On the Gassing Behaviour of Synthetic Ester Under Arcing Faults
Bibliographic record
Abstract
In this work, non and aged synthetic esters have been subjected to electrical arcing faults having different intensities. Open beaker thermal aging is performed at $125 ^{\circ}\mathrm{C}$ while the monitoring intervals include 250-aged, 500, 750, and 1000 hours. Arcing fault intensity is realized by performing a repeated number of flashovers in the bulk of the liquid. This includes 30, 60, 90, 120, and 150 repeated breakdowns followed by immediate DGA measurements. This allowed an understanding of the fault gassing behavior at different aging durations and different fault intensities. The degree of degradation is monitored by prominent aging markers, acidity, and interfacial tension in each case. The discussions include digesting the impact of fault gas with degradation at different fault levels and potential correlations for synthetic esters. Appropriate Duval triangle and Duval pentagon methods are used to verify the fault gas diagnostic prediction ability. The results obtained from this study showed that the intensity of the gassing tendency evolves with the degradation rate and is attributable to the intensity of the arcing fault.
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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 | 0.000 | 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".