Investigation of electric field effect of bubble defects in XLPE high voltage cables
Bibliographic record
Abstract
High-voltage cross-linked polyethylene (XLPE) cables play a pivotal role in power systems owing to their unique advantages. Nonetheless, during cable operation, small bubble defects can arise from manufacturing imperfections or operational issues. Over time, these defects can distort the electric field within the cable, potentially leading to local breakdowns. To investigate the impact of bubble defects on the electric field distribution within XLPE cables, this study employs the COMSOL finite element software to construct a simulation model. Through this model, we simulate the electric field strength inside the cables and analyze its distribution characteristics. Additionally, we explore the effects of varying bubble sizes and positions on field strength distortion. Our findings reveal that a bubble diameter of 0.5mm in the XLPE cable results in electric field strength aberration. Furthermore, as the bubble size increases, the aberration in electric field strength becomes more pronounced. Similarly, as the bubble moves closer to the core end, the deviation in electric field strength intensifies, leading to a greater impact. The insights from this study offer valuable guidance for the operation and maintenance of actual cables.
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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".