A numerical study on the effect of gate configuration on the hydraulic parameters of dam spillways
Bibliographic record
Abstract
• Novel insights on flow depth and velocity variations in single vs. double-gate spillways. • Double-gate configuration leads to more uniform water height across the channel width. • Single-gate setup shows higher flow depth fluctuations, especially in mid-channel. Understanding the importance of hydraulic parameters affecting erosion is crucial for designing hydraulic structures, particularly in open channel spillways. While previous research has studied the impact of hydraulic parameters on the erosion of spillways, limited attention has been given to the specific influence of flow parameters in different gate configurations. To address this issue, our study provides a valuable understanding of the effects of flow depth, average, and maximum velocity variations in both single and double-gate scenarios using numerical modeling. The study utilized the computational fluid dynamics (CFD) software to conduct numerical simulations of the Romaine IV reduced scale spillway. Results show that the gate configuration has a great impact on flow depth and velocity variations. The division of a flow in the double-gate scenario, significantly influences the flow distribution, representing a more uniform water height across the channel width. However, flow depth fluctuations are higher in the single-gate setup, especially in the middle-width section. Furthermore, velocity variations show an important difference in the middle of the channel at the upstream, where the central pier functioning as a gate separator causes a local reduction in velocity, dropping to zero; after this point, the velocity values converge again demonstrating nearly similar values for the two scenarios.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".