Simulation of BB-2 beam billet conti-nuous casting for production of large-sized I-beams
Bibliographic record
Abstract
In connection with expansion of construction sector, it is planned to develop 80‒90‒100 I-beams. For these I-beams, universal section of continuously cast billet BB-2 (1050×450×120) was developed. The purpose of this work was to check casting parameters of given billet in a simulation model, using LVMFlow software, to confirm analytical calculations. Following parameters were chosen as parameters to be evaluated: geometric shape of the cast billet, temperature and dynamic parameters of casting. For maximum reliability, boundary conditions were set similar to real parameters of the CCM-3 at EVRAZ NTMK JSC, however, as assumptions, the calculation was carried out only in zone of direct contact with mold sleeve, and plane deformation condition was set along casting. Simulation results showed possibility of using LVMFlow to simulate the beam blanks casting processes with high degree of convergence. Casting BB-2 billet is technically possible in the conditions of continuous caster No. 3 at JSC EVRAZ NTMK, when the mold is replaced. Hydrodynamic pressure is created only on walls of crystallizer; there is vacuum on remaining surfaces due to lack of crystallizer walls narrowing sleeve towards cooling. Crystallization occurs most slowly along the interface between the wall and the BB flanges, however, there are no defects in the form of splashes, due to the low hydrodynamic pressure in these zones
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".