Bed roughness effect on flow separation beneath partially submerged simulated ice cover in a shallow channel
Bibliographic record
Abstract
The effect of bed roughness on shear layer separation and coherent structures beneath a partially submerged cover in a shallow channel is evaluated. A planar particle image velocimetry system is used to conduct detailed instantaneous velocity measurements beneath the partially submerged simulated ice cover. The results indicate that roughness influences near-wall turbulence, whiles the separated shear layer dominated the flow dynamics close to the undersurface of the cover. The instantaneous velocity field shows elongated separated shear layer underneath the cover for flow over the smooth bed compared to the rough bed. The bed roughness contributed to a reduction in size of the recirculation bubble at the undersurface of the cover. The instantaneous size of the recirculation bubble shows expansion and contraction of the separated shear layer when compared to the mean bubble size, depicting intense shear layer flapping at the undersurface of the cover, and this is dominant for the smooth bed flow. Close to the leading edge of the cover, the instantaneous spanwise vorticity magnitude shows dominance of small-scale instabilities akin to the Kelvin-Helmholtz type instability at interface of the separated shear layer. The separated shear layer generated large-scale vortices of varying length scale when compared to the bed roughness. Although bed roughness promoted near-wall turbulence with elevated levels of Reynolds stresses compared to the smooth bed, at the undersurface of the cover, the high levels of stresses were due to shear layer separation. A wide range of integral length scales are estimated within the separated shear layer, which contributed significantly to the generation of the Reynolds stresses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".