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Record W4392873047 · doi:10.14447/jnmes.v27i1.a03

The Impact of Functionally Graded Material Insulator in a Three Phase Gas Insulated Busduct under Protrusion Defect

2024· article· en· W4392873047 on OpenAlexvenueno aff
K. V. Subrahmanyam, K. Mercy Rosalina

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2024
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsnot available
Fundersnot available
KeywordsInsulator (electricity)Materials scienceGas phaseComposite materialStructural engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Regardless of the environment, the power system network must be continuously operational.Current spacer failures of Gas Insulated Busduct (GIB) have been noted as a result of a number of manufacturing and switching faults, including delamination, protrusion, depression, gap, etc.These defects have a severe negative effect on the insulator's surface, which de-energises the gas-insulated busduct device and causes a significant financial loss.For the purpose of studying the electric stress at the Triple Junction, a Functionally Graded Material (FGM) spacer is built for a three phase GIB with protrusion irregularity in this work.The stress is reduced by inserting metal inserts at the end of the zero potential.Functionally graded materials are spatially distributed with numerous filler materials to achieve homogeneous electric field stress by doping them with various permittivity values.The spacer used in the simulation is made to withstand a range of voltages as well as varied FGM gradings.Grading's impact on electric field stress is identified and further diminished with the addition of the MI to the FGM insulator.The outcomes are discussed and analysed to demonstrate how well the proposed spacer works.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.016
GPT teacher head0.285
Teacher spread0.269 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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