The Influence of Variable Density on Turbulent Wall Jet: A Numerical Comparative Study
Bibliographic record
Abstract
The first objective of this numerical research is to help understand the influence of variable density on the structure of turbulence, through the study of a wall jet, and to validate our results with those of the experimental study of A. Soudani. The source of density variation is the mixture between two different non-reactive fluids, with a fixed temperature and pressure. A mass weighted averaging for different variables is applied to the calculation, using ANSYS FLUENT 15.0 commercial software. The principal experience consists of injecting tangentially and alternatively near the wall a gas (air-helium) different from the external flow, through a slot of height 3mm between two plane walls. Such a process permits to provoke an important density difference. The study reaches the conclusion that turbulence is strong, with a slight increase of velocity near the wall and an evident diminution of skin friction, in the case of light fluid injection. The second aim is to estimate the Kolmogorov and large eddies’ scales to construct LES grid to access instant variables in experience.
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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) | 0.000 | 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 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".