Effect of Shear Cutting on Microstructure and Magnetic Properties of Non-Oriented Electrical Steel
Bibliographic record
Abstract
In manufacturing electrical machine cores, the electrical steel laminations are often mechanically cut, leading to residual stress and a deterioration in magnetic properties. Several cutting techniques are used in the industry, such as shear cutting, punching, and laser cutting. The influence of shear cutting on the steel microstructure and magnetic properties was investigated in this paper. A single sheet tester was used for the measurements of two different grades of non-oriented electrical steel at different induction levels (0.1-1.5 T) and a wide range frequency (3 Hz-1 kHz). A scanning electron microscope was used for the characterization of the microstructure (grain size) at the cutting edges. The mechanical properties near the edge of the lamination were measured using nanoindentation. An increase in magnetic loss due to cutting was observed to be ~20% for B35AV1900 and ~9% for 35WW300, corresponding to a damaged area extending up to a distance of ~170 and ~140 μm, from the cut edge, respectively.
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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 | 0.000 | 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".