MétaCan
Menu
Back to cohort
Record W2077329790 · doi:10.1109/tpel.2012.2195682

A Comparison of Soft-Switched DC-to-DC Converters for Electrolyzer Application

2012· article· en· W2077329790 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 Transactions on Power Electronics · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced DC-DC Converters
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsConvertersForward converterFlyback converterĆuk converterBoost converterTransformerElectronic engineeringVoltageElectrical engineeringComputer scienceEngineeringMaterials science

Abstract

fetched live from OpenAlex

An electrolyzer is part of a renewable energy system and generates hydrogen from water electrolysis that is used in fuel cells. A dc-to-dc converter is required to couple the electrolyzer to the system dc bus. This paper presents the design of three soft-switched high-frequency transformer isolated dc-to-dc converters for this application based on the given specifications. It is shown that LCL-type series resonant converter (SRC) with capacitive output filter is suitable for this application. Detailed theoretical and simulation results are presented. Due to the wide variation in input voltage and load current, no converter can maintain zero-voltage switching (ZVS) for the complete operating range. Therefore, a two-stage converter (ZVT boost converter followed by LCL SRC with capacitive output filter) is found suitable for this application. Experimental results are presented for the two-stage approach which shows ZVS for the entire line and load range.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.972
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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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