Design optimization of capacitive bushing using Nelder-Mead method and computer simulations
Bibliographic record
Abstract
This study proposes using the Nelder-Mead method and computational simulations based on the finite element method (FEM) to optimize the capacitive core of an oil-impregnated paper bushing. To this end, a representation of the studied bushing was built using computer-aided design software and simulated in COMSOL Multiphysics®. Its core was designed according to a conventional methodology and the proposed optimized methodology. In the proposed optimized methodology, the number of conducting layers was reduced in order to reduce construction materials, and the Nelder-Mead optimization method was used to adjust the position and length of the conductive layers, having as objective to minimize the maximum axial and radial electric fields in the bushing. As result, the bushing designed using the proposed methodology presented a reduction of 24.9% of the maximum electric field intensity. The results suggest that using optimization methods such as the Nelder- Mead method in combination with FEM-based computational simulations can be an effective tool for the optimization of capacitive bushings, reducing manufacture costs and increasing the power system's reliability.
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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) | 0.000 | 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 | 0.001 | 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".