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Record W806653838 · doi:10.1139/tcsme-2014-0032

MESH CONVERGENCE STUDY FOR 2-D STRAIGHT-BLADE VERTICAL AXIS WIND TURBINE SIMULATIONS AND ESTIMATION FOR 3-D SIMULATIONS

2014· article· en· W806653838 on OpenAlexaffvenue
Saman Naghib Zadeh, Matin Komeili, Marius Paraschivoiu

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2014
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Turbulent Flows
Canadian institutionsConcordia University
Fundersnot available
KeywordsVertical axis wind turbineAerodynamicsWakeComputational fluid dynamicsTurbulenceGridStall (fluid mechanics)MechanicsMesh generationTurbine bladeTurbineReynolds-averaged Navier–Stokes equationsConvergence (economics)Aerospace engineeringPhysicsGeologyGeometryEngineeringMathematicsFinite element methodStructural engineering

Abstract

fetched live from OpenAlex

Mesh resolution requirements are investigated for 2-D and 3-D simulations of the complex flow around a straight-blade vertical axis wind turbine (VAWT). The resulting flow, which may include large separation flows over the blades, dynamic stall, and wake-blade interaction, is simulated by an Unsteady Reynolds-Averaged Navier–Stokes analysis, based on the Spalart-Allmaras (S–A) turbulence model. A grid resolution study is conducted on 2-D grids to examine the convergence of the CFD model. Hence, an averaged-grid residual of y+ > 30 is employed, along with a wall treatment, to capture the near-wall region’s flow structures. Furthermore a 3-D simulation on a coarse grid of the VAWT model is performed in order to explore the influence of the 3-D effects on the aerodynamic performance of the turbine. Finally, based on the 2-D grid convergence study and the 3-D results, the required computational time and mesh to simulate 3-D VAWT accurately is proposed.

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)0.002
metaresearch head score (Gemma)0.009
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: Methods
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations27
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicFluid Dynamics and Turbulent FlowsFrench-language works237,207