DIRECT NUMERICAL SIMULATION OF THE GROWTH OF COHERENT FLOW STRUCTURES IN A TRIGGERED TURBULENT SPOT
Bibliographic record
Abstract
Hairpin-like coherent flow structures have been identified as the dominant vortical structures in transitional and turbulent boundary layers and free shear layers. To fully characterize the processes occurring within such flows, it is important to study the growth mechanism of the hairpin vortices, particularly at their early stages of development, and the development of the resultant wave packets containing multiples of these flow structures. The formation of an artificially-triggered turbulent spot in isolation provides a suitable test case to study the mechanism through which a hairpin vortex forms in a shear layer and how the formation of one such flow structure may produce a local flow environment that promotes the creation of similar flow structures in sequence. The present study involves direct numerical simulations wherein an isolated turbulent spot is produced through a perturbation in the form of a pulsed jet ejected transversely through a square orifice in the test surface. The simulated spots compare favorably with spots measured experimentally under similar freestream conditions. Two levels of freestream acceleration−one that is nominally zero and another that is above the typical threshold required for relaminarization−are applied to the flow to assess the sensitivity of the hairpin-like vortical structures to freestream acceleration. Hairpin-like vortices near the spot trailing edge are observed to grow primarily through an instability of shear layers created between high- and low-velocity streaks near the spanwise edges of the spot.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".