Aspect ratio effects on flow past a bed-mounted emergent cylinder
Bibliographic record
Abstract
The wake characteristics of an emergent bed-mounted circular cylinder of diameter d are investigated for intermediate aspect ratios located within a fully developed turbulent boundary layer using particle image velocimetry. The Reynolds number based on flow depth (H) and bulk velocity (Um) is 24 700, and the aspect ratio (AR), defined as the ratio of H/d, is varied from 1.7 to 6.7. The impact of AR on time-averaged flow statistics including mean velocity, Reynolds stresses, flow anisotropy, and two-point correlations was analyzed in the vertical central plane and across three spanwise planes. This study builds upon the earlier work of Heidari et al. [Phys. Fluids 29(6), 065111 (2017)], which investigated an emergent, bed-mounted cylinder with AR = 11. The results reveal that the flow topology and coherent structures in the wake are influenced by AR across all measurement planes. In the low AR cases, detached reverse flow regions were observed near the bed, as bed friction interferes with the formation of the von Kármán vortex street. Proper orthogonal decomposition (POD) reveals a decrease in energy content in the near-bed plane with increasing AR consistent with enhanced small-scale activity. In contrast, the trend is reversed in the mid-depth and near-free surface planes, where turbulent kinetic energy becomes concentrated in the low-order modes as AR increases. Furthermore, for AR = 1.7, the POD modes are highly correlated throughout the flow depth, whereas higher AR cases show weaker correlations, indicating complex flow structures.
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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 | 0.000 |
| 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 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".