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Record W6993007704

A NUMERICAL STUDY ON THE FLOW DIVERGENCE AROUND A HIGH SOLIDITY VERTICAL AXIS WIND TURBINE

2019· dissertation· en· W6993007704 on OpenAlexaff

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSolidityTurbineAspect ratio (aeronautics)Tip-speed ratioFlow (mathematics)Reynolds numberVertical axis wind turbineDivergence (linguistics)
DOInot available

Abstract

fetched live from OpenAlex

This thesis reports on a numerical investigation into the three-dimensional flow divergence around a high solidity vertical axis wind turbine. Three-dimensional unsteady Reynolds averaged Navier-Stokes simulations of an H-type vertical axis wind turbine were used to examine the impact of turbine aspect ratio and tip speed ratio on the flow divergence. The turbine height was changed to alter the turbine aspect ratio, while keeping the diameter constant, to ensure that the solidity and tip speed ratio values were comparable between the different aspect ratios tested. The power output of the turbine consistently increased with aspect ratio and the optimal tip speed ratio for peak performance was negligibly affected. The flow divergence results showed that larger aspect ratio turbines had significantly more flow divergence with a 1 m/s entrance velocity difference between the smallest and largest cases. These two results where contradictory as a larger aspect ratio turbine was more efficient even though it had a smaller fraction of the upstream flow entering the upwind pass. The reason for this result was that impact of the tip effects, which caused a power reduction near the end of the blades. The distance from the blade tips that experienced a power reduction was constant for turbines of aspect ratio one and greater, resulting in a smaller turbine having a greater fraction of its height effected by the tips. This caused the overall power output for a smaller aspect ratio turbine to be lower even though its centre performance was higher, due to an increased entrance velocity. The change in flow divergence with tip speed ratio was also examined to better understand the driving force behind the divergence. It was found that the turbine power output was not the direct cause of flow divergence. The blade forces, specifically the force generated in the upstream direction had a strong linear correlation with the upstream flow divergence.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.210
Teacher spread0.194 · 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 source (direct Gemma or distilled Codex), 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
Published2019
Admission routes1
Has abstractyes

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