Hybrid RANS/LES of turbulent flow in a rotating rib-roughened channel
Bibliographic record
Abstract
In this paper, we investigate the effect of the Coriolis force on the flow field in a rib-roughened channel subjected to either clockwise or counter-clockwise system rotation using hybrid RANS/LES based on wall modelling. A simplified dynamic forcing scheme incorporating backscatter is proposed for the hybrid simulation approach. The flow is characterized by a Reynolds number of Re = 1.5 × 104 and a rotation number Ro ranging from −0.6 to 0.6. The mean flow speed and turbulence level near the roughened wall are enhanced under counter-clockwise rotation and suppressed under clockwise rotation. The Coriolis force significantly influences the stability of the wall shear layer and the free shear layers generated by the ribs. Consequently, it is interesting to observe that the classification of the roughness type relies not only on the pitch ratio, but also on the rotation number in the context of rotating rib-roughened flows. In order to validate the present hybrid approach, the first- and second-order statistical moments of the velocity field obtained from the simulations are thoroughly compared with the available laboratory measurement data.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".