Energy-based quasi-static modeling of the actuation and sensing behavior of single-crystal iron-gallium alloys
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
An energy based model [W. D. Armstrong, J. Appl. Phys. 81, 2321 (1997); J. Atulasimha, Ph.D. thesis, Aerospace Engineering, University of Maryland, College Park, MD, 2006] is employed to predict the actuation (λ−H and B−H at various compressive stresses) and sensing behavior (B−σ and ε−σ at various bias fields) of single-crystal FeGa alloys. The significant feature of this formulation is that, in addition to modeling actuation behavior, the sensing behavior can be predicted based on parameters estimated from the actuator characteristics. These predictions are then validated against experimental data for furnace cooled 19 at. % [100] oriented single-crystal FeGa alloys. Furthermore, an attempt is made to couple the energy-based sensing model with a lumped-parameter model that simulates the magnetic interaction between the magnetostrictive specimen and the magnetic circuit comprising the transducer. This enables a prediction of the variation in field through the sample due to changes in reluctance of the magnetostrictive sample with stress, as well as the impact of this variation in field on the B−σ and ε−σ curves. These predictions are benchmarked against experimental data, wherein the bias field varies due to change in sample reluctance with application of compressive stress while the drive current to the transducer is maintained constant.
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