Near-field microwave non-destructive testing for defect shape and material identification
Why this work is in the frame
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Bibliographic record
Abstract
Abstract We propose a near-field approach to microwave non-destructive detection and evaluation of defects, which is based on electromagnetic (EM) numerical modeling of the forward problem and on an adjoint-variable approach to the calculation of the response Jacobians of the forward model. The measured response of the structure under test is matched to that of the forward model. The inverse least square problem is solved iteratively by an optimizer. The approach features high computational efficiency due to the use of adjoint-based response sensitivities, which are developed here to handle materials with complex permittivity. It allows the recovery of both shape and material parameters of the defect. Examples of defects in lossy media are considered. The numerical EM analysis is carried out with a frequency-domain solver based on the transmission line method. The initial discretization grid is preserved throughout the optimization iterations. Keywords: Electromagnetic modelingInverse problemsNon-destructive testingOptimizationSensitivity analysis Notes All matrices and vectors are in bold italics. We define the gradient operator as a row operator (Haug et al. Citation1986). When F represents a real function, equation (Equation7) is where R returns the real value of the complex quantity in the brackets. For a real-valued response F, the semi-analytical formula (Equation10) is . The subscripts R and I denote the real and imaginary parts of the complex quantity, respectively.
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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 | 0.001 | 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) | 0.000 | 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