Numerical Study of the Influence of Material Properties on Pulsed-Field Magnetization for HTS Bulk Magnets
Bibliographic record
Abstract
To optimize pulse field magnetization processes for high-temperature superconducting (HTS) bulk magnets, it is important to control the magnetic field amplitude and the driving temperature. Many publications have reported on the experimental and numerical results of the pulsed-field magnetization method. In the numerical method, the HTS bulk properties are modeled to simplify the calculations, examples being the Bean model and the Kim model, etc. During pulsed-field magnetization the critical current density in the HTS bulk changes dramatically due to the magnetic field and temperature rise induced by the ac losses. For these reasons these properties are key to the analysis of the pulsed-field magnetization process, which is calculated using the measured practical HTS bulk properties, and these results show different temperature rise and trapped magnetic field characteristics. We assumed that HTS bulk has intrinsic deterioration in practice. Therefore, we recalculated using the adjusted parameters, and these analytic results correspond with the experimental results.
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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 | 0.001 |
| 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".