Dielectric material degradation monitoring of dielectric barrier discharge plasma actuators
Bibliographic record
Abstract
It is a known phenomenon that some dielectric materials used to construct plasma actuators degrade during operation. However, the rate at which this process occurs, to what extent, as well as a method to monitor is yet to be established. In this experimental study, it is shown that electrical measurements can be used to monitor changes in the material of the plasma actuators. The procedure we introduce for monitoring the actuators follows from the work of Kriegseis, Grundmann, and Tropea [Kriegseis et al., J. Appl. Phys. 110, 013305 (2011)], who used Lissajous figures to measure actuator power consumption and capacitance. In the present study, we quantify changes in both the power consumption and capacitance of the actuators over long operating durations. It is shown that the increase in the effective capacitance of the actuator is related to degradation (thinning) of the dielectric layer, which is accompanied by an increase in actuator power consumption. For actuators constructed from layers of Kapton® polyimide tape, these changes are self-limiting. Although the polyimide film degrades relatively quickly, the underlying adhesive layer appears to remain intact. Over time, the effective capacitance was found to increase by up to 36%, 25%, and 11% for actuators constructed with 2, 3, and 4 layers of Kapton tape, respectively. A method is presented to prevent erosion of the Kapton dielectric layer using a coating of Polydimethylsiloxane oil. It is shown the application of this treatment can delay the onset of degradation of the Kapton dielectric material.
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 | 0.001 |
| 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 | 0.001 |
| 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".