Study of multipactor suppression of microwave components using perforated waveguide technology for space applications
Bibliographic record
Abstract
With the development of space technology, microwave components with increased power handling capability and reduced weight have been urgently required. In this work, the perforated waveguide technology is proposed to suppress the multipactor effect of high power microwave components. Meanwhile, this novel method has the advantage of reducing components' weight, which makes it to have great potential in space applications. The perforated part of the waveguide components can be seen as an electron absorber (namely, its total electron emission yield is zero) since most of the electrons impacting on this part will go out of the components. Based on thoroughly benchmarked numerical simulation procedures, we simulated an S band and an X band waveguide transformer to conceptually verify this idea. Both electron dynamic simulations and electrical loss simulations demonstrate that the perforation technology can improve the multipactor threshold at least ∼8 dB while maintaining the acceptable insertion loss level compared with its un-perforated components. We also found that the component with larger minimum gap is easier to achieve multipactor suppression. This effect is interpreted by a parallel plate waveguide model. What's more, to improve the multipactor threshold of the X band waveguide transformer with a minimum gap of ∼0.1 mm, we proposed a perforation structure with the slope edge and explained its mechanism. Future study will focus on further optimization of the perforation structure, size, and distribution to maximize the comprehensive performances of microwave components.
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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 | 0.001 |
| 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".