Experimental Investigation of DBD Plasma Actuators Driven by Repetitive High Voltage Nanosecond Pulses with DC or Low-Frequency Sinusoidal Bias
Bibliographic record
Abstract
Experimental studies were conducted of a flow induced in an initially quiescent room air by a single asymmetric dielectric barrier discharge driven by voltage waveforms consisting of repetitive nanosecond high-voltage pulses superimposed on DC or alternating sinusoidal or square-wave bias voltage. To characterize the pulses and to optimize their matching to the plasma, a numerical code for short pulse calculations with an arbitrary impedance load was developed. A new approach for non-intrusive diagnostics of plasma actuator induced flows in quiescent gas was proposed, consisting of three elements coupled together: the schlieren technique, burst mode of plasma actuator operation, and 2-D numerical fluid modeling. This approach allowed us to restore the entire two-dimensional unsteady plasma induced flow pattern as well as characteristics of the plasma induced force. The experiments and computations showed vortex flow structures induced by the actuator. Parametric studies of the vortices at different bias voltages, pulse polarities, peak pulse voltages, and pulse repetition rates were conducted. The significance of charge build-up on the dielectric surface was demonstrated. Based on the observations, a new voltage waveform, consisting of high-voltage nanosecond repetitive pulses superimposed on a high-voltage low-frequency sinusoidal voltage, was proposed. Advantages of the new voltage waveform were demonstrated experimentally.
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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) | 0.001 | 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".