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Record W2148006771 · doi:10.1109/tdc.2001.971317

Computation of power line structure surge impedances using the electromagnetic field method

2002· article· en· W2148006771 on OpenAlexaff
F. Dawalibi, W. Ruan, Simon Fortin, Jianjun Ma, W.K. Daily

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsSurgeSoil resistivityCharacteristic impedanceElectrical impedanceSurge arresterGroundTransmission lineElectromagnetic fieldElectric power transmissionElectrical engineeringWave impedanceWaveformPhysicsEngineeringAcousticsVoltage

Abstract

fetched live from OpenAlex

The power line structure surge impedance is computed using an electromagnetic field approach for various transmission and distribution line structure configurations (ranging from a single wood pole to lattice steel towers) including their grounding systems. The influence of the soil resistivity and different grounding system configurations on the structure surge impedance has been studied. The structure surge impedances are computed for three impressed surge current waveforms: (a) step current wave; (b) ramp current wave; and (c) typical double-exponential lightning surge current. The computed surge impedances using the electromagnetic field approach are compared with those obtained using formulae based on a geometrical model of the power line structure. It is shown that the computed values based on the electromagnetic field theory are, to various degrees, different from the values computed using the formulae based on the geometrical model of the structure. The study also reveals that: (a) the surge impedance of a lattice steel tower decreases only slightly when the soil resistivity is increased from 0.1 /spl Omega/-m to 500 /spl Omega/-m; and (b) when the footing resistance is held constant, the surge impedance of a single pole changes by about 5%, when counterpoises instead of rod clusters are used.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.484
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)0.0020.000

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 head0.268
Teacher spread0.255 · 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

Citations16
Published2002
Admission routes1
Has abstractyes

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