Effect of Room’s Temperature and Electrode Gap on Current of Negative Corona Discharge in Rod-Plane Electrode Configuration
Bibliographic record
Abstract
The stable corona discharge is widely used in filtration and electrostatic separation in recent years, and several models have been used by researchers to analyze one of its most important properties which is the current-voltage characteristic. The aim of this paper is to investigate the influence of ambient temperature and electrodes’ gap on negative DC discharge using rod-plane geometry, and the Townsend formula was found to be most appropriate model (I=K.V.(V-V0)). The experimental results show that for the same voltage level applied to the high voltage electrode, the discharge current rises with increasing temperature and decreases as the electrodes’ gap increases. Using curve fitting, it was proven that the geometric factor K is proportional to temperature and to the power of the distance between electrodes independently, and the threshold voltage V0 is proportional to the product of the temperature reciprocal and the power of the inter-electrode spacing. From these results, a new modified Townsend formula by introducing the air temperature and the distance between electrodes is proposed to calculate the discharge current with an accuracy of ±10%.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".