Effect of turbulence on the wake of a wall-mounted cube
Bibliographic record
Abstract
The influence of turbulence on the flow around a wall-mounted cube immersed in a turbulent boundary layer is investigated experimentally with particle image velocimetry and hot-wire anemometry. Free-stream turbulence is used to generate turbulent boundary layer profiles where the normalised shear at the cube height is fixed, but the turbulence intensity at the cube height is adjustable. The free-stream turbulence is generated with an active grid and the turbulent boundary layer is formed on an artificial floor in a wind tunnel. The boundary layer development Reynolds number ( $Re_{x}$ ) and the ratio of the cube height ( $h$ ) to the boundary layer thickness ( $\unicode[STIX]{x1D6FF}$ ) are held constant at $Re_{x}=1.8\times 10^{6}$ and $h/\unicode[STIX]{x1D6FF}=0.47$ . It is demonstrated that the stagnation point on the upstream side of the cube and the reattachment length in the wake of the cube are independent of the incoming profile for the conditions investigated here. In contrast, the wake length monotonically decreases for increasing turbulence intensity but fixed normalised shear – both quantities measured at the cube height. The wake shortening is a result of heightened turbulence levels promoting wake recovery from high local velocities and the reduction in strength of a dominant 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) | 0.001 | 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".