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Record W2135710804 · doi:10.1109/pes.2004.1373019

Optimization-enabled electromagnetic transient simulation

2004· article· en· W2135710804 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

VenueIEEE Power Engineering Society General Meeting, 2004. · 2004
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsResearch ManitobaUniversity of Manitoba
Fundersnot available
KeywordsEmtpTransient (computer programming)Computer scienceConvertersRange (aeronautics)Power (physics)Electric power systemControl theory (sociology)Mathematical optimizationEngineeringControl (management)Mathematics

Abstract

fetched live from OpenAlex

Summary form only given. Electromagnetic transient simulation programs (EMTP-type programs) are powerful tools for the study of a wide range of power system transient problems. This paper introduces a novel tool in which an EMTP-type program becomes the objective function evaluator for a non-linear optimization algorithm. In this approach, the non-linear optimization program is given control to perform several consecutive runs with a view to minimizing (or maximizing) the desired objective function, which is computed from the results of each simulation run. Since the optimization algorithm strategically selects the parameters for the EMTP run, the overall design process is orders of magnitude faster than that possible from sequential or random (Monte-Carlo type) multiple-runs of the EMTP-type program. The paper discusses the mechanics of the interface as well as design of objective functions. The power of the proposed method is demonstrated through two examples for the design of power electronic converters.

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 score0.758
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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