Influence of Gelling in Natural Esters Under Open Beaker Accelerated Thermal Aging
Bibliographic record
Abstract
The present work is focused on the oxidation aspects (focused on gelling) of natural esters and its influence on the performance of transformer insulation systems. Even though natural esters are not suitable for breathing units, the scenario considered simulates a defect in the sealing system and thus bringing the liquid in direct contact with atmospheric air. Commercially available natural ester liquids are thermally degraded under open beaker conditions in the presence of cellulose with a controlled aging history. The accelerated aging conditions are maintained until the formation of sol and gel is evident in the bulk of the liquid. Later, the insulating liquids and insulating papers are analyzed to understand the behavioral impact of sol and gel on the insulation. The discussions in this article are supported by the physicochemical and electrical characterizations of the degraded liquids and papers. The characterizations include Fourier transform infrared spectroscopy (FTIR), ac breakdown voltage (BDV) failure probability rate, X-ray diffraction (XRD), degree of polymerization (DP), and viscosity. It is found that before the formation of gelling, sol is witnessed in the bulk of the liquid. The presence of the sol highly influences the viscosity of the liquid and aids in rapid acceleration of the oxidation process. It is understood that that the gelling phenomena in natural esters do not have a noticeable impact on the liquid BDV failure rate and paper degradation.
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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) | 0.000 | 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".