Mean model of the dielectric barrier discharge plasma actuator including photoionization
Bibliographic record
Abstract
Abstract A numerical algorithm is proposed for simulation of the dielectric barrier discharge plasma actuators including photo-ionization. The computational bottleneck related to a very long computing time has been circumvented by suppressing the discharge pulses and proposing a mean discharge model. It incorporates an artificial damping term into the electron transport equation to suppress the formation of pulses, which significantly accelerates the simulation. Based on the fluid description of three generic species: electrons, positive and negative ions, the model accounts for the drift, diffusion, and reaction terms. The reaction coefficients are extracted from the Boltzmann equation considering the local field approximation. A self-sustained discharge is achieved by including photo-ionization during the positive voltage phase, and the secondary electron emission from the metal surface, during the negative voltage phase. The proposed methodology compromises the computational burdens of the first-principle approaches and inadequacy of the simplistic models in incorporating the problem physics. The accuracy of the proposed methodology has been validated by comparing the computational and experimental data for the electrical and flow characteristics of a laboratory actuator.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".