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Record W2276359731 · doi:10.14288/1.0065023

Modelling of transmission lines using idempotent decomposition

2009· article· en· W2276359731 on OpenAlexaff
Fernando José Marcano

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMathematicsMathematical analysisMatrix (chemical analysis)Transformation matrixTransformation (genetics)Phase (matter)Frequency domainEigenvalues and eigenvectorsTransmission lineTopology (electrical circuits)Computer sciencePhysicsTelecommunicationsCombinatorics

Abstract

fetched live from OpenAlex

The modelling of wave propagation in multiconductor transmission line involves full matrices for the wave propagation and characteristic impedances functions. Modal decomposition, as in the fdLine model in the EMTP, leads to an elegant and numerically efficient solution, even in the presence of frequency dependent parameters. The advantages of modal decomposition are lost, however, when the transformation matrix relating modal and phase quantities cannot be assumed constant and real but is complex and changes with frequency. This is the case, for instance, when there is strong conductor asymmetry in multicircuit transmission lines and cable systems. A number of alternatives have been proposed to solve the problem of frequency dependent transformation matrices: from frequency synthesis of the transformation matrices to working directly in the phase domain. Both of these approaches, however, have drawbacks. Direct synthesis of the transformation matrices with stable rational functions is difficult because the eigenvectors that make up the columns of these matrices are not uniquely defined at each frequency point. Direct phase-domain modelling is also difficult because an N-phase transmission line has N propagation modes and N time delays and the N2 elements of [Aphase] are a combinations of these basic travelling times and modes. The idempotent Line Model (idLine) expresses the line propagation function as a matrix directly in phase coordinates [Aphase] (thus avoiding modal transformation matrices), but the expression is in terms of the N natural propagation modes (thus avoiding mixed-up travelling times). With idempotent decomposition, the line propagation matrix can be written as a combination of the modal propagation functions with the idempotent matrices as weighting factors. As opposed to the eigenvectors, which are defined only up to an arbitrary complex constant, the idempotent coefficient matrices are uniquely defined at each frequency point. In the idempotent line model, each scalar modal propagation function is synthesised in the frequency domain using a rational function approximation for the wave shaping and the mode's travelling time for the wave delay. The elements of the idempotent matrices are relatively simple functions of frequency that can also be synthesised using rational function approximations. The proposed model is very accurate and numerically stable. A number of simulations are presented and comparisons are made between the new model, the traditional fdLine model, and the "exact" solution obtained with the frequency domain program FDTP.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.185
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2009
Admission routes1
Has abstractyes

Explore more

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