Dielectric behavior of transformer oil when contaminated and/or fortified with nanoparticles
Bibliographic record
Abstract
Liquid insulation, a key element in the transmission and distribution of electric power, guarantees safe operation from power transformers, cables, circuit breakers etc. by successfully transferring heat from the equipment as well as acting as the electrical insulating medium. In liquid insulation, mineral oil is widely used as an insulating medium in power industries. In the first part of this research project the impact of the aging of mineral oil on partial discharge is investigated as well as on other chemical and physical properties. For different accelerated aging times, different experiment are set up so that the aforementioned impact is measured along with several other parameters. Investigations are also performed on new oil to provide baseline comparison. The aim of this part of the research is to find relationships between partial discharge inception voltage (PDIV) and the other parameters of oil to do a suitable interpretation between them during aging time. Recently, interest has been growing in enhancing the insulating properties of mineral oil by adding nanoparticles. The literature survey revealed the promising impact of TiC>2 nanoparticles. In the second part of this project, the dielectric performance of mineral oil was therefore investigated by adding different concentrations of TiO2 nanoparticles (from 0.003 g/ml to 0.01 g/ml) using ultrasonic methods. All the investigation tests were performed at different temperatures ranging from -47 to 47°C to correspond with environmental temperature changes in Canada. The results were compared in terms of breakdown and dielectric properties, such as permittivity and resistivity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".