3D numerical investigation of internal defects in a 28 kV composite insulator
Bibliographic record
Abstract
This paper presents a numerical investigation based on 3D finite element method modeling of a dead-end 28 kV non-ceramic insulator having different internal semi-conductive defects in terms of size and position. All the internal defects were modeled as cylinders of 1.5 mm of radius having different lengths: 15 mm and 30 mm which correspond to 3.5 % and 7 % of the insulator length respectively. The internal defect was positioned close to the HV electrode and in the middle of the insulator (floating potential) at equal distance between the sheds. The simulations have been focused on the modification of the axial and radial E-field components closed to the insulator shank surface as well as at the vicinity of the insulator shed extremity. The results obtained demonstrated that small conductive internal defects (lower than 3.5 % of the insulator length) led to a significant distortion of the axial and radial E-field components at the shank surface. The E-field component distortion obtained for a small defect (floating potential) positioned in the middle of insulator between sheds is detectable at the shank surface but invisible at the shed extremity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".