Optimal Coil Design of an Electromagnetic Actuator Using Particle Swarm Optimization
Bibliographic record
Abstract
This paper aims to reduce the heating of the electromagnetic actuators of a magnetic bearing. The electrical current of the coils was above normal, so the need for a new coil design to reduce heating due to high currents. In this scenario, the proposed methodology allows minimizing copper losses using Particle Swarm Optimization, so that the best result of the design parameters will be used in the construction of the new coil for the actuator. For the development of this work, it was decided to use a computational tool for public use, FEMM (Finite Element Method Magnetics) to simulate the electromagnetic device. In the simulations, the densities of magnetic fluxes in the core and in the air gap are shown, as well as the energies, electromagnetic forces and losses in the copper of the electromagnetic actuator winding. Finally, an optimal model of the actuator is obtained through the use of optimization techniques. Therefore, the results obtained demonstrate that the proposed methodology is configured as an interesting strategy for the purpose of this work.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".