Bibliographic record
Abstract
The results of a laboratory study of hydraulic jumps on corrugated beds are presented. Experiments were performed for a range of Froude numbers from 4 to 10. Three values of the relative roughness t/y1 of 0.50, 0.43, and 0.25 were studied. It was found that the tailwater depth required to form a jump was appreciably smaller than that for the corresponding jumps on smooth beds. Further, the length of the jumps was about half of those on smooth beds. The integrated bed shear stress on the corrugated bed was about 10 times that on smooth beds. The axial velocity profiles at different sections in the jump were found to be similar, with some differences from the profile of the simple plane wall jet. The maximum velocity um at any section in terms of the velocity U1 of the supercritical stream was correlated with the longitudinal distance x in terms of L, which is the distance where um=0.5U1, and this relation was the same as that for jumps on smooth beds with the difference that L/y1 was much smaller for jumps on corrugated beds. The normalized boundary layer thickness δ/b, where b is the length scale of the velocity profile, was equal to 0.45 for jumps on corrugated beds compared to 0.16 for the simple wall jet. The results of this study show the attractiveness of corrugated beds for energy dissipation below hydraulic structures.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".