Evaluation of two commercial finite element packages for calculating AC losses in 2-D high temperature superconducting strips
Bibliographic record
Abstract
This paper compares the speed and accuracy of two commercial packages based on the finite element method (FEM) for calculating the AC losses in high temperature superconductors (HTS). The softwares investigated in this paper were COMSOL Multiphysics and FLUX 3D (2D module). This choice was motivated by 1) the ability of the packages to model the nonlinear resistivity of HTS (mandatory condition), 2) the possibility to extend the analysis to 3-D in the future, and 3) the possibility to solve the associate thermal problem (with additional modules). Nevertheless, in this paper, the analysis was restricted to 2-D and no thermal coupling. To generate objective comparisons, the base case of a 2-D rectangular strip was considered under three important regimes, i.e. 1) transport current, 2) perpendicular applied field, and 3) both excitations simultaneously. In all cases, the superconductor was modelled with a classical E-J power-law characteristic. The results are summarized in a number of graphics showing the sensitivity of each package to 1) the number of elements in the mesh, 2) the n-value in the power-law characteristic, and 3) the aspect ratio of the strip.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".