Modelling and Numerical Analysis for High Frequency Characteristics of Laminated Galfenol Based on Eddy-Current
Bibliographic record
Abstract
Galfenol, a novel magnetostrictive and ferromagnetic material, has been employed in various applications because of the material’s outstanding mechanical properties. For high frequency applications, the energy loss of eddy-current is a critical criterion because this loss not only reduces the power efficiency for Galfenol material, but also rapidly generates large amounts of heat that can destabilize the system. While laminating ferromagnetic material has been proved to be an effective way that minimises eddy-current, the objective of this research is to investigate the laminated Galfenol material’s plausibility in high frequency applications. For the prescribed geometry, an accurate model for the generated eddy-current is derived based on the Maxwell equations. Combining a built magnetic coupled dynamic model, the relationship between the strain response and the applied magnetic field is derived under high frequency conditions. The simulative results of the laminated Galfenol rods are compared to those rods without laminations. The comparison shows that the laminated Galfenol rod exhibits a milder hysteresis than the non-laminated Galfenol rod. Furthermore, the laminated Galfenol rod is able to maintain a high strain output with a broader frequency range compared to the non-laminated Galfenol rod. This work proves that laminating Galfenol rods are capable of restricting the generation of eddy-current and improving high frequency characteristics significantly.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".