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Record W1963409649

Behaviour of an insulation system in gas groups IIA, IIB & IIC

2010· article· en· W1963409649 on OpenAlexaff
Saeed Ul Haq, Bharat Mistry, Ramtin Omranipour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHigh voltage insulation and dielectric phenomena
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsExplosive materialPartial dischargeIgnition systemStatorEngineeringCorona dischargeInsulation systemReliability engineeringAutomotive engineeringVoltageNuclear engineeringForensic engineeringEnvironmental scienceElectrical engineeringProcess engineeringChemistry
DOInot available

Abstract

fetched live from OpenAlex

Safe operation of electrical rotating machines in explosive gas environments often present in the petrochemical industry is of primary concern. To ensure safe operation of machines in these environments, the working group committees of IEC standards continue to develop state of the art test methods to assure that electric machinery built to these standards will be safe to operate in such crucial environments. Partial discharge (PD) and corona discharge activities are phenomena related to the applied voltage. There are many other design and environmental related factors that can additionally cause variation in the level of corona discharge activity. It is understood that if the PD or corona discharge activity exceeds certain limits, it may ignite a specific explosive gas or vapor of gas as defined in the IEC Std. 60079–15. To understand the behavior of insulation systems in explosive environments, a steady state ignition test also known as an “Incendivity test” was performed on a partially wound stator in gas groups IIA, IIB, and IIC as specified in the IEC standard. The factors contributing to discharge activity and their mitigation are also discussed in this paper.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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
Published2010
Admission routes1
Has abstractyes

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