Three-dimensional analysis of dielectric-loaded waveguide discontinuity by edge FEM combined with SOC technique
Bibliographic record
Abstract
In this paper, the application of the edge-based vector finite-element method combined with the short-open calibration (SOC) technique to three-dimensional waveguide discontinuity was presented. This SOC technique is directly accommodated in the FEM algorithm, and is used to truncate the computational domain. The developed FEM algorithm is applied to the modeling of dielectric-filled waveguide discontinuities that can be segmented into two distinct sections: the static model of feed lines, and the dynamic model of circuit discontinuity. The FEM is formulated in such a way that the port voltages and currents are explicitly represented through relevant network matrices. The SOC technique is used to remove or separate unwanted parasitics brought by the approximation of the impressed voltage source, as well as the problem of the resulting consistency between different simulations. Truncation of the computational domain by the SOC technique makes the iterative solvers for large sparse linear matrix equations from the FEM converge much faster than by perfectly matched layers (PML). Results for full-height/partially dielectric-filled waveguide discontinuities are very well compared with available publications. © 2000 John Wiley & Sons, Inc. Microwave Opt Technol Lett 27: 438–444, 2000.
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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 | 0.000 | 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".