Open channel flow recovery in the wake of a flat plate on rough beds
Bibliographic record
Abstract
The flow recovery in the wake of a surface-mounted flat plate is investigated in an open channel. The plate with a thickness-to-chord ratio (t/c) of 0.12 is placed with the chord parallel to the flow. The characteristics of the mean velocity and higher-order statistics obtained along the wake axis upstream and downstream of the plate are discussed in the presence of bed roughness. Inner scaling of the mean velocity profile shows a depression in the outer region of the flow. The near-wall portion of the velocity profile in the plate wake region was found to recover faster to the upstream state. The profiles of the turbulent intensity in the plate wake deviate from the upstream profiles and recover gradually with downstream distance. The upstream turbulent intensities for the wire-mesh rough surface peak at farther wall normal locations compared to those of the sand grain and smooth surfaces. A similar roughness effect was observed at the downstream locations amidst the distorted flow, especially, in the intermediate and far wake regions. In the near- and intermediate-wake regions, both the velocity skewness and flatness factors data for the rough walls were higher compared to the data for the smooth surface. For all surfaces, even at the last measuring station (x = 200t) considered in the study, the skewness and flatness factors were found to be still recovering to the upstream condition.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".