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Record W3157209029 · doi:10.1109/tpwrs.2021.3077391

Hybrid Average-Value/Detailed Modeling of Line-Commutated AC–DC Converters With Internal Faults For Electromagnetic Transient Simulations

2021· article· en· W3157209029 on OpenAlex
Seyyedmilad Ebrahimi, Navid Amiri, Juri Jatskevich

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Power Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicHVDC Systems and Fault Protection
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransient (computer programming)ConvertersComputer sciencePower (physics)Line (geometry)Hybrid systemElectric power systemControl theory (sociology)Electronic engineeringVoltageEngineeringElectrical engineeringMathematicsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

Recently, a hybrid average-value/detailed modeling technique has been presented for efficient electromagnetic transient (EMT) simulation of power systems containing ac-dc line-commutated rectifiers (LCRs). In this letter, the hybrid modeling methodology is extended to consider asymmetrical operation of LCRs due to internal faults of switches. The hybrid model permits large time-steps as opposed to conventional switching models that require precise handling of switching events and respectively small time-steps. The extended hybrid model is also demonstrated to possess numerical advantages over the existing state-of-the-art average-value models (AVMs) of faulty LCRs while providing more accurate results.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.734
Threshold uncertainty score1.000

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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