Experimental study on the suspended sediment settlement characteristics and incipient velocity in the straight-line sedimentation basin of the irrigation headworks
Bibliographic record
Abstract
To explore the movement characteristics of sediment-laden flow and the basic settlement characteristics of suspended sediment in the sedimentation basins. The prototype observation of the straight-line sedimentation basin for irrigation headworks on the northern slope irrigation area of Tianshan Mountain was carried out, and analyzed the velocity, sediment content, and particle size in different sections. The results showed that the setting of sediment-blocking weirs was the primary factor affecting the settlement of suspended sediment, flow rate was the secondary factor. The overall trend of the suspended sediment content changed along the path was an oscillating trend. Sediment-blocking weirs had a significant effect on the sand particles, followed by silt particles, and clay particles were almost unaffected. The empirical formula of grouped silt deposition rate of sedimentation basin suitable for the northern slope irrigation area of Tianshan Mountain was obtained by using dimensional analysis method. A comparison of different incipient velocity formulas for fine particles revealed that when particle size remains consistent, higher suspended sediment content further reduces incipient velocity, which affected the size of the cohesive force between the fine particles. The findings from this study provide novel insights into the suspended sediment settlement characteristics in sedimentation basins.
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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 | 0.001 | 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".