Towards Fractal Antennas: A multiband Sierpinski Triangle (Gasket) Fractal Vivaldi Antenna
Bibliographic record
Abstract
Using Sierpinski Triangle Fractals (STFs), a revised Vivaldi antenna with multiband coverage is presented. This report explains how fractal itera-tions can be increased to increase the impedance bandwidth and create new bands for multiband applications. A study has also shown that radia-tion patterns that resemble Euclidean shapes remain the same as their fractal iteration increases. The purpose of this study is to address a series of issues, including improvements in the impedance bandwidth, radiation properties, and a comparison between the simulated and measured re-sults throughout the entire document, as well as the summary of findings within the report. Using fractal-structured Sierpinski gaskets in the feed line of the Vivaldi antenna, this project introduced a new method of feeding the antenna by using fractal structures Sierpinski gaskets. This project introduces a unique feeding method that was never discussed previously and is being tested for the first time. Using this method, a significant amount of work was accomplished in designing and optimizing the radial stubs of the antenna feeding lines for the Vivaldi antenna. It is designed so that when a feed line's central frequency corresponds with an antenna's bandwidth, its radial stub works as a short circuit termination. It transfers energy to its slotted line when its center frequency corre-sponds with the antenna's bandwidth. The radial stub in the feed line of the Vivaldi antenna is usually designed this way and is typical of how it is usually constructed. Using the fractal patch method, as antenna band-width is moved away from the central frequency of the antenna, the di-mensions of the radial stub will change in relation to the wavelength as the antenna bandwidth is moved away from its central frequency. As a result, the radial stub will no longer function as a short circuit termina-tion, and as a result, the antenna will no longer function as an antenna. Consequently, the antenna's slotted line cannot transfer a sufficient amount of energy into the slotted line, which results in a reduction in ef-ficiency. Based on this study's results, the main problem with this meth-od is that the radial stab of the feed line has only one resonance frequen-cy. The following report sums up my research from the NAMRL research laborato-ry as part of my master's studies [1].
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".