Factors Influencing the Optimization of Magnetically Coupled Coil Structures-Analysis and Discussions
Bibliographic record
Abstract
The paper explores the factors influencing the optimization of magnetically coupled coil structures through in-depth analysis and discussions. Optimizing the wireless power transfer system (WPTS) is crucial as it enhances the efficiency, reliability, and overall performance of the system, leading to more effective and sustainable wireless energy transmission solutions. The optimization process involves considering multiple aspects, such as coil structure, configuration, number of turns, coil shape, working frequencies, electromagnetic properties of the medium, and coil distance. To identify the relevant parameters (R, L, C, and G) for a system consisting of two magnetically coupled coils used WPTS, advanced electromagnetic field numerical simulation software is employed. Among the widely utilized software tools for estimating the parameters of electromagnetic systems is the ANSYS Q3D EXTRACTOR, available in both 2D and 3D versions.
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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 | 0.001 |
| 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".