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Record W4389541073 · doi:10.17118/11143/20864

Analytical and CFD analysis of a heat generator to match a vertical axiswind turbine

2023· article· en· W4389541073 on OpenAlexaffabout
Navid Nazari, Xili Duan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVertical axisVertical axis wind turbineComputational fluid dynamicsTurbineHorizontal axisMarine engineeringWind powerGenerator (circuit theory)MechanicsAerospace engineeringMechanical engineeringComputer sciencePhysicsEngineeringElectrical engineeringPower (physics)Engineering drawingStructural engineeringThermodynamics

Abstract

fetched live from OpenAlex

Abstract: In cold climates, such as in Canada, a major part of consumed energy in the residential sector is in the form of heat, so developing a technology to convert wind energy, which is considered a sustainable resource, directly into heat will be attractive from both efficiency and economic standpoints. In this paper, we apply agitation technology, a widely-used method in industrial processes, to design a heat generator that can directly convert wind kinetic energy into thermal energy using a 12KW vertical axis wind turbine. Furthermore, based on the geometry of an agitator tank, a CFD analysis was performed to predict the flow characteristics. This study considers different flow variables, including radial velocity, turbulent kinetic energy, and turbulent kinetic energy dissipation rate. Moreover, the effect of viscous dissipation on the fluid temperature rise was assessed. The obtained results revealed that the designed agitator perfectly matches a wind turbine operating in a steady-state condition to generate maximum heat energy.

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)0.000
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 score0.078
Threshold uncertainty score0.248

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2023
Admission routes2
Has abstractyes

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