Large Eddy Simulation of a Three Dimensional Buoyant Jet
Bibliographic record
Abstract
This study is related to the numerical simulations of a three dimensional buoyant jet. The governing equations of the fluid are solved with the help of a buoyancy-extended large eddy simulation (LES) numerical model. In addition, the dynamic procedure is used to evaluate the Smagorinsky model coefficient. The finite difference formulations of the governing equations are split into three parts related to advection, dispersion and propagation. The advection part is solved by the QUICKEST scheme. The dispersion part is solved by the central difference method and the propagation part is solved implicitly by using the Gauss-Seidel iteration method. The initial turbulence of the buoyant jet from the orifice is accounted for by introducing random disturbances to the flowing parameters. Ensemble averaged relationships for the buoyant jet trajectory; jet sizes and concentration dilution are presented. The salient characteristics of the buoyant jet are captured, including variability among different realizations of the buoyant jet, the development of protuberances, the horseshoe cross sectional shape and the hollow trough along the upper surface of the jet. The protuberance characteristic and the asymmetric shape of the jet from the present study are compared with the results from the conventional κ-ε model. The horseshoe cross sectional shape and the trough or bifurcation characteristics are investigated by studying the inner structures of the flow field. These quantitative relationships and qualitative observations are found to be in good agreement with experimental results from an earlier investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".