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Record W2536379000 · doi:10.1109/epc.2007.4520363

VRB Modelling for the Study of Output Terminal Voltages, Internal Losses and Performance

2007· article· en· W2536379000 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsMcGill University
Fundersnot available
KeywordsInternal resistanceVoltageState of chargeBattery (electricity)Transient (computer programming)Energy storageScalabilityElectrical engineeringComputer scienceTransient voltage suppressorPower (physics)Materials scienceAutomotive engineeringEngineeringElectronic engineering

Abstract

fetched live from OpenAlex

There is a growing interest in using large scale energy storage in wind systems for power smoothing and energy redistribution. Vanadium-redox batteries are well suited for this type of application because of their high efficiency, high scalability, fast response, long life and low maintenance requirements. This paper looks into determining an appropriate electrical vanadium-redox battery (VRB) model for this type of application. In particular, model details including stack voltage, series resistance, state of charge (SOC) and transients modeling are examined. The model is used to obtain results on the energy content, and terminal voltage profile of the battery. The battery performance is also assessed, including VI transfer characteristic, transient response and efficiency.

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 score0.361
Threshold uncertainty score0.145

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 head0.029
GPT teacher head0.251
Teacher spread0.222 · 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

Quick stats

Citations119
Published2007
Admission routes1
Has abstractyes

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