Safety Assessment of Irrigation Weirs by Modeling Local Scour Potential Downstream of Energy Dissipator
Bibliographic record
Abstract
The phenomenon of local scour downstream of irrigation weir energy dissipators is one of the basic degradation problems in hydraulic structures on rivers.The hydraulic jump in the stilling basin, which is triggered by flow turbulence due to energy dampening, forms current vortices in horizontal and vertical directions.Eddy currents that are not fully controlled and damped in the stilling basin can cause scouring, especially in the vertical direction just downstream of the energy dissipators construction.Simultaneous accumulation of scour in the long term can endanger buildings around the weir, especially the stilling basin, both downstream wings and the main weir.This paper aims to assess weir safety by predicting scour characteristics under end sill energy dissipators using the hybrid model: HEC-RAS and Scour Empirical Equation.The simulation is carried out on three conditions, namely minimum, average and maximum discharges with input of sediment grain gradations obtained from field measurements.The three types of discharge are obtained from the transformation of daily rainfall into daily discharge using the HEC-HMS Model.The results of scour predictions in the 3 scenarios were compared with the results of scour measurements at the study location.The results of the study indicate that the greatest scour depth at the maximum discharge of almost 1.5 meters has reached the depth of the end sill of the energy dissipator.This prediction result was also verified by the observation scour depth of more than 1.5 meters.Observation results also show that the Energy Dissipator II has collapsed massively both in the center and on the left and right sides of the energy dissipator.Based on the results of the study and investigation, it can be concluded that the weir safety at the study location can be categorized as low with the potential for very large scour.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".