Finite-Difference Time-Domain Modeling of Periodic Guided-Wave Structures and Its Application to the Analysis of Substrate Integrated Nonradiative Dielectric Waveguide
Bibliographic record
Abstract
The finite-difference time-domain (FDTD) method incorporating an equivalent resonant cavity model is presented for the modeling and analysis of guided-wave propagation characteristics of complex periodic structures. By transforming electromagnetic field variables into a new set of periodic variables, which can also be resolved from the Maxwell's equations, one can convert a periodic guided-wave problem into an equivalent resonator problem. Thus, the FDTD method used for a resonant cavity problem can be adopted to simulate periodic guided-wave structures. In addition, the proposed FDTD algorithm can be extended to model lossy periodic propagation problems. In this study, the substrate integrated nonradiative dielectric waveguide, which is a special type of periodic guided-wave structure subject to a potential leakage loss due to its periodic gaps, is investigated as a showcase. The proposed method is first validated and is then used to analyze the guided-wave characteristics of substrate integrated nonradiative dielectric waveguides. It is shown that the substrate integrated nonradiative dielectric waveguide structure, which can easily be fabricated in planar form, has a well-behaved propagation property suitable for high-performance millimeter-wave circuit design.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".