Numerical investigation of the velocity and spreading characteristics of non-circular turbulent jets at different Reynolds numbers
Bibliographic record
Abstract
The flow field characteristics of non-circular turbulent jets are investigated numerically. A steady numerical simulation is conducted using the k–ε turbulence model in Ansys Fluent software. A hotwire anemometer is utilized to collect velocity data along the jet centerline for velocity validation. The jet exit Reynolds numbers vary from 200 to 5000, covering both laminar and turbulent regimes. The mean flow field characteristics, such as mean velocity, turbulent intensity, velocity decay, and half-jet spread width, are examined. The simulated results depict that mean velocity profile decay reveals a universal decay pattern, and the lateral velocity distribution shows a top-hat-like velocity profile in the near field. It significantly changed into peak-shaped and parabolic-shaped at a far downstream distance. The turbulent intensity profile reveals that shear layer growth begins near the jet exits, and entrainment becomes strong with the Reynold number. The potential core region increases with Reynolds numbers. The jet spread width shows a linear increment with the jet exit Reynolds number. The presented numerical results agree well with the measured experimental results and are consistent with published data.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".