Incipient Motion of Bed Material in a Channel with Varying Width and Vegetated Channel Walls
Bibliographic record
Abstract
This experimental study aims to investigate the characteristics of turbulent flow in channels with vegetated banks and varying channel width under the condition of the incipient motion of bed material. The natural reeds were used as emergent vegetation on the sidewalls of a laboratory flume. In total, nine experimental runs have been conducted with different experimental setups by using three different particle sizes of bed material and three different channel bed slopes. An Acoustic Doppler velocimetry (ADV) was used to acquire velocity components in three directions. The results of this study indicate that the streamwise velocities have the maximum and minimum values at the cross sections with the narrowest and widest width, respectively. When the aspect ratio is less than 5, the maximum velocity occurs below the water surface, due to presence of the secondary currents. It is found that, at all measurement points, the distribution of the Reynolds shear stress has a Z-shaped profile owing to presence of vegetation on the channel sidewalls. By extrapolating the profiles for flow velocity and Reynolds shear stress towards the surface of the channel bed, the near-bed incipient velocities and the corresponding shear stresses for the incipient motion have been determined. By increasing the channel bed slope, the estimated near-bed parameters for all particle sizes decreased, indicating the dominance of the gravity effect over the pressure gradient effect. It was also observed that the Shields method was invalid for assessing the incipient motion of bed material in the presence of vegetation on the sidewalls of a channel that has a varying width.
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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 | 0.000 |
| 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 | 0.000 |
| 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".