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Record W2765245069 · doi:10.5539/mas.v11n11p66

PV Improved Power Using Off-Normal Sun Tracking

2017· article· en· W2765245069 on OpenAlexvenueno aff
Musa Abdalla, Hanan Abu Quba

Bibliographic record

VenueModern Applied Science · 2017
Typearticle
Languageen
FieldComputer Science
TopicSolar Radiation and Photovoltaics
Canadian institutionsnot available
FundersUniversity of Jordan
KeywordsPhotovoltaic systemTracking (education)Power (physics)Environmental scienceOrientation (vector space)Maximum power point trackingComputer scienceNormalityWind speedWork (physics)Solar trackerMeteorologyAutomotive engineeringControl theory (sociology)MathematicsPhysicsElectrical engineeringArtificial intelligenceStatisticsEngineeringGeometry

Abstract

fetched live from OpenAlex

Harvested Power from two axes tracking Photovoltaic modules is analyzed and investigated for the objective of enhancing its reduced efficiency in hot to moderate climates. A novel proposed natural cooling of the modules that depends on optimizing the PV different dynamical models is presented. The optimized PV orientation angles for the tracking system revealed that exact normality of the sun rays over the PV module may not be the best setup! The wind speed and direction over the PV impacts the collector’s temperature and consequently the PV efficiency. Finally, the work was verified and validated using real collected data from a weather station in Jordan.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0030.001
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 head0.033
GPT teacher head0.280
Teacher spread0.247 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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