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Record W2007603602 · doi:10.1109/tec.2011.2176128

A Novel Approach to Saturation Characteristics Modeling and Its Impact on Synchronous Machine Transient Stability Analysis

2011· article· en· W2007603602 on OpenAlex
Saeedeh Hamidifar, Narayan C. Kar

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

VenueIEEE Transactions on Energy Conversion · 2011
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSaturation (graph theory)Control theory (sociology)Stability (learning theory)Trigonometric functionsComputer scienceTransient (computer programming)TrigonometrySynchronous motorControl engineeringAlgorithmEngineeringMathematicsArtificial intelligenceMachine learning

Abstract

fetched live from OpenAlex

Saturation in the ferromagnetic core significantly affects the performance of electrical machines. In the performance analysis of electrical machines, an accurate representation of the saturation characteristics in the machine model is important. In this paper, a new trigonometric algorithm is proposed to represent the saturation characteristics of electrical machines based on the measured saturation characteristics data points. This model can be applied to various kinds and sizes of electrical machines. The calculated results demonstrate the effectiveness of the proposed model. This trigonometric model has been applied to a conventional synchronous machine model and extensive stability performance analysis has been carried out. This further reveals the usefulness of the proposed trigonometric saturation model and the importance of the inclusion of saturation in stability analysis.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.650
Threshold uncertainty score0.601

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 head0.028
GPT teacher head0.225
Teacher spread0.197 · 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