Experimental Study of Turbulent Wake Flow Around Trapezoidal Cylinders With Varying Streamwise Aspect Ratios
Bibliographic record
Abstract
Abstract The effects of streamwise aspect ratio (AR) on the asymmetric wake flow over and behind right-angled trapezoidal cylinders with AR (= upper cylinder length to height ratio) = 1, 2, 3, 4, and 5 were investigated using particle image velocimetry. The Reynolds number based on the freestream velocity and cylinder height was 14700. The flow characteristics are examined in terms of the mean velocity flow, Reynolds stresses, probability density function (PDF), and two-point correlations. The results show that the primary vortex in the AR1 and AR2 trapezoidal cases extends into the wake region but is confined to the surface of the longer cases and two asymmetrical wake vortexes are only observed in the longer cases. Dual peaks of elevated streamwise Reynolds stresses are observed in the wake region, regardless of the aspect ratios. The magnitudes of the Reynolds stresses and turbulent kinetic energy are higher in the shorter cases (AR1, AR2, and AR3 cases) compared to the longer cases. The PDF distributions show a bimodal asymmetrical shape in the shorter cases but a nearly Gaussian distribution in the AR5 case. Two-point autocorrelations of the streamwise and vertical velocity fluctuations revealed that the spatial coherency of the turbulent structures is highly sensitive to the streamwise aspect ratio and reference locations. Systematic comparison between the present asymmetric results and symmetric wakes generated by rectangular cylinders with similar aspect ratios and Reynolds number shows significant differences between the asymmetric and symmetric wakes, especially at smaller aspect ratios.
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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".