Temperature Dependence in the Jiles–Atherton Model for Non-Oriented Electrical Steels: An Engineering Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
High operating temperatures modify the magnetic behavior of ferromagnetic cores which may affect the performance of electrical machines. Therefore, a temperature-dependent material model is necessary to model the electrical machine behavior more accurately during the design process. Physics-inspired hysteresis models, such as the Jiles-Atherton (JA) model, seem to be promising candidates to incorporate temperature effects and can be embedded in finite element simulations. In this paper, we have identified the JA model parameters from measurements for a temperature range experienced by non-oriented electrical steels in electrical machines during their operation. Based on the analysis, a parameter reduction has been performed. The proposed approach simplifies the identification procedures by reducing the number of model parameters and does not require any additional material information, such as the Curie temperature. The resulting temperature-dependent JA model is validated against measurements, and the results are in good agreement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it