Investigation Into the Effects of the Reflection Phase Characteristics of Highly-Reflective Superstrates on Resonant Cavity Antennas
Bibliographic record
Abstract
First we describe two frequency selective surfaces (FSSs), one capacitive and the other inductive, that are designed to exhibit identical high-reflection magnitude at an arbitrary frequency. These two FSSs are then employed as the superstrate of two RCAs having identical microstrip patch source. In order to determine the resonant conditions and obtain approximate values for the antenna directivity, RCAs are initially analyzed using the well known simple ray-tracing method. Next, a full-wave analyzer (ANSOFT Designer v4.0), based on the method of moments (MoM), is utilized to thoroughly analyze the RCAs. Experimental results are provided to support the full-wave simulations, as well. In contrast to the prediction of the ray-tracing modeling, which is merely based on the reflection magnitude of the FSSs, it is pointed out that their phase properties have noticeable effects on the RCA gain. Second, two other RCAs are designed based on high permittivity and high permeability superstrates with identical contrast. There, too, it is shown that the reflection phases of the RCA superstrates determine the air-gap heights which in turn affect the RCA gains.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.001 | 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".