Modelling of Flow Patterns over Spillway with CFD (Case Study: Haditha Dam in Iraq)
Bibliographic record
Abstract
Spillways are designing to release surplus water over a volume of storage. The excess water flows from the top of the reservoir and is carried back to the river by a spillway. Many radial gates were destroyed under hydrodynamic load. Radial gate connectors are susceptible to fatigue failure due to excessive vibration; therefore, gate vibration during operation must be investigated to confirm safe operation at the design water pressure. Several studies were carried out to analyse and simulation of flow over the spillway. In this article, the flow pattern over the Haditha dam spillway has been simulated using computational fluid dynamics (CFD). The numerical model was performed using Ansys Fluent 2020 R1 to simulate the flow properties; determination of cavitation damage at three discharges corresponding in the design of Haditha dam are 4700, 7140, and 7900 m3/s. In addition to finding the effect of gate vibration under dynamic water loads. The Realisable k-ɛ turbulence model was utilised with the volume of fluid (VOF) model to simulate the interaction between air and water phases. The validation of the numerical model was achieved by comparing it with a physical model. The physical model of the Haditha Dam spillway was made from iron with a scale of 1:110. It has been designed and constructed in a hydraulic laboratory according to the modelling principle of the hydraulic structure. The results showed that a high agreement between the physical and numerical model and the k-ɛ turbulence model could simulate the Haditha dam spillway with low cost and few times. The cavitation damage may occur at the region start at the end of the arching spillway to stretches downstream, and there is no damage of gate vibration under dynamic water load.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".