Dimensionless numbers for tundish modelling and the Guthrie number ( <i>Gu</i> )
Bibliographic record
Abstract
Modelling the transport phenomena in tundishes has been a vast area of research for the last three decades. Many papers have been published and are available in the literature on this subject. The basics of modelling involve a similarity criterion between the model and the full scale prototype and are well documented in major textbooks. However, the similarity criteria are different for different cases. For example, for fluid flow in a tundish, the Re and Fr similarity is considered, whereas for heat transfer, the Pr and Pe number similarity should be considered. Numerous other examples can be cited. It is really important to know which similarity criteria should be used for a particular case. In this paper, a new dimensionless number Gu has been proposed when dealing with the modelling of inclusions separating out in a tundish. All dimensionless numbers can be represented as a ratio of two characteristic time scales, and this fact is highlighted in the present paper.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".