Numerical study of separated cross‐flow near a two‐dimensional rough wall with narrow apertures and suction
Bibliographic record
Abstract
Abstract The turbulent flow (Re = 1.5 × 105) near a rough wall with narrow apertures has been numerically analysed to study the effect of the aperture geometry and wall suction on the flow characteristics. The aperture entry geometry is characterized by roughness height and roughness width. The roughness height is varied from 0.3 to 1.2 mm and roughness width is varied from 2.6 to 4.0 mm. The wall suction is characterized by slot velocity which is varied from 0.25 to 5 m/s. The flow characteristics in terms of fluid streamlines, flow resistance, wall pressure, and wall shear have been presented for several cases. The results show that the flow through the apertures is dominated by a separation vortex that covers the aperture. As roughness height increased (or slope of the roughness), the vortex size increased. With increasing wall suction, the vortex size decreased and moved towards the aperture opening. The flow resistance characterized by pressure drop across the aperture is significantly high for very low wall suction and it is increased with increasing roughness slope. At higher wall suction the slot velocity and roughness geometry has less influence on flow resistance. Wall pressure and skin friction coefficients are dependent on the ratio of roughness height to width.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Simulation or modeling | low |
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".