Numerical Impact of Using Different $E$ –$J$ Relationships for 3-D Simulations of AC Losses in MgB2Superconducting Wires
Bibliographic record
Abstract
AC losses in superconductors are generated every time a time-varying current/field is present. Engineers must be able to predict these losses as accurately as possible during the design phase of power applications. The electrodynamics of superconductors can be formulated as a nonlinear eddy current problem in which the resistivity of the superconducting region is a highly nonlinear function of the current density. In 3-D finite-element simulations, it leads to time-consuming simulations and convergence issues. In this paper, we compare two different E-J constitutive equations, namely: 1) power law model and 2) the percolation model (PM), programmed within both the H-φ and T-φ formulations. Based on the 3-D case of a three-filament twisted superconducting wire, the numerical performance of all these formulations/material models is compared in terms of accuracy, computation times, number of time steps, and number of Newton iterations for different relaxation methods. It is shown that the combination of the T-φ formulation and the E-J PM works fine and should be further developed, as it seems to constitute the best modeling option from both a numerical and physical point of view.
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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".