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Time-Domain Modeling of Transmission Line Crossing Using Electromagnetic Scattering Theory

2020· article· en· W3115417977 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsTransmission lineFinite-difference time-domain methodElectric power transmissionTime domainScatteringSolverComputational electromagneticsElectromagnetic fieldPhysicsPerfectly matched layerMathematical analysisPerfect conductorConductorLossless compressionOpticsComputer scienceGeometryMathematicsAlgorithmElectrical engineeringTelecommunicationsEngineeringMathematical optimization

Abstract

fetched live from OpenAlex

Summary form only given. Classical multiconductor transmission line (MTL) theory, which is employed in electromagnetic transient (EMT) simulators, is built on the assumptions that the wire structure is infinitely long and has a uniform cross-section. Therefore, nonuniformities which occur in physical power systems, such as transmission line crossings, are not represented in classical MTL models. A new transmission line model has been developed to calculate space varying per unit length (PUL) parameter matrices near a conductor crossing using electromagnetic scattering theory. The proposed scattered field transmission line (SFTL) model has been implemented for lossless, frequency independent conductors, that cross each other at a variable crossing angle. A single dimensional finite difference time domain (1D-FDTD) algorithm has been used to obtain the time-domain solution at each simulation time-step. Obtained results have been compared with those from a 3D full-wave electromagnetic solver.

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.

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: none
Teacher disagreement score0.531
Threshold uncertainty score0.648

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)0.0010.000

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 head0.024
GPT teacher head0.271
Teacher spread0.247 · 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