Numerical simulations of ice-covered EHV post station insulator performance equipped with booster sheds
Bibliographic record
Abstract
The main objective of this paper is to study numerically the influence of addition of 6 booster sheds (BS) to 2 units of EHV porcelain post insulator on their electrical performance under severe wet-grown ice accumulation based on experimental results. The numerical investigations have been carried out during melting period in order to determine the potential and electric field distributions and the voltage drop along the different air gaps resulting from the addition of BS. Numerical simulations were done using the finite element method (FEM). Adding BS helps to created artificially air gaps which length depends on their position along the ice-covered insulator. Numerical simulations have helped to demonstrate that voltage drop repartition along the different air gap is not uniform. In particularly, it was shown that more that 53% of the applied voltage is concentrated along the first air gap closed to the HV electrode, which also the longest. Also, it was demonstrated that numerical simulations can be useful and an interesting alternative to experimental test in order to improve and optimize the use of BS for improving electrical performance of post insulator under severe icing conditions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".