Topology Optimization of Coaxial Magnetic Gear based on Reluctance Network Analysis
Bibliographic record
Abstract
Coaxial Magnetic Gear (CMG) can transmit torque between an input and an output shaft without mechanical contact. The pole pieces in the middle rotor play a role in flux modulation. The geometry of the pole pieces affects the torque transmission capabilities and is one of the most challenging and crucial aspects of CMG design. Benefiting from the development of topological optimization methods for designing magnetic devices, we investigate the optimal material distribution in the middle rotor of a CMG. The topology optimization aims to create a meaningful geometry with improved performance (increased volumetric torque density, reduced torque ripple). Finally, the optimized result suggests a curved shape along both side boundaries of pole pieces and small holes on the boundaries close to the inner rotor. The parameter and performance are evaluated by the Reluctance Network Analysis (RNA), which accounts for magnetic material nonlinearity.
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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) | 0.002 | 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 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".