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Record W2007157848 · doi:10.1109/pcicon.2011.6085858

What does it take to design a low inrush large induction motor?

2011· article· en· W2007157848 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.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsGeneral Electric (Canada)
Fundersnot available
KeywordsInrush currentInduction motorAutomotive engineeringComputer scienceEngineeringVoltageElectrical engineeringTransformer

Abstract

fetched live from OpenAlex

The need for a low inrush A. C. motor is usually based on a weak power system where conventional starters are not desirable. Low inrush motors are often used in marine services like Floating Production, Storage & Offloading (FPSO) and Liquefied Natural Gas (LNG) plants where weight and space is at a premium. They are also needed for pulpwood refiners in paper industry or at remote sites like mining operation where the electrical power system is weak, and there is a concern that a normal inrush motor could create a significant voltage drop causing a negative impact to other equipment in the electrical system. In such cases, a low inrush motor is preferred even though there may be some operating performance drawbacks. Customized low inrush motors are challenging to a machine designer when one is trying to meet application as well as performance requirements. This paper covers all those areas of concern and addresses them in order to design low inrush induction motors.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.118
Threshold uncertainty score0.530

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 communication0.0000.001
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 head0.044
GPT teacher head0.245
Teacher spread0.201 · 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

Quick stats

Citations6
Published2011
Admission routes1
Has abstractyes

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