Thickness gauging using a high-temperature electromagnetic acoustic transducer with optimized magnetic field
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An Electromagnetic Acoustic Transducer (EMAT) designed for high-temperature operation has been developed for thickness gauging in extreme environments. A multiphysics approach was employed to design and evaluate the EMAT, combining numerical simulations and experimental validations on both aluminum and steel samples. Results demonstrate that the optimized EMAT generates clear backwall echoes, achieving a signal-to-noise ratio (SNR) of up to 22 dB on steel samples. The presence of a magnetic core significantly enhances the magnetic field, leading to stronger ultrasonic wave generation. These findings validate the potential of the proposed EMAT for high-temperature thickness gauging applications.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it