Turbulence structure of non-uniform rough open channel flow
Bibliographic record
Abstract
This paper focuses on the turbulence structure in a non-uniform, gradually varied, sub-critical open channel flow (OCF) on a rough bed. The flow field is analysed under accelerating, near-uniform and decelerating conditions. Information for the flow and turbulence parameters was obtained at multiple sections and planes using two different techniques: two-component laser Doppler velocimetry (LDV) and particle image velocimetry (PIV). Different outer region velocity scaling methods were explored for evaluation of the local friction velocity. Analysis of the mean velocity profiles showed that the overlap layer exists for all flow cases. The outer layer of the decelerated velocity profile was strongly affected by the pressure gradient, where a large wake was noted. Due to the prevailing nature of the experimental setup it was found that the time-averaged flow quantities do not attained equilibrium conditions and the flow is spatially heterogeneous. The roughness generally increases the friction velocity and its effect was stronger than the effect of the pressure gradient. It was found that for the decelerated flow section over a rough bed, the mean flow and turbulence intensities were affected throughout the flow depth. The flow features presented in this study can be used to develop a model for simulating flow over a block ramp. The effect of the non-uniformity and roughness on turbulence intensities and Reynolds shear stresses was further investigated.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".