LARGE AND VERY LARGE SCALE STRUCTURES IN THE OUTER REGION OF AN ADVERSE PRESSURE GRADIENT TURBULENT BOUNDARY LAYER
Bibliographic record
Abstract
Elongated regions of low and high momentum have been studied in the outer region of a turbulent boundary layer subjected to a strong adverse pressure gradient. Large sets of spanwise-streamwise instantaneous velocity fields are acquired by PIV (Particle Image Velocimetry) at three wall-normal positions (0.2δ, 0.5δ, 0.8δ) at three different streamwise locations in the adverse-pressure-gradient zone, from downstream of the strong suction peak up to detachment. Low- and high-speed regions are defined based on the fluctuating streamwise component of velocity. A pattern recognition method and a classification scheme are employed in order to obtain certain characteristics of the low- and high-speed u-structures. Like in the case of zero-pressure-gradient turbulent boundary layers, long meandering regions of low and high speed are observed in the outer region of the present flow. These structures are often longer than the 3δ streamwise length of our measurement planes and have dimensions that scale on boundary layer thickness. High- and low-speed u-structures are evenly spaced and their width is generally comparable to those previously reported for such structures in the overlap region of zero-pressure-gradient turbulent boundary layers. The results also show that the adverse pressure gradient not only reduces the frequency of appearance of streaky structures but also shortens them in the lower part of the outer region (at 0.2δ) while in the upper part (at 0.5δ and 0.8δ) their dimensions and arrangement seem to be unaffected by the pressure gradient.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".