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Record W4407398864 · doi:10.1049/hve2.70001

Development of a field‐programmable gate array‐based real‐time generic solver for power electronics circuits with arbitrary configurations

2025· article· en· W4407398864 on OpenAlexaff
Yuan Chen, Jiadai Liu, Hui Ding, Yi Zhang

Bibliographic record

VenueHigh Voltage · 2025
Typearticle
Languageen
FieldEngineering
TopicReal-time simulation and control systems
Canadian institutionsRTDS Technologies (Canada)
Fundersnot available
KeywordsElectronicsSolverField (mathematics)Electronic circuitPower (physics)Power electronicsElectrical engineeringGate arrayComputer scienceField-programmable gate arrayElectronic engineeringEngineeringEmbedded systemPhysicsMathematicsVoltage

Abstract

fetched live from OpenAlex

Abstract Using a field‐programmable gate array (FPGA) as the core computational engine, this paper proposes a digital real‐time electromagnetic transient simulator for a generic power electronic system. The LC switching model is employed for constant network conductance representation. The fully paralleled and pipelined design for network solutions and component computation accomplished the highest performance and efficiency on the FPGA. A customised 48‐bit floating‐point data format is proposed to achieve high simulation precision. This dedicated design is necessary for power electronic simulation. A typical power electronic transformer, which is a heavy computation burden for real‐time simulation, demonstrates the effectiveness of the proposed simulator.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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