A Novel Scaling Process for the Computation of Multiconductor Transmission-Line Modal Properties Using the Basis Invariance of Total Current and Power
Bibliographic record
Abstract
It is generally regarded that some properties of the characteristic modes of multiconductor transmission lines, such as per-unit-length impedance, admittance, or characteristic impedance, cannot be meaningfully computed analytically. This inability arises from the nature of the definition of the modes – sets of relative voltages and/or currents – which in the prevailing understanding may be arbitrarily scaled. Several methods with which to compute scaling factors have been proposed, but often – and as demonstrated in this work – the results of these processes do not agree with values determined directly from field quantities or experiments. This work begins by examining several facets of multiconductor-transmission-line modes under the approximation of ideal TEM propagation: firstly, that transmission-line modes are normal, and secondly, that as a result of possessing this property, it is postulated that total currents in the terminal domain may be directly equated to those in the modal domain. It is then shown that these relations allow the scaling factors to be determined to within a sign, and as a result, modal properties may be directly computed. This technique allows for the extraction of the modal transmission-line properties for any arbitrary system of conductors. Multiple examples are studied numerically, in which it is shown that the proposed process results in much stronger agreement with field solution than other proposed processes, and further validation of the proposed process is provided though experimentally obtained data.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".