The current pulses characteristics of the negative corona discharge in SF<sub>6</sub>/CF<sub>4</sub> mixtures
Bibliographic record
Abstract
Abstract This paper presents the results of numerical investigation of the current pulses characteristics in SF6/CF4 mixtures for the negative point-plane corona discharge. The pressure and the temperature of gas mixtures are 0.4 MPa and 300 K, respectively. The CF4 content varies from 20% to 80%. The 2D axisymmetric geometry with point-plane electrodes is investigated, and the three drift-diffusion equations are solved to predict the characteristics of the negative corona discharge. In addition, Poisson’s equation is coupled with the above three continuity equations to calculate the electric field. In order to calculate the electron impact coefficients, including the Townsend ionization and attachment coefficients, as well as the mobilities and diffusion coefficients for electrons, the two-term Boltzmann equation is solved. The characteristics of three ionic species at five stages of the first current pulse in 60%SF6-40%CF4 and 20%SF6-80%CF4 mixtures are selected to discuss the development mechanism of current pulses. Moreover, the reduced electric field strengths at the corresponding time instants are presented to help understand the discharge process. The current waveform and the total number of three species are compared in all the cases to analyze the effects of the CF4 content on the discharge. The reduced electric field strength is also helpful in understanding the effects of CF4 content. When the CF4 content increases to 80%, the discharge is more intensive and the pulse frequency also increases.
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 | 0.000 |
| 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".