Stress-Induced Self-Magnetic Flux Leakage at Stress Concentration Zone
Bibliographic record
Abstract
The residual magnetization technique is a new method for detecting stress concentration zones (SCZs) in ferromagnetic materials. Local rising of stress at SCZs, such as cracks, results in the development of local elastic and plastic deformation. The two deformation regimes produce different magnetic characteristics, which have competing effects on self-magnetic-flux-leakage signals. In the present research, samples with three different groove depths were subjected to different tensile stress levels. A surface scanning system was used to record the variation of magnetic signals at grooves of varying depth under steadily increasing stress conditions. The results show that elastic deformation increases peak-to-peak values of normal magnetic components and a maximum gradient of the normal magnetic component in the direction of applied stress, while the development of local plastic deformation reduces signal intensity at groove locations. The magnetic object (MO) model is used to explain the mechanism for excess flux leakage field at SCZs as being due to the conversion of magnetoelastic energy—introduced by the application of tensile stress up to the local yield point—into magnetostatic surface poles that are sensed as an increase in the normal component of leakage.
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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 | 0.000 |
| 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) | 0.001 | 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".