Effect of Velocity Ratio on Vortex Shedding From a Short Stack
Bibliographic record
Abstract
The influence of the jet-to-cross-flow velocity ratio, R, on vortex shedding from a cylindrical stack of aspect ratio AR = 9 was investigated using hot-wire anemometry. The cross-flow Reynolds number was ReD = 2.3×104 and R was varied from 0 to 3. The stack was partially immersed in a flat-plate boundary layer, where the boundary layer thickness-to-height ratio at the location of the stack was δ/H = 0.5. In the downwash flow regime, when R < 0.7, a single Strouhal number (e.g., St = 0.167 at R = 0) was measured along the entire stack height. In the crosswind-dominated flow regime, when 0.7 ≤ R < 1.5, a higher Strouhal number was obtained (e.g., St = 0.185 at R = 1.0). In the transitional and jet-dominated flow regimes, a jump in Strouhal number (e.g., from St = 0.176 to 0.193 at R = 2.0), occurred within the flat-plate boundary layer. The power spectra showed that the shape and strength of the vortex shedding peak changed along the stack height. In general, the peak was more broad-banded near the base of the stack, became sharper and more distinct within the middle of the combined stack and jet wakes, and then reduced in strength in the jet wake and jet regions. In the transitional and jet-dominated flow regimes, the jump in Strouhal number was seen as a gradual change in dominance between two closely spaced peaks, with both peaks co-existing near the edge of the boundary layer.
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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".