Integration of Energetic Model for Ferromagnetic Hysteresis in Finite Volume Method for Electromagnetic Field Calculation
Bibliographic record
Abstract
In this article, a coupled algorithm between the control volume method and the hysteresis dynamic energetic model for ferromagnetic hysteresis is presented. To illustrate the dynamic behavior of ferromagnetic materials, the quasi-static model is extended by adding two components to the applied magnetic field “Hedd”, and “Hexc”. The added fields are related to the excess losses and classical eddy losses. Thus, two new supplementary coefficients are added to the model parameters. The determination of those coefficients is attained by measuring the energy density for two distinct frequencies. This model introducing the magnetic induction as an independent variable is presented in order to be directly used in time-stepping finite volume calculations applied to the magnetic vector potential formulation. The calculated results are validated by experiences performed in an Epstein’s frame. To check the effectiveness of this model combined with the control volume method in the time domain, the obtained results are compared with experiments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".