3-D Modeling of Coils for Pulsed Field Magnetization of HTS Bulk Pellets in an Electrical Machine
Bibliographic record
Abstract
In this paper, we propose to study and design a coil used to magnetize, by means of a pulsed field magnetization (PFM) process, an inductor of a radial flux superconducting machine with one pair of poles. Each pole contains four similar high-temperature superconducting (HTS) bulks of 30 mm diameter arranged in a square pattern. The cryostat already exists for this application and the temperature of the HTS bulks can vary from 4.2 K to their critical temperature, in a transient state. For a given primary source of energy, here a capacitor bank of 10 kJ (5 mF, 2 kV) is available, the PFM process depends strongly on the value of the coil inductance used to generate pulsed field, because it defines the waveform of the current: peak value and time constant. Thus, three-dimensional modeling of the coil is required in order to be sure that its inductance and the magnetic field produced will provide a full magnetization of HTS bulks. From the practical point of view, we would like to achieve an average magnetization of each pole around 3 T. In this paper, numerical modeling of coils with different number of turns coupled with circuit's equations is achieved. The maximum magnetic field obtained on the HTS bulks and estimated magnetization at the top center of each HTS bulk, are presented and discussed.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".