occurring for a Reverse Tapered Ladle Shroud during start-up were studied using CFD software ANSYS Fluent 19.1. This allowed us to study the initial multi-phase flow developed during the start-up and potential steel reoxidation, based on a first principles approach. Time-dependent phase fields as well as attendant velocity and turbulence fields were obtained, resulting in the prediction of a turbulent multi-phase flow during start-up and filling. Additionally, some transient phenomena like steel splashing and air suction were observed mathematically. A full-scale water model of the Ladle Shroud was used to qualitatively validate the initial multi-phase turbulent flow inside the Ladle Shroud, in the absence of inert gas injection.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".