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Record W3208826420

Preliminary parametric study of a tidal energy device using an open-source CFD tool

2021· article· en· W3208826420 on OpenAlexaffvenue
Abolghasem Pilechi, Sean Ferguson, Behnaz Ghodoosipour, Andrew Cornett, Laird Bateham

Bibliographic record

VenueNPARC · 2021
Typearticle
Languageen
FieldEngineering
TopicWind Energy Research and Development
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsComputational fluid dynamicsOpen sourceMarine engineeringEnvironmental scienceComputer scienceMechanical engineeringEngineeringMeteorologyPhysicsAerospace engineeringOperating systemSoftware
DOInot available

Abstract

fetched live from OpenAlex

Simultaneous advancements in high-performance computing technologies (HPC) and fluid dynamics science have set the stage for practical computational fluid dynamics (CFD) modelling of complex real-life problems including fluid-structure interaction. The presented research summarizes the capabilities of the OpenFOAM CFD toolbox to facilitate design optimization of an innovative tidal energy device. Numerical simulations were conducted for different environmental conditions and operating scenarios to characterize the flows through the device. The influence of changing the number of turbine blades as well as their submergence depth in the incident flow was tested through a series of 2D numerical simulations which consider the dynamics of the rotary component of the system. The results of the simulations were used to investigate potential strategies for design optimization, ultimately improving efficiency.

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)0.001
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.041
GPT teacher head0.278
Teacher spread0.238 · 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
GenreMethods

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
Published2021
Admission routes2
Has abstractyes

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