Aged oils reclamation: Facts and arguments based on laboratory studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lifetime extension of power transformers is a subject of high importance for electric power systems utilities. The decision of replacing, refurbishing or repairing a service aged power transformer requires considering several factors, especially the cost and time to execute the work. The lifetime of the power transformer being related to the condition of the insulation system; one way of improving the situation is to reclaim insulating oil by Fuller's Earth treatment. This procedure is economically attractive because of increasing prices for both mineral and synthetic transformer coolants, effective cost and environmentally sounds. Reclamation rejuvenates the transformer oil by eliminating contaminants. In this paper, a series of experiments has been performed with service aged oils reclaimed in laboratory conditions. Fast, inexpensive and reliable laboratory testing procedures developed by ASTM (D 6802 and D6181) were also used to monitor decay products as traces impurities. The results obtained in laboratory conditions, indicate that a large number of reclamation passes (around 15 passes) are required to regenerate inservice aged oil to a grade close to new oil. It is also shown that not only the reclamation improves the gassing tendency of oil, but also the type of Fuller's Earth is very important for reclamation process. By upgrading the analytical chemistry of oil, the predictive maintenance of this non-renewable resource is modernized, its cost diminished and the service reliability of transformers enhanced. Currently, Fuller's Earth is only used once. After depletion it must be disposed of in a land fill. By using two organic solvents that are recoverable by atmospheric distillation, it is shown, in laboratory conditions, that this mineral absorbent can be reactivated and successfully reused many times.
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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 | 0.001 |
| 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 it