Rigidité diélectrique d'un interface gazsupport avec contaminant métallique dans l'air sec et ses mélanges avec le SF<sub>6</sub>
Bibliographic record
Abstract
In this paper, we conduct a series of experiments aimed at analysing the dielectric properties of compressed dry air, and some SF6air mixtures up to 700 kPa, under application of AC 50 Hz and lightning impulse (LI) 1.2 μs/50 μs voltage. The investigations were carried out by using a cylindrical spacer model with an adhering particle on the surface under homogenous field conditions. We measure the partial discharges (PD) propagation characteristics under LI voltage stress, as well as the PD inception voltage and the flashover voltage for the contaminated particle. We also investigate the surface charge accumulation on the spacer surface under contaminated particle conditions. The results of the experiments reveal the influence a conducting particle has on the determined flashover field strength, for SF6air mixtures compared with pure, compressed dry air. This influence is discussed for different particle lengths, but also for three different particle positions in the gap. Pure dry air achieves a higher dielectric strength when the particle gets into contact with the high voltage electrode, under negative LI voltage stress. The same result is obtained for the SF6air mixtures, when the particle is located in the middle of the gap, as floating electrode on the spacer surface. The reported results contribute to the improvement of the models of breakdown through the interface gassolid isolator. The application of these models should offer the possibility for considering the use of dry air, or its mixtures with SF6 which, normally have a lower relative global warming potential than pure SF6.[Traduit par la Rédaction]
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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 | 0.000 |
| 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 | 0.000 |
| 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".