Interactions of large-scale free-stream turbulence with turbulent boundary layers
Bibliographic record
Abstract
The scale interactions occurring within a turbulent boundary layer are investigated in the presence of free-stream turbulence. The free-stream turbulence is generated by an active grid. The free stream is monitored by a single-component hot-wire probe, while a second probe is roved across the height of the boundary layer at the same streamwise location. Large-scale structures occurring in the free stream are shown to penetrate the boundary layer and increase the streamwise velocity fluctuations throughout. It is speculated that, depending on the extent of the penetration, i.e. based on the level of free-stream turbulence, the near-wall turbulence production peaks at different wall-normal locations than the expected location of $y^{+}\approx 15$ for a canonical turbulent boundary layer. It is shown that the large scales dominating the log region have a modulating effect on the small scales in the near-wall region; this effect becomes more significant with increasing turbulence in the free stream, i.e. similarly increasing $Re_{\unicode[STIX]{x1D706}_{0}}$ . This modulating interaction and its Reynolds-number trend have similarities with canonical turbulent boundary layers at high Reynolds numbers where the interaction between the large scales and the envelope of the small scales exhibits a pure amplitude modulation (Hutchins & Marusic, Phil. Trans. R. Soc. Lond. A, vol. 365 (1852), 2007, pp. 647–664; Mathis et al. , J. Fluid Mech. , vol. 628, 2009, pp. 311–337). This similarity has encouraging implications towards generalising scale interactions in turbulent boundary layers.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".