Influences of blockage ratio and Reynolds number on the spatiotemporal dynamics around a rectangular prism
Bibliographic record
Abstract
Particle image velocimetry is used to experimentally investigate the influence of blockage ratio (BR) and Reynolds number (Re) on the turbulent flow around a rectangular prism with depth-to thickness ratio of 3. The prism was selected because it falls within the intermediate regime where the turbulent dynamics is sensitive to the incoming boundary condition. The tested blockage ratios were 2.5%, 5%, and 10% at Reynold numbers of 3000 and 7500. The results are analyzed in terms of the mean flow, turbulent kinetic energy (TKE), frequency spectra, reverse flow area, as well as spectral proper orthogonal decomposition (SPOD). The results indicate that as blockage ratio and/or Reynolds number increase, the tendency of reattachment of the separated shear layer onto the surface of the prism increases while the location of maximum TKE over the prism shifts toward the leading edge, indicating earlier transition of the separated shear layer from laminar to turbulence. For the cases without mean reattachment over the side faces of the prisms, the separated bubble over and downstream of the prism exhibits strong tendency of synchronization in terms of the instantaneous areas of the flow reversal, suggesting a global instability mechanism encompassing the entire prism. In cases with mean flow reattachment, conversely, the low-frequency flapping motion manifests over the prism. SPOD analysis further shows that the relevant shedding dynamics are captured in the first mode and the von Kármán shedding structures have the highest energy.
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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) | 0.001 | 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".