Investigation of dredging pattern due to changes in jet cross-section
Bibliographic record
Abstract
Sediment management is a significant part of the decision-making process that hydraulic engineers need to undertake as it has a direct bearing on the environment. Sediment dredging from around intake structures and reservoirs impose a high operating cost. Jets can efficiently remove large quantities of sediment at low operational costs. This study assesses the scouring pattern development by changing nozzle parameters to achieve maximum scouring conditions. Toward this end, scour holes induced by jets generated using the nozzles with four inner angles (30°, 45°, 60°, and 90°) are tested on a cohesionless sediment bed. The experimental results show that the inner nozzle angle, α, and the densimetric Froude number, F 0 , affect the scour pattern. This work illustrates that the scour hole dimensions grow with increasing α and F 0 . Based on the velocity measurements, for the range of jet discharges considered herein, the relative velocity U m / U 0 is increased by 20%–25% for the nozzle with α = 90° compared to the nozzle with α = 30°.
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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".