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Record W2165095692 · doi:10.1109/61.852993

Highly accurate modeling of frequency-dependent balanced transmission lines

2000· article· en· W2165095692 on OpenAlexaff
Christian Dufour, Hoang Le‐Huy

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsTransmission lineEmtpFrequency domainElectrical impedanceElectric power transmissionTime domainCharacteristic impedanceLine (geometry)Transfer functionFourier transformInverseFrequency responseEquivalent circuitFunction (biology)Electronic engineeringMathematicsMathematical analysisAlgorithmPhysicsComputer scienceEngineeringVoltageElectrical engineeringTelecommunicationsElectric power systemGeometry

Abstract

fetched live from OpenAlex

Accurate low frequency time domain response of modally decomposable balanced transmission lines are obtained using a modified Marti line modeling. In the proposed modeling, the low frequency fitting of the characteristic impedance function Z/sub c/ (/spl omega/) is modified to fit the short-circuit characteristic of the line. Time domain simulations using the inverse Fourier transform shows the validity of the procedure. As a result, at the same time that the time domain response of the line is improved, the number of poles used in the analytic approximation of the line functions is lowered by a factor of ten compared with EMTP fitting routines.

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 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 categoriesInsufficient payload (model declined to judge)
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 score0.383
Threshold uncertainty score0.998

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)0.0030.000

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 head0.009
GPT teacher head0.216
Teacher spread0.207 · 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.

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

Citations11
Published2000
Admission routes1
Has abstractyes

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