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Best-in-Class Stator Winding Insulation System for Large Rotating Machines with Enhanced Dielectric Performance

2025· article· en· W4413442748 on OpenAlexaff
Saeed Ul Haq, George B. Hanna, Madu TS Moorthy, Muhammad Khan, T. F. Toledo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsStatorDielectricInsulation systemMechanical engineeringElectrical engineeringMaterials scienceClass (philosophy)Electromagnetic coilComputer scienceAutomotive engineeringEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper provides an overview on stringent requirements for stator windings that are used in petrochemical, power utilities and nuclear plants. For nuclear applications, it is critical that a machine must be designed for a Design Basis Accident (DBA), refers to a specific accident scenario that a plant design must consider and prepare for, such as a Loss of Coolant Accident and built to withstand without loss to the systems, structures, and components necessary to ensure public health and safety. Stator winding insulation system can be quite complex due to the interactions of materials and geometry; therefore, testing is the most appropriate method for qualification. For utilities, Petroleum and Chemical Industry standards such as IEEE, IEC and API are followed to qualify a reliable system suitable for service life as specified in API. The proposed insulation systems (Best-in-Class) after going through stringent qualification program are also implemented for services industry with acceptable thermal, electrical and dielectric performance.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.260
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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 designSimulation or modeling
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
Published2025
Admission routes1
Has abstractyes

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