Monitoring the Sol and Gel in Natural Esters under Open Beaker Thermal Aging
Bibliographic record
Abstract
The application of natural ester-based dielectric liquids for liquid-filled transformers is a topic of high concern for transformer owners and utilities. The potential advantages of being biodegradable, high flash point, good dielectric properties, and high moisture tolerance encapsulated natural esters to be a promising solution for transformer insulation systems. Several research reports are affirmative towards the usage of natural esters in transformers. Meanwhile, the poor oxidation stability of natural esters is a challenge that needs to be emphasized. Natural esters develop a polymerized aging product known as gelling under the influence of oxygen. Before gelling occurs, the first thing is to form sol in the bulk of the liquid that influences the liquid viscosity and further accelerates oxidation. Thus, in this paper, a natural ester is subjected to accelerated thermal aging to observe and understand the formation of sol. However, accelerated thermal stressing is continued till gelling is evident in the liquid. The changes in liquid absorbance with aging and the level after which sol is developed is reported. The changes in the viscosity of the natural ester with the formation of sol and gel are also reported. Further, the compositional changes of the liquid that are responsible for the formation of sol are reported using FTIR analysis. Finally, the breakdown failure rate of the completely gelled natural ester is reported to understand the influence of the gelling on the liquid breakdown strength.
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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".