Numerical study for the computation of critical submergence for side circular intake under uniform flow
Bibliographic record
Abstract
This paper discusses a numerical model study for the simulation of flow characteristics and critical submergence for a laterally placed horizontal circular bottom intake under uniform flow. The proposed model simulates the free surface using the volume of fluid model to check the vortex formation at critical submergence. A new combined approach using phase volume fraction and swirl strength-based vortex identification mechanism is used to compute the critical submergence. The swirl strength-based vortex identification mechanism can show the vortex tube in approach flow with swirl generated at the free surface due to the axial flow withdrawal through side bottom intake at critical submergence. The computational fluid dynamics (CFD) model results were validated using experimental data, which showed a maximum error of less than ±10% in the prediction of the critical submergence. The effect of significant parameters like intake and approach flow Froude number and sill height of intake on the critical submergence is discussed. The results of this study help practitioners to adopt CFD-based numerical modelling for the design of water intakes instead of entirely relying on physical model studies, which require more finance and time.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".