Estimate of void fraction and air entrainment flux in hydraulic jump using Froude number
Bibliographic record
Abstract
Hydraulic jumps are induced in hydraulic facilities for the purposes of energy dissipation or flow aeration. Presently there is no means for a simple estimate of void fraction distribution and air entrainment flux, without detailed physical modelling. This paper presents a semi-theoretical model to simulate the void fraction and velocity distributions in hydraulic jumps characterized by partially-developed inflow conditions. Relationships were established between the inflow Froude number, jump roller length and key parameters that determine the full expression of void fraction and velocity profiles. The proposed model enables accurate prediction of void fraction, longitudinal velocity, and air flux using the inflow Froude number. The results indicated considerable air flux contribution of free-surface aeration, in addition to the singular air entrainment at the jump toe, for moderate to large Froude numbers. A Froude number between 8 and 9 tended to achieve highest aeration rate with maximum total air flux in the roller.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".