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Wake Analysis of a Freewheeling Vertical Axis Hydrokinetic Turbine in Aquatic Environment

2024· article· en· W4402156861 on OpenAlexaff
Abbas Dharamsi, Ishan Tandon, Ibrahim Aqdiam, Eric Bibeau

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsWakeTurbineMarine engineeringEnvironmental scienceAerospace engineeringEngineering

Abstract

fetched live from OpenAlex

Hydrokinetic turbines are a promising form of renewable energy, offering sustainable power generation. The aim of this study is to investigate the behavior of such turbines under real-world conditions, giving insights on flow and turbulence patterns in aquatic environments. Continuous field velocity measurements were performed to examine the behavior and impact of a 25 kW vertical axis hydrokinetic turbine (VAHT) under freewheeling conditions. Flow velocities were measured using acoustic Doppler current profiler (ADCP) and acoustic Doppler velocimeter (ADV) probes. Numerous measurements were taken at different distances behind the turbine, ranging from 1 turbine diameter up to 17 turbine diameters. The focal objective was to investigate turbulence intensity levels at various depths and distances behind the turbine. Results showed that turbulence was most intense in the vicinity of the turbine, peaking at the turbine centerline with 83.98% for the first test and 119% for the second test with ADCP, and 40.82% for the first test and 54.64% for the second test with ADV. Turbulence intensity gradually decreased as the distance behind the turbine increased. Data from both ADCP and ADV were used to further verify the results and compare the findings. Combining the insights from both measurement methods gave a detailed understanding of the flow and turbulence characteristics behind the vertical-axis turbine.

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 score0.019
Threshold uncertainty score0.929

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.209
Teacher spread0.201 · 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
Published2024
Admission routes1
Has abstractyes

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