Seepage effects on turbulence characteristics in an open channel flow
Bibliographic record
Abstract
An experimental study was carried out to understand the effects of seepage on the turbulence characteristics of flow in an open channel. Tests with both suction and injection were conducted covering a range of seepage rates. The tests were conducted at two different flow Reynolds numbers (Re = 31 000 and 47 500). The variables of interest include the mean velocity, turbulence intensity, Reynolds shear stress, shear stress correlation, and higher-order moments. Quadrant de- composition was also used to extract the magnitude of the Reynolds shear stress from the bursting events. The introduction of seepage causes a significant change in the mean velocity profile and the magnitude of this change depends on the seep- age rate. Injection increases the magnitude of the various turbulence parameters and suction reduces the values in compari- son with the no-seepage condition. The introduction of injection increases the bed stability, whereas suction causes a reduction. The effect of seepage on the velocity characteristics is not restricted to the near-bed region but can also be no- ticed near the free surface. The results from the analysis of turbulent bursting events clearly show a distinct effect of seepage well beyond the near-bed region.
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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 | 0.001 |
| 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".