Effect of binding wire on electric field distribution of overhead insulated conductor in distribution network
Bibliographic record
Abstract
Abstract In recent years, the ablation damage of overhead insulated conductor on the top of insulators has posed a threat to the safe and stable operation of distribution network. In this paper, a three-dimensional model including insulator, binding wire and conductor is established in the finite element simulation. Then analyse the influence of the existence of binding wire and the diameter of binding wire on the electric field distribution of conductor. Providing a theoretical basis for the cause and prevention of the ablation damage of conductor insulation layer. The simulation results are as follows: When binding wire exists, electric field distortion will occur in the insulation layer and surface air around the conductor. The maximum electric field intensity of the surface air around conductor reaches 15.5kV/cm, which is about 690% higher than that without a binding wire. The maximum electric field intensity of the insulation layer reaches 4.3kV/cm, which is 980% higher than that without binding wire. In addition, as the diameter of the binding wire increases, the maximum electric field intensity in the insulating layer decreases and the maximum electric field intensity in the air on the surface around the conductor has small change.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".