Review and Comparison of Hysteresis Models for Magnetostrictive Materials
Bibliographic record
Abstract
The modeling of magnetization in magnetostrictive materials is studied in this article. Magnetostrictive materials elongate in the presence of a magnetic field, and can be useful as actuators. These materials are highly nonlinear, and hence, difficult to control. Accurate models are important to the development of stabilizing controllers with good performance. Here, Terfenol-D, a commonly used magnetostrictive material, is studied. A setup is designed to measure magnetic flux density and stress applied to a Terfenol-D sample. Displacement, electrical current sent to a magnet generating the requested magnetic field, and temperature at different locations are measured. Using experimental data, the Preisach, homogenized energy, and Jiles—Atherton models are evaluated. For each model, the parameters are identified for Terfenol-D. The ease of use and accuracy of these models in the prediction of Terfenol-D behavior are compared.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 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".