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Record W2013500965 · doi:10.1109/tpwrd.2007.893384

Characteristics of Voltage Swell in Multigrounded Systems

2007· article· en· W2013500965 on OpenAlexaff
Janak Acharya, Wilsun Xu

Bibliographic record

VenueIEEE Transactions on Power Delivery · 2007
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSwellVoltageConductorSoftware deploymentElectrical conductorElectrical engineeringPhase (matter)EngineeringComputer sciencePhysicsMaterials science

Abstract

fetched live from OpenAlex

The effects of multigrounded neutral (MGN) in three-phase distribution systems are not easy to analyze due to the presence of a fourth conductor-the neutral and its multigrounded arrangement. As a result, the mechanism of voltage swell in MGN feeders becomes difficult to understand. The amount of voltage swell in a MGN feeder is affected by unique factors such as the current in the neutral wire and the neutral-to-phase voltage induction. The purpose of this letter is to reveal and quantify all factors that contribute to voltage swell and substation ground potential rise in an MGN system. The results are expected to help utility engineers to understand the impact of MGN on distribution system operations and to assist their deployment of the MGN schemes

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.010
GPT teacher head0.201
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations6
Published2007
Admission routes1
Has abstractyes

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