MétaCan
Menu
Back to cohort
Record W2962846149 · doi:10.1109/tpwrd.2019.2930557

Harmonic Analysis of Three-Phase Diode Bridge Rectifiers Under Unbalanced and Distorted Supply

2019· article· en· W2962846149 on OpenAlex
Ameen Hassan Yazdavar, Maher A. Azzouz, Ehab F. El‐Saadany

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 Power Delivery · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of WindsorUniversity of Waterloo
Fundersnot available
KeywordsHarmonicsJacobian matrix and determinantControl theory (sociology)HarmonicHarmonic analysisElectronic engineeringEngineeringDiodeNonlinear systemThree-phaseTotal harmonic distortionVoltageComputer scienceMathematicsElectrical engineeringPhysicsApplied mathematicsAcoustics

Abstract

fetched live from OpenAlex

Developing an effective harmonic power flow tool requires fast and accurate calculations of the harmonics generated by the nonlinear elements. This paper presents a time-domain-based method for obtaining all steady-state characteristic and noncharacteristic harmonics generated by three-phase diode bridge rectifiers, under unbalanced and distorted supply. The developed model is generic and able to address both continuous- and discontinuous-conduction modes with a single formulation. By introducing a virtual resistance on the rectifier's DC side, the model is extended to accommodate any DC-side filter. Further, a unique analytical Jacobian matrix is developed to guarantee a quadratic convergence for the iterative part of the proposed method. The effectiveness of the proposed method for harmonic analysis is confirmed through a comparative evaluation with time-domain simulations using PSCAD/EMTDC.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.615

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)0.0000.000

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 head0.008
GPT teacher head0.206
Teacher spread0.198 · 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