An Experimental Study of a Turbulent Wall Jet on Smooth and Transitionally Rough Surfaces
Bibliographic record
Abstract
The effect of surface roughness on the mean velocity and skin friction characteristics of a plane turbulent wall jet was experimentally investigated using laser Doppler anemometry. The Reynolds number based on the slot height and exit velocity of the jet was approximately Re = 7500. A 36-grit sheet was used to create a transitionally rough flow (44 < ks+ < 70). Measurements were carried out at downstream distances from the jet exit ranging from 20 to 80 slot heights. Both conventional and momentum-viscosity scaling were used to analyze the streamwise evolution of the flow on smooth and rough walls. Three different methods were employed to estimate the friction velocity in the fully developed region of the wall jet, which was then used to calculate the skin friction coefficient. This paper provides new experimental data for the case of a plane wall jet on a transitionally rough surface and uses it to quantify the effects of roughness on the momentum field. The present results indicate that the skin friction coefficient for the rough-wall case compared to a smooth wall increases by as much as 140%. Overall, the study suggests that for the transitionally rough regime considered in the present study, roughness effects are significant but mostly confined to the inner region of the wall jet.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".