Comparison between 2D and 3D modeling of an EHV post station insulator equipped with a grading ring
Bibliographic record
Abstract
This paper presents a comparative study between 2D axisymmetric and 3D modeling of an EHV post station insulator equipped with a standard corona ring. The simulations were performed using the FEM commercial software Comsol Multiphysics® and particular attention was dedicated to the presence of two anchors or brackets of the grading ring. These anchors were taken into account in both 2D axisymmetric and 3D models in order to study their influence on the E-field distribution and magnitude closed to the HV insulator. The results obtained highlights the fact that the metallic anchors can have a notable influence on the E-field strength when 3D modeling was used. However, this influence is only limited within the vicinity of the HV electrode and does not extend to the entire potential and E-field distribution along the EHV insulator. The metal anchor tends to decrease the E-field strength closed to the HV electrode, providing a better grading effect. However, as the position is moving away from the metal anchor, the 3D and 2D axisymmetric E-field again becomes the same. This demonstrated that it is not necessary to take into account the metal anchors when 3D modeling of outdoor insulator equipped with grading ring has to be performed. Moreover, the results demonstrated that the creation of a complete electrical link between the grading ring and the HV electrode could result in a better improvement of the E-field strength reduction in the vicinity of the HV electrode.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".