Effect of gap flow on the shallow wake of a sharp-edged bluff body—Coherent structures
Bibliographic record
Abstract
This experimental study was carried out to investigate the turbulent wake generated by a vertical sharp-edged flat plate suspended in a shallow channel flow with a gap near the bed. This paper is the third part of an extensive study to characterize the gap-flow effects and is primarily focused on the characteristics of vortices in the wake flow. Two different gap heights were studied which were compared to the no-gap flow case. The Reynolds number based on the water depth was 45 000. Extensive measurements of the flow field in the vertical and horizontal planes were made using a particle-image velocimetry (PIV) system. The large vortices were exposed by analyzing the PIV velocity fields using the proper orthogonal decomposition (POD) method. Only a few modes for the POD reconstruction were used to recover ∼50% of the energy content. A vortex identification algorithm was then employed to quantify the properties of the exposed vortices. A statistical analysis of the distribution of number, size, and strength of the identified vortices was carried out to explore the characteristics of the vortices. The results revealed that the gap flow causes an increase in the number of vortices up to ∼81% higher than the no-gap flow case, but a decrease in the vortex size and strength. The occurrence of pairing and tearing processes is observed in the wake flow. In addition, a mathematical model was used to predict the relationship between the vortex circulation and vortex size, which is found to be a function in several parameters.
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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 | 0.000 |
| 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) | 0.001 | 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".