MétaCan
Menu
Back to cohort

Analysis of Power Transformers under Geomagnetically Induced Currents

2023· article· en· W4385934361 on OpenAlexaff
Vahid Behjat, Mohsen Mostafaei, Afshin Rezaei‐Zare, Muhammad Ali Masood Cheema

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsYork University
Fundersnot available
KeywordsGeomagnetically induced currentDelta-wye transformerEnergy efficient transformerDistribution transformerTransformer effectIsolation transformerTransformerRotary variable differential transformerLinear variable differential transformerCurrent transformerTransformer typesElectrical engineeringEngineeringElectromagnetic coilElectronic engineeringVoltagePhysicsMagnetic fieldEarth's magnetic fieldGeomagnetic storm

Abstract

fetched live from OpenAlex

This paper describes the development of a low-frequency model to analyze impacts of Geomagnetically Induced Currents (GIC) on power transformers. GIC causes power transformer core and tank saturation which can conduce to flow of harmonic currents, voltage-control problems, and heating of the transformer internal components, ultimately leading to possible damages and gas relay alarm/operation. To analyze the transformer, first, an accurate low-frequency transient model is developed to allow the flow of GIC in the power transformer windings. The developed transformer transient model is based on the topological representation of the transformer core, flux air paths, and tank and is accurate enough for considering low and mid-frequency transients including GIC. The calculated currents are fed into a Finite Element Model of the transformer developed for the purpose of GIC study in this research work. Utilizing the FEM model, the pattern of electromagnetic flux distribution and hot spots caused by GIC in the transformer core and tank are specified. The extracted characteristic features of the transformer will provide helpful insights into the optimal design and production of power transformers.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.536
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.029
GPT teacher head0.282
Teacher spread0.253 · 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.

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

Citations1
Published2023
Admission routes1
Has abstractyes

Explore more

Same topicMagnetic Properties and ApplicationsFrench-language works237,207