On the turbulent flow characteristics of wall-attaching synthetic jets at varying offset height ratios
Bibliographic record
Abstract
This study investigates the influence of offset height ratio on the unsteady flow characteristics and coherent structures of wall-attaching synthetic jets using improved delayed detached eddy simulations. The simulations were conducted at a Reynolds number based on the average jet-exit velocity and nozzle diameter of Re=565, with an actuation frequency of 300 Hz. Four offset ratios (G/d=1, 2, 3, and 4, where G is the distance from the nozzle centerline to the bottom wall and d is the nozzle diameter) and a reference free synthetic jet (FSJ) were examined using instantaneous, phase-averaged, and time-averaged statistics, including Q-criterion, vortex-core circulation tracking, and proper orthogonal decomposition (POD). The results show that reducing G/d promotes stronger jet deflection and earlier attachment of the synthetic jet on the wall, leading to the development of a wall synthetic jet. At G/d=1, the vortex rings attach almost immediately on the wall, inducing strong spanwise stretching, vorticity redistribution, and rapid breakdown and decay of the jet. Increasing the offset ratio to G/d=2 delays wall attachment but introduces lower shear layer asymmetry that alters the evolution of the counter-rotating vortex pair. For G/d=3 and 4, the vortex evolution and the flow field are similar to the FSJ and also exhibit self-similarity in the far field. POD analysis reveals that, as the offset height ratio decreases, the strong jet-wall interactions significantly increase the range of turbulent scales, leading to an increased modal requirement in flow field reconstruction.
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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".