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Record W2000690226 · doi:10.1109/ceem.2006.258096

Electromagnetic Fields of Energized Conductors in Multilayer Soils

2006· article· en· W2000690226 on OpenAlexafffund
Simon Fortin, Yixin Yang, Jianjun Ma, F. Dawalibi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsSafe Engineering Services & Technologies (Canada)
FundersUniversity of British ColumbiaUniversité Laval
KeywordsElectrical conductorConductorSoil resistivitySuperposition principlePermittivityElectrical resistivity and conductivityComputationDipoleElectric fieldMaterials sciencePhysicsElectrical engineeringDielectricEngineeringComposite materialOptoelectronicsComputer science

Abstract

fetched live from OpenAlex

This paper discusses the computation of electromagnetic fields due to energized thin-wire conductors in a horizontal multilayer soil. The computation uses a full wave solution for the Hertz vector potential caused by an electric dipole located in the soil or in the air. The soil layers can have arbitrary resistivity, permeability, permittivity, and thickness. The field generated by a linear conductor is obtained by integrating the contribution of dipoles along the conductor. The field of an arbitrary conductor network is obtained by superposition of the contribution of all the network conductors. Both energized conductors and the calculation points can be in the air or in the soil. Numerical results are shown for several examples using a four layer soil. The results obtained with the new method are in good agreement with the analytical result for a uniform soil results in the limiting case where the resistivity of all soil layers is the same

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.151
Threshold uncertainty score1.000

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 head0.004
GPT teacher head0.203
Teacher spread0.198 · 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 designBench or experimental
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

Citations10
Published2006
Admission routes2
Has abstractyes

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