Effect of Reynolds number on turbulent channel flow over a superhydrophobic surface
Bibliographic record
Abstract
The slip boundary and the near-wall statistics of a fully developed turbulent channel flow over a superhydrophobic surface (SHS) was investigated in a low Reynolds number (Re) range. The Re was varied from 6200 to 9400, based on the bulk velocity and the full-channel height. The root-mean-square of the surface roughness, normalized by the inner flow scaling, varied from 0.26 to 0.35 with increasing Re. Time-resolved, two-dimensional particle tracking velocimetry (PTV) was used to obtain the mean velocity profile in the linear viscous sublayer. Furthermore, time-resolved three-dimensional PTV was applied to obtain the Reynolds stresses. The estimated wall shear stress showed that the drag reduction of the SHS increased slightly from 37% to 42% when Re increased. With increasing Re, the slip velocity increased linearly from 0.25 m/s to 0.34 m/s, and the slip length reduced from 97.5 μm to 69.6 µm. When normalized using inner scaling, slip velocity and length remained constant with increasing Re. The mean velocity of the SHS demonstrated a log-law with the universal von Kármán constant but shifted upward by an amount equal to the normalized slip velocity. The SHS increased the dimensional Reynolds stresses in the near-wall region and attenuated them farther away from the wall. With increasing Re, the differences between the dimensional Reynolds stresses of the smooth surface and the SHS increased. However, when Reynolds stresses were normalized using friction velocity, the Reynolds stresses of the SHS overlapped for all the investigated Re and were larger than the normalized Reynolds stresses of the smooth surface.
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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".