Modelling and Electrothermal Simulation of Temperature Rise in a SF6-Free MV Circuit-Breaker
Bibliographic record
Abstract
Active research for replacement of SF6 is more complex and requires the validation of many criteria to ensure proper operation of the circuit-breaker under normal conditions. Among these criteria, there is the temperature rise of the conductors which must not exceed a limit in accordance with the IEC or IEEE standard. After completion of dielectric type tests, it was proved that pure nitrogen at 2.5 bar can replace SF6 at 1.5 bar in a VOX 38kV outdoor circuit breaker by meeting the dielectric requirements. This article deals with the simulation of the temperature rise in different elements of the circuit breaker with these two gases: SF6 and N2. The coupling of computational fluid dynamics and computational electro magnetics and non-isothermal flow are used to determine the temperature rise of the breaker. Simulation tests were performed at rated nominal current 2000 A, 50 Hz with specifications of IEEE and IEC standards and finally, the requirements were met with SF6 at 1.5 bar whose results are in good agreement with those of the experimental tests carried out and allowing to predict the results with N2 at 2.5 bar with numerical model build. The results with N2 show a better thermal behavior of all the conductors of the breaker than with SF6 and conclude that pure nitrogen at 2.5 bar can replace SF6 at 1.5 bar in a 38kV outdoor circuit-breaker.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".