The effect of the geometric features of the turbulent/non-turbulent interface on the entrainment of a passive scalar into a jet
Bibliographic record
Abstract
We consider the scalar concentration field in the proximity of the turbulent/non-turbulent interface (TNTI) of a round momentum-driven turbulent jet at Re = 10 600. Orthogonal cross sections of the jet are taken at 50 nozzle diameters from the nozzle exit using planar laser-induced fluorescence. The conditional scalar concentration is evaluated along the interface-normal direction, identifying the thickness of the TNTI region as 0.64λ (where λ is the Taylor microscale). Conditioning the scalar concentration within the TNTI revealed higher values of the passive scalar in the vicinity of the boundary elements shaped by large vorticity structures, i.e., isosurface points with low curvature (flat regions), small interface angle, and large radial distance from the jet centerline. In contrast, small vorticity structures near the boundary manifesting with high interface curvature, high interface angle, and small radial distance are associated with lower concentration values. Using the current experimental resolution, we find that high concentrations near the far boundary points persist up to a distance of 0.40λ–0.48λ into the TNTI region, after which boundary points closer to the jet centerline exhibit larger concentration values along the interface-normal direction, similar to the fully turbulent region. The cross correlation analysis showed that in regions characterized by low streamwise momentum, there are positive, albeit small, scalar correlations between the non-turbulent and the TNTI regions. The latter may imply local detrainment of the fluid particles containing the scalar at far radial positions.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".