Turbulence Modification Due to Wave Action at Low Reynolds Numbers in Horizontal Open-Channel Flow
Bibliographic record
Abstract
Wave-turbulence interaction was experimentally investigated in turbulent open-channel flows with a shear-free wavy surface using a photochromic dye activation technique. In the experiments conducted, two-dimensional waves of different amplitudes, wavelengths, and frequencies were superimposed on a liquid surface via a mechanical wave maker. The range of Reynolds numbers varied from 3900 to 5000 based on the hydraulic diameter, with the corresponding aspect ratio of the channel width to liquid depth varying from 7.5 to 5.Within the range of Reynolds numbers investigated, the results showed that the streamwise turbulence intensity increased in the bulk and interfacial regions in comparison to the undisturbed flow.Furthermore, video sequences of the flow visualization experiments clearly revealed that the spanwise motion of the liquid was significantly suppressed; the traces did not immediately deform in the spanwise direction but retained their shape with increasing wave amplitude and frequency as compared to smooth interface flows. This suggests that waves may have suppressed longitudinal vortices generated near the smooth interface. The suppression of the longitudinal vortices in wavy open-channel flows has been proposed as a mechanism responsible for the turbulence energy redistribution, different from that for smooth open-channel flows.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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".