DEVELOPMENT OF A FIELD CONCENTRATOR COIL BY FINITE ELEMENT MODELING FOR POWER EFFICIENCY OPTIMIZATION IN EDDY CURRENT THERMOGRAPHY INSPECTION
Bibliographic record
Abstract
Eddy current thermography is a relatively new inspection technique that takes advantage of the electromagnetic induction phenomenon to generate heat in electro conductive materials during inspection. An interesting advantage of eddy current heating compared to classical optical or ultrasonic heating is that the excitation source is smaller and can be conveniently shaped in order to provide energy efficient localized heating. Such excitation source is more suitable for the development of portable instruments and to perform field inspections. In this paper, finite element modeling (FEM) is used to optimize the eddy current coil configuration in terms of heating power efficiency. The performances of air‐core coils, normally used in eddy current thermography, and a new field concentrator coil are compared and discussed. FEM results demonstrate that the proposed field concentrator coil improves the magnetic coupling with the inspected material and requires less energy than air‐core coils to generate the same temperature variation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".