Forcing term discretization techniques in the external field-to-MTL coupling problems
Bibliographic record
Abstract
In this paper, two, under certain conditions, equivalent models of electromagnetic plane wave coupling to multiconductor transmission lines (MTLs) are described. The ‘frequency-to-time domain’ (FTD) model incorporates the effect of the impinging electromagnetic waves by means of distributed voltage and current sources whose expressions are found through mathematical approximations made in the frequency domain followed by a transformation to the time domain. The approximations were made in order to gain an advantage in computation time in the discrete FTD (DFTD) model. In contrast to this approach, the same distributed sources of the ‘approximate analytic’ (AA) model are derived by directly evaluating the corresponding integral formulas. It is shown that, although the same second-order-accurate discretization technique has been employed to create both the DFTD and the discrete AA (DAA) models, the simulation results are not the same. In the case of the DFTD model, significant numerical error can be seen in the simulation results, whereas the DAA model does not show such a behaviour. It is shown that time averaging of the forcing terms in the DFTD model helps to reduce the numerical errors significantly at no extra computational cost. Copyright © 2001 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".