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Record W2158262239 · doi:10.1115/1.2213271

New Spatio-Temporal Wind Exergy Maps

2006· article· en· W2158262239 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Energy Resources Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsOntario Tech University
FundersNatural Sciences and Engineering Research Council of CanadaIstanbul Teknik ÜniversitesiUniversity of Ontario Institute of Technology
KeywordsExergyWind powerEnvironmental scienceWind speedTurbineMeteorologyEnergy (signal processing)Atmospheric sciencesMarine engineeringEngineeringGeologyGeographyMathematicsAerospace engineering

Abstract

fetched live from OpenAlex

In this paper, energy and exergy characteristics of wind energy are investigated. The effects of wind speed and air temperature and pressure at the inlet of a wind turbine on windchill temperature are examined. We also investigate energy and exergy efficiencies of the wind energy generating system and verify the models through a case study on a 100 kW wind generating system for 21 climatic stations in the province of Ontario, Canada. New energy and exergy efficiency maps of the wind energy generating system are introduced to provide a common basis for regional assessments and interpretations. These efficiency maps are plotted for 4 months of the year (January, April, July, October), which are taken to be representative months of the seasons. The results show that aerial differences between energy and exergy efficiencies are approximately 20%–24% at low wind speeds and approximately 10%–15% at high wind speeds.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.486
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.004
GPT teacher head0.188
Teacher spread0.183 · 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