Numerical Modeling of Vertical Buoyant Jets Subjected to Lateral Confinement
Bibliographic record
Abstract
The near-field flow and mixing properties of vertical buoyant jets subjected to lateral confinement are studied numerically for different cases, including different confinement indexes and jet densimetric Froude numbers. The performances of different turbulence models are investigated, such as the standard k-ϵ turbulence model and buoyancy-modified k-ϵ model. The modeled results are compared to previous and present experimental observations. The present paper confirms that the universally accepted model (k-ϵ turbulence model) can be satisfactorily accurate, eliminating the need for an advanced modeling approach, as long as suitable modifications are performed. In contrast to previous studies, which used one single and constant value of Ptr and Pr numbers, the present study links these two numbers to the F number, which is more practical and can produce very good results. This study also makes it possible to roughly quantify the rate at which the jet concentration spread width grows and identify the location where impingement occurs, which enables engineers or researchers to perform a quick estimation of the evolution and profile of a laterally confined vertical buoyant jet.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".