Horizontal Single Belt Casting of Thin Strips of an Advanced High Strength Steel (Fe–21%Mn–2.5%Al–2.8%Si–0.08%C wt%)
Bibliographic record
Abstract
This research presents numerical modeling and experimental results on thin strips of Fe–21%Mn–2.5%Al–2.8%Si–0.08%C wt% steel, obtained using the horizontal single belt casting (HSBC) process. The free stream of the molten metal, exiting from a nozzle slot, was observed to be highly unstable and nonuniform, after interacting with a 30° inclined refractory plane of a delivery system. However, increasing the inclination of the refractory plane to 45°–60° allows the falling molten metal free stream to become much more stable and less fluctuating. In addition, the molten metal can undergo a hydraulic jump when impacting and flowing down these inclined refractory planes. These hydraulic jumps result in the generation of free surface waves, which travel further downstream. Fortunately, these instabilities are not usually detrimental to the surface quality of the casting, as they are rapidly damped, to disappear within a short distance, prior to solidification. The types and numbers of solid phases then forming for this steel, under the relevant Scheil cooling conditions, are determined using FactSage software. The surface roughness of the cast strip was evaluated using a Nanovea 3D surface profilometer. Microstructures of the cast and heat‐treated strips were determined using Optical and Electron microscopes.
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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".