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Record W2117865362 · doi:10.1109/elinsl.2004.1380655

Optimization of corona ring design for long-rod insulators using FEM based computational analysis

2005· article· en· W2117865362 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsUniversity of Waterloo
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaConsejo Nacional de Ciencia y Tecnología
KeywordsCorona (planetary geology)Finite element methodCorona ringInsulator (electricity)Ring (chemistry)Transmission lineOptimal designSoftwareMaterials scienceMechanical engineeringElectronic engineeringEngineeringComputer scienceStructural engineeringElectrical engineeringCorona dischargePhysicsVoltage

Abstract

fetched live from OpenAlex

The paper presents a method to optimize the location and the dimensions of the corona ring for transmission line composite insulators using finite element based software, FEMLAB. The procedure used to optimize the corona ring design, which handles more than one parameter, has been verified with examples that have an analytical solution or known optimal values. In this work the optimization is based on finding the maximum field along the insulator surface, such that this maximum field is well below the corona inception level. The design parameters of the ring diameter, diameter of the ring tube, position of the ring in its vertical plane, and the maximum field that cannot exceed the corona inception level have been used in the optimization process.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.327
Threshold uncertainty score0.909

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.042
GPT teacher head0.287
Teacher spread0.244 · 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