Air-core vortex formation in a draining reservoir using smoothed-particle hydrodynamics (SPH)
Bibliographic record
Abstract
Vortex formation under unsteady flow conditions in a draining reservoir is studied. Considering the capabilities of mesh-free Lagrangian numerical methods in the simulation of highly deformed free surfaces, the smoothed-particle hydrodynamics approach is employed. The results of this numerical model are validated with the experimental data of the current study, including the depth over the intake at which vortex forms (critical submergence) and the velocity field. Experiments were also conducted in a rotating cylinder while water was draining from an outlet at its bottom center. The particle image velocimetry technique was used for measuring the velocity field in planes perpendicular to the vortex axis. The numerical results including the velocity distribution and water level variations as well as the depth at which an air-core forms were in acceptable agreement with the experimental data. In addition, vortex formation and the corresponding velocity and pressure distribution as well as the streamlines are analyzed based on the numerical results. The results indicate that as the flow depth decreases, high values of vorticity and low pressures are generated at the vicinity of the outlet, and over time, the generated vorticity develops in depth toward the free surface, and an air-core vortex forms.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".