Effect of Reynolds number, near-wall perturbation and turbulence on smooth open-channel flows
Bibliographic record
Abstract
Three series of experiments were conducted to study the effect of Reynolds number, near-wall perturbation and turbulence on the velocity characteristics of smooth open-channel flows. Measurements were carried out using a laser Doppler anemometer. The variables of interest include mean velocity, turbulence, velocity probability density functions and Gram-Charlier series coefficients. For the range of depth Reynolds number studied (23×103 < Re h <72×103), the turbulence intensity and Reynolds shear stress profiles show that the effect of Reynolds number can be significant in open-channel flows. However, at identical distances from the bed, the velocity probability density functions are relatively insensitive to Reynolds number effects. The coefficients of the Gram-Charlier series expansion are also independent of Reynolds number for wall normal distances y+ <300. In the case of the flow with the near-wall perturbation, the mean velocity profile at the farthest downstream station more-or-less recovers to the undisturbed state, whereas the turbulence intensity profiles do not completely recover. From the various profiles obtained downstream of the perturbation, the wall-normal distance corresponding to 0.01<y/h<0.1 requires a greater longitudinal distance to recover to the undisturbed state. As noticed from the velocity defect profiles, the effects of near-wall disturbance begin to penetrate into the flow with increasing distance from the perturbation. The presence of higher levels of turbulence influences the skin friction coefficient, the extent of collapse with the log–law and the wake parameter.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".