Experimental Validation of a New Power-Equivalent Magnetic Permeability Model for Induction Heating Applications
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Bibliographic record
Abstract
This article discusses a recently published methodology to determine the time-harmonic (TH) effective magnetic permeability used to simulate induction heating problems comprising non-linear and hysteretic materials. The model and its implementation in a whole multiphysics numerical scheme are first shown and calibrated with temperature-dependent magnetic measurements for simulating the specific behavior of an AISI 4340 working steel piece during the induction heating process. Then, the experimental setup designed to send <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\sim }4$ </tex-math></inline-formula> kW of heating power in steel disks is explained. The setup allows the disks to reach the austenitization and Curie temperature of steel in 30 s. The temperature distributions were measured with an infrared (IR) thermal camera and compared with the simulation both in space and time during the heating. In addition to being numerically inexpensive, the computational model successfully predicts the temperature within 10% of accuracy between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$200 ^{\circ} \text{C}$ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$800 ^{\circ} \text{C}$ </tex-math></inline-formula>.
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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