Investigation of pulsed direct-current plasma jets in a turbulent boundary layer
Bibliographic record
Abstract
Characteristics of the plasma jet produced by a pulsed direct-current (pulsed-DC) dielectric barrier discharge (DBD) and its interaction with a turbulent boundary layer (TBL) are investigated in detail using stereo particle imaging velocimetry. Quiescent-flow characterization results show that a positive starting vortex and a negative near-wall jet structure are induced by the pulsed-DC DBD plasma actuator. With increasing pulse width and discharge frequency, the jet velocity magnitude increases monotonously, as a direct result of the extension of fluid particle acceleration time. During the interaction with a cross-flow TBL, two streamwise vortices with opposite signs are observed at the two sides of the electrode junction, which essentially originate from the starting vortex and negative jet in quiescent air. The skin-friction drag variations are dominated by the cross-stream momentum transportation of streamwise vortices, with drag reduction in the vortex upwash zone and drag increase in the downwash zone. Compared with the conventional alternating-current DBD plasma actuators, the turbulent fluctuations produced by pulsed-DC DBD are much higher, which also affects the skin-friction drag. Further proper orthogonal decomposition (POD) analysis reveals that two distinctly different flow patterns are produced by pulsed-DC DBD working at small and large pulse widths. The dominant POD modes causing the most velocity fluctuation are the spanwise translation and deformation of plasma-induced streamwise vortices. These results provide insights into the basic phenomenon of pulsed-DC plasma jets in cross flow, which recently has demonstrated its promising applications in turbulent skin-friction reduction.
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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".