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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 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: none
Teacher disagreement score0.880
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
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 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

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