Numerical Analysis of Electrical Parameter Effects on Nanosecond Pulsed Dielectric Barrier Discharge Actuator
Bibliographic record
Abstract
Dielectric barrier discharge (DBD) actuators are devices used for active flow control applications. This paper presents a numerical investigation using a two species fluid model on how varying the electrical parameters of a DBD actuator influence plasma development during the first initial cycles of actuation. Peak voltage amplitudes of 1 - 2 kV are applied sinusoidally with pulse widths of 100 ns and 200 ns to investigate the change in electrical current, plasma length, surface charge accumulation, and charged particle densities. The electrical current magnitude was found to increase with applied voltage and pulse width. All cases produced a current spike during the second cycle before reaching a quasi steady state for the third cycle and onwards. However, increasing the pulse width was found to reduce the current spike observed. When comparing the maximum distance the plasma propagated along the dielectric surface to the applied voltage and size of the pulse width, a near linear relationship was observed. As voltage was increased, the surface charge accumulated on the dielectric was extended further downstream, due to the plasma region propagating further downstream. A similar result was observed for increasing the pulse width. In addition to extending the surface charge further down the dielectric, an increase in peak voltage amplitude increased the magnitude of the surface charge as well. When increasing the voltage amplitude and pulse width, a higher concentration of electrons and positive ions was generated. An electron void was observed to develop for all cases during the end phase of the cycles. The void decreased in size as the voltage level was increased and as the pulse width was increased. The results presented show there is a significant dependency on the supplied voltage amplitude on plasma developed from DBD actuators.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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 teacher head, 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".