A flume experiment on the effect of channel width on the perturbation and recovery of flow in straight pools and riffles with smooth boundaries
Bibliographic record
Abstract
The scaling relation between channel width and the spacing of macroscale bed forms has long interested earth scientists and engineers. The current paper conceptualizes flow over such macro bed forms using perturbation theory. The objectives are to characterize the response of flow to pressure gradients that occur in convectively accelerating flow and convectively decelerating flow (CDF), as occurs in pools and riffles, and to determine how the response is modified by the width of the channel. Flume experiments are described that use idealized two‐dimensional bed forms and an inner movable wall to isolate the effect of channel width. Ultrasonic Doppler velocimetry profilers operating at 40 Hz are used to measure velocity. Results show that the recovery of the shear velocity (u*) and Coles wake parameter (Π) follows a simple relaxation response toward uniform flow conditions that is insensitive to channel width, while the lateral concentration of flow (Ψ) and the principal Reynolds stress ( ) occur as two‐stage spreading and relaxation responses that follow a scaling relation on the order of 3–4 times the channel width, or approximately one half of the typical distance between pools. The increases during CDF, precisely in the location where mean bed velocity is at a minimum. It thus appears that hydrodynamic recovery from perturbation helps to explain the sensitivity of the scale of macro bed forms in rivers to channel width. Mobile beds and 3‐D geometries should be tested to verify how mean flow and turbulent scales evolve as linked aspects of a complex response to perturbation.
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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) | 0.001 | 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".