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Record W2085943836 · doi:10.1109/tia.2015.2431639

DC Arc Flash Studies for Solar Photovoltaic Systems: Challenges and Recommendations

2015· article· en· W2085943836 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 Industry Applications · 2015
Typearticle
Languageen
FieldEngineering
TopicElectrical Fault Detection and Protection
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsDatasheetPhotovoltaic systemReliability engineeringHazardAutomotive engineeringArc flashElectrical engineeringPower (physics)Solar energyComputer scienceEngineeringVoltage

Abstract

fetched live from OpenAlex

A dc arc flash hazard exists in solar photovoltaic (PV) power systems, but there is no widely accepted methodology for characterizing the severity of the hazard. Calculation methods have been proposed, and most rely on the nameplate I-V characteristic of the PV modules at standard test conditions to determine the worst case incident energy. This paper proposes to consider other factors in performing a dc arc flash hazard analysis, including possible weather conditions and variations of PV module characteristics from the datasheet ratings. It is recommended to consider two conditions when determining the worst case incident energy from a PV system: 1) the failure of all protective devices to trip within 2 s due to insufficient current and 2) the array output power exceeding the nameplate rating due to technological and environmental factors.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.766

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 integrity0.0000.001
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 head0.090
GPT teacher head0.310
Teacher spread0.220 · 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