Effects of upstream and downstream slopes and clay content on levee's breaching by overtopping
Bibliographic record
Abstract
Abstract The present study investigated the effects of clay content and levee's slopes on the breach formation process for levees constructed by both cohesive and non‐cohesive soils. Twelve experiments were carried out and the breach formation of levees was observed by measuring the breach discharge variations and scour topography with time. The initiation of surface erosion was analysed by comparing the estimated bed shear stress and the critical soil shear stress, and the rate of erosion during breaching was estimated by employing the erosion index. The erosion of levees due to overtopping was classified into three regimes of uniform surface erosion, erosion from the toe, and single scour formation. It was found that the upstream levee's slope had negligible effects on the breach process, whereas the downstream slope significantly increased the erosion index. The peak breach discharge increased with increasing downstream slope and it occurred earlier. Experimental results also showed that the peak breach discharge was higher in non‐cohesive levees than the cohesive embankments and it occurred much earlier. Based on dimensional analysis, empirical equations were proposed to predict the breach discharge and the topography of erosion during the breach.
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) | 0.000 | 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".