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Record W1981874574 · doi:10.1109/ceidp.2012.6378820

Impact of poor power quality on stress grading system of cable termination

2012· article· en· W1981874574 on OpenAlexaffabout
Utkarsh R. Patel, Shesha Jayaram

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsElectrical engineeringRenewable energyHarmonicsPower cablePenetration (warfare)TelecommunicationsVoltageComputer sciencePhysicsEngineeringMaterials scienceLayer (electronics)Composite materialOperations research

Abstract

fetched live from OpenAlex

Renewable energy penetration is on the rise in the Ontario distribution network. Renewable energy sources such as wind farms and solar PV system have poor power quality, therefore, it is expected that it will hamper the power quality of the grid. The insulation system is vulnerable to the steady state power quality issues. Poor power quality can have adverse effects on cable accessories such as cable joints and terminations. The impact of poor power quality on the SG layer of cable termination and electric field concentration on the surface of cable termination is identified in this paper. In particular, the effect of distorted voltage waveforms on cable termination is studied considering the penetration of odd harmonics from 3rdto 15thharmonic at 10%, 20%, and 30% level. The cable termination is diagnosed with electrostatic voltmeter (ESV) that measures potential on the surface of the cable termination.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.026
GPT teacher head0.325
Teacher spread0.300 · 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 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

Citations2
Published2012
Admission routes2
Has abstractyes

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