Path to turbulence in a transitional asymmetric planar wake
Bibliographic record
Abstract
We report on a transitional, high-resolution direct numerical simulation of a temporally developing planar asymmetric wake at Re = 4000 based on the mass flux deficit. The asymmetric wake is formed by a Blasius and a fully turbulent boundary layer on either side of an infinitely thin splitter plate. Such a setup has direct relevance in low-Reynolds number aeronautics where pressure gradients on an airfoil can relaminarize transitional wall-bounded flows, thus generating a half-laminar/half-turbulent wake. The spreading and normalized turbulence intensity of the asymmetric wake are lower than the initially fully laminar wake but greater than the initially turbulent wake. In the far-field, the flow reaches a fully symmetric and nearly self-similar state with a high level of structural organization, originating from the transition of the laminar side. The structures are generated by the mutual interaction of the turbulent/laminar half-wakes. A forcing from the turbulent side accelerates the development of spanwise-organized structures on the laminar side, which evolve and develop a high-level of spanwise coherence. Unlike the classical transitioning wakes, the pairing of the roller is bypassed. Instead, the spanwise-aligned bulges appear from the initially turbulent half-wake. Under the local shear of the Blasius boundary layer, these bulges undergo a “kinking-and-stretching” mechanism similar to that of the mixing layer. The spanwise organization of the structures is maintained far downstream.
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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 | 0.000 | 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".