FDTD Subcell Modeling of the Inner Conductor of the Coaxial Feed: Accuracy and Convergence Analysis
Bibliographic record
Abstract
In this paper, we analyze the method of exciting and truncating the coaxial probe used to excite an electromagnetically coupled patch antenna. The goal of the analysis is to avoid the unstable and unreliable behavior of finite-difference time-domain (FDTD) solution. The model considered here is based on the subcell thin wire modeling of inner conductor of a coaxial probe. Two main categories of structures and excitation models are considered. In the first category, the truncated thin wire is separated from the absorbing boundary by two FDTD cells, for several excitation models and their location along the wire. In the second category, the thin wire is extended into the absorbing boundary, and both the hard and the resistive source models are investigated. The comparison of the results for the two aforementioned categories of the FDTD coaxial probe feeds may be of particular interest to computational electromagnetics community, as it may yield insight into the limitations of the most commercial software packages which do not allow for extension of the coaxial probe model into the absorbing boundary.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".