Heuristic UTD Diffraction Coefficient for Three-Dimensional Dielectric Wedges
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Bibliographic record
Abstract
This article presents a heuristic diffraction coefficient for 3-D dielectric wedges of arbitrary angles. First, the proposed diffraction coefficient is derived for 2-D wedges with soft and hard polarization, by enforcing continuity of the total field at every shadow boundary associated with the multiply reflected fields inside the wedge. The accuracy of the proposed heuristic 2-D solution is verified comparing with the UTD solution derived from Maliuzhinets' exact integration. Then, it is extended to 3-D wedges for arbitrary polarizations and incident/scattered directions by transforming ray-fixed to edge-fixed coordinate systems. The total field predicted using the proposed heuristic diffraction coefficient is continuous for arbitrary angle 3-D dielectric wedges, including interior wedges, and is close to the geometrical optics field far from the shadow boundaries. The proposed method is validated against a Method-of-Moment solution. Finally, we show the method can significantly improve the accuracy of ray-tracing modeling of wave propagation in arched tunnels.
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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)
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Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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