CFD Analysis of Oscillating Blades for Small Horizontal Axis Wind Turbines in Dynamic Stall Condition
Bibliographic record
Abstract
Unsteady aerodynamics and specifically the dynamic stall phenomenon significantly affect the aerodynamic performance of the wind turbine blades. This paper presents a 2D computational investigation on the aerodynamic characteristics of three specific airfoils for small horizontal axis wind turbines subjected to unsteady viscous flow. The unsteady incompressible Navier-Stokes equations are considered, and ANSYS-Fluent CFD code is used for the flow simulation. The simulation method is validated by calculating the aerodynamic coefficients of a pitching NACA23012 airfoil and comparing the results with the corresponding published experimental data. A complete set of dynamic simulations is then performed to find lift and drag forces acting on the airfoils in different unsteady conditions such as various Reynolds numbers and different amplitude and frequency of pitching oscillations. The results of this study emphasize that the curvature of leading edge and the thickness of the airfoil have major roles in early flow separation and dynamic stall of a pitching airfoil. The dynamic stall has wide negative effects on the performance of the blades such as lift reduction, drag increment and delay in the flow reattachment that are discussed in this paper.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".