Risk Assessment of Failure of Outdoor High Voltage Polluted Insulators under Combined Stresses Near Shoreline
Bibliographic record
Abstract
The aim of this paper is to investigate the various effects of climate conditions on outdoor insulators in coastal areas as a result of saline contamination under acidic and normal cold fog, determining significant electrical and physico-chemical changes on the insulator surface and considering the effect of discharge current, electric field distribution and surface roughness. To replicate similar conditions near the shoreline, experimental investigations have been carried out on insulation materials with the combined application of saline contamination and acidic or normal cold fog. The test samples included silicone rubber (SiR), ethylene propylene diene monomer (EPDM) and high-density polyethylene (HDPE), which were used as reference. The materials are of the same composition as those used in real-life outdoor high voltage insulators. All samples were aged separately in an environmental chamber for 150 h for various saline contaminations combined with acidic and normal cold fog, and were generated by means of the adopted experimental setup. This analysis represented conditions similar to those existing near the shoreline exposed to saline and acid spray during winter and early spring. Electric field and discharge current along polymeric samples were examined under acidic and normal cold fog. Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopic (SEM) were used to probe the physico-chemical changes on the samples surface and investigate the hydrophobicity recovery property after aging tests. Finally, a comparative study was carried out on polymeric samples before and after being exposed to the acidic and normal cold fog based on the results obtained from the experiment. Research data may provide references for the better prediction of surface degradation as well as for the better material coating and design of external insulation.
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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) | 0.001 | 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 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".