Maximizing protection by minimizing arcing times in medium voltage systems
Bibliographic record
Abstract
Arcing faults in the Forest Products Industries are real risks that often lead to severe injuries and fires. From an economic point of view, the consequences due to direct and indirect costs can be extremely high as well. There are various opportunities to prevent arcing faults, but faults cannot be totally eliminated. This is why several approaches to mitigate the consequences of arcing faults have been introduced, especially in the last decade. Several manufacturers have started to produce arc flash protection relays based on optical detection of light energy from an arc event. In most applications, the light information is confirmed by overcurrent information before a trip command is initiated to an upstream current breaking device. The tripping of a circuit breaker, for instance, occurs in only a few milliseconds. In most cases, this seems to be the state-of-the-art technology leading to very reasonable incident energy levels. However, it is essential to be able to minimize not only the thermal impact but the pressure wave as well. This paper investigates technology aimed at maximizing the protection for the pressure wave.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".