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Record W1980494676 · doi:10.1541/ieejias.130.646

Power Hardware-in-the-loop Simulation of a Gas Engine Cogeneration System for Developing a Power Converter System

2010· article· en· W1980494676 on OpenAlex
Hong Miao, Satoshi Horie, Yushi Miura, T. Ise, Yuki Sato, Toshinari Momose, Christian Dufour

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

VenueIEEJ Transactions on Industry Applications · 2010
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsOpal-Rt Technologies (Canada)
Fundersnot available
KeywordsCogenerationGas engineHardware-in-the-loop simulationPower (physics)Boost converterGenerator (circuit theory)Buck converterElectricityEngineeringBuck–boost converterAutomotive engineeringElectrical engineeringElectricity generationControl engineeringPhysicsVoltage

Abstract

fetched live from OpenAlex

This research focuses on the development scheme of a power converter in a gas engine cogeneration system using a power hardware-in-the-loop simulation. A matrix converter is adopted to substitute a conventional ac/dc/ac converter and transfers three phase electricity to single phase electricity directly. To inevstigate the interaction between gas engine-generator unit and the proposed matrix converter, a power hardware-in-the-loop simulation is carried out, in which a piece of real matrix converter is installed in the simulation loop and interfaces with the numerical model of gas engine-generator unit. Numerical models of gas engine and generator are presented and verified by experiment. The configuration of the power hardware-in-the-loop simulation is described and results are also presented, through which the practical application of matrix converter is well demonstrated.

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: none
Teacher disagreement score0.962
Threshold uncertainty score0.809

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 head0.012
GPT teacher head0.242
Teacher spread0.230 · 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