Study of the impact of photoionization on negative and positive needle-plane corona discharge in atmospheric air
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Bibliographic record
Abstract
A 2D axisymmetric model of the atmospheric pressure needle-plane corona discharge incorporating the photoionization phenomenon is presented in this paper. The photoionization model was developed using a three-term exponential approximation based on a model suggested by Bourdon et al. The coefficients of the photoionization model were tuned by reproducing the results of a positive corona discharge and comparing them with the experimental data published previously in the literature. In fact, this photoionization model is an essential module for studying a self-sustained positive corona discharge. Incorporating the photoionization phenomenon in the numerical model for the negative corona discharge causes an average of 5% increase in both the frequency and the DC current of the discharge. The relative importance of the photoionization in both positive and negative coronas was put in a quantitative frame by introducing the ratio of the integral of the impact ionization source term (IIS) divided by the Integral of the photoionization source term (IPS). With the help of this ratio and the spatial distribution of the two source terms, the minor role played by the photoionization source term for the negative discharge is justified. In the case of the positive discharge, the vital importance of the photoionization for sustaining the discharge is explained. Moreover, for the negative corona discharge, comparison of the ratio of the secondary emitted electrons (SEE) from the cathode surface divided by the IPS, at different instants of the formation of a Trichel pulse was found to be beneficial for the purpose of evaluating the relative importance of the photoionization. It is concluded that, although SEE on the rising edge of the Trichel pulse is smaller than the IPS since the injected electrons from the cathode surface are generated in the area with the strongest electric field, they have a greater contribution to the discharge current.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it