Effect of turbulent coflows on the dynamics of turbulent twin jets
Bibliographic record
Abstract
The impact of turbulent coflows on the dynamics of turbulent twin round jets is investigated experimentally. Parallel twin jets, at three jet spacing values and two Reynolds number/jet-to-coflow velocity ratios, were released into turbulent coflows with two distinct levels of turbulence intensity. Velocity measurements were made using acoustic Doppler velocimetry. An increase in the coflow turbulence intensity leads to an earlier merging and combining of the jets and also accelerates the rate of decay with downstream distance of the mean centerline excess velocity of the jets. The mean velocity on the symmetry line, for different values of jet spacing, ratios of jet exit velocity to coflow mean velocity, and coflow turbulence intensity, is self-similar when scaled by the maximum mean velocity on the symmetry line and the corresponding streamwise distance. Moreover, as the turbulence level of the coflow intensifies, the turbulence intensity along the symmetry line of the jets increases. The longitudinal integral length scale on the symmetry line of the twin jets decreases as the coflow turbulence intensity increases. The energy spectra of the coflowing twin jets show that the turbulence in the coflow transfers the energy contained by the larger scales to the smaller scales at a greater rate than that which occurs for jets in a quiescent background. However, as the jet spacing increases, less energy is transferred to the smaller scales.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".