Effects of Blockage Ratio on the Spatiotemporal Dynamics of Turbulent Flow Separation Around a Square Cylinder at Moderate Reynolds Numbers
Bibliographic record
Abstract
Abstract The effects of blockage ratio (BR) on turbulent flows around square cylinders at moderate Reynolds numbers are investigated using a time-resolved particle image velocimetry (TR-PIV). The blockage ratios range from 2.5% to 15%, and the Reynolds numbers based on the freestream velocity and cylinder thickness are 3000, 7500, and 15,000. The flow dynamics are examined in terms of the mean flow, Reynolds stresses, frequency spectra, reverse flow area, and proper orthogonal decomposition (POD). The results show that the wake characteristics are nearly independent of the Reynolds number and blockage ratio. Spectral analyses of the velocity fluctuations demonstrate that the von Kármán (VK) shedding frequency is independent of the Reynolds number and blockage ratio, however, the Kelvin–Helmholtz (KH) frequencies increase with increasing Reynolds number and blockage ratio. The probability density function of the reverse flow area shows unimodal and bimodal distributions for the lower (BR ≤ 5%) and higher (BR ≥ 10%) blockage ratios, respectively, and the mean reverse flow area and its standard deviation decrease with increasing blockage ratio. The results also show that the contributions from the first POD mode pair to the total energy increase with blockage ratio but independent of the Reynolds number. The POD mode coefficients show significant cycle-to-cycle variation at lower blockage ratios, suggesting that the energetic structures are comparatively less organized at lower blockage ratios. The spectra of the velocity fluctuations, reverse flow area, and POD mode coefficients all show dominant peaks at the fundamental shedding frequency.
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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".