Experimental investigation of the effects of different DBD plasma actuators on the aerodynamic performance of the NACA0012 airfoil
Bibliographic record
Abstract
Abstract This study aims to investigate the flow control performance of linear and serpentine dielectric barrier discharge (DBD) plasma actuators mounted on the leading edge of a NACA0012 airfoil to control flow separation and improve aerodynamic performance. Experiments were conducted in a subsonic wind tunnel at Reynolds numbers of 87 × 103, 131 × 103, and 175 × 103. Velocity profiles in the wake and static pressure distributions over airfoil were measured using hot-wire anemometry and pressure sensors, respectively. All experiments conducted in the different plasma actuation parameters, including wave voltages (6, 8, 10 kV) and wave frequencies (6, 10 kHz), and the optimal combination of V pp = 10 kV and f AC = 10 kHz was identified. The results of several wind tunnel experiments showed that, a substantial increase in the lift coefficient of up to 26.58% and a delay in stall angle of attack up to 4º due to the implementation of DBD plasma actuators. Additionally, the serpentine actuator demonstrated a more significant impact on separation control compared to the linear actuator where the serpentine actuator has controlled the stall phenomenon more effectively in post-stall angles compared to the linear actuator due to generation of 3D structures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".