Study on characteristics of magnetic memory testing signal based on the stress concentration field
Bibliographic record
Abstract
Metal magnetic memory testing technology has been effectively used in stress concentration areas and micro‐cracks detection of ferromagnetic metal components. However, due to the lack of profound theoretical basis and effective experimental research, the magnetic memory signal characteristics and magnetism quantitative relationship has not yet been determined. In this study, the full electronic potential magneto‐mechanical model is established which is using the norm conserving pseudo‐potential algorithm based on the first‐principle. The quantitative relationship is then calculated between the stress concentration and the magnetic memory signal. The calculation results show that the changes of the wave function, which result from the stress concentration in the solid band, are the fundamental cause of the magnetic memory phenomenon, and atomic magnetic moment, lattice constant and the magnetic flux leakage signal strength linearly changes as a function of stress trend. As the stress concentration reached the critical stress point, the lattice structure was damaged, and the magnetic memory signal had undergone mutation. In this study, the experimental results are consistent with the theoretical calculation results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".