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A Data-Driven Approach for the Prediction of Reynolds Number Effects on Wind Turbine Airfoil Aerodynamic Polars
  • Oguz Uzol,
  • Ahmet ÖZGÖREN
Oguz Uzol
Middle East Technical University (METU

Corresponding Author:[email protected]

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Middle East Technical University (METU
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This study presents a data-driven approach to extrapolate and predict Reynolds number effects on wind turbine airfoil polars. For this purpose a database is created using experimentally obtained aerodynamic coefficients from open literature for airfoils with thickness-to-chord ratio (t/c) values in the range of 15% to 30% in order to be more relevant to wind turbine blade design applications. All available airfoil geometries are parameterized using PARSEC methodology, and a Pareto analysis is performed to understand the sensitivity of maximum lift coefficient ( C l max ) and minimum drag coefficient ( C d min ) variations to geometrical inputs as well as to the Reynolds number using statistical tools. Based on this analysis, response surfaces are generated to predict C l max and C d min of a given airfoil operating at a given Reynolds number. These predicted values are then utilized in a power-law based estimation methodology to obtain predictions for full polars, which are then compared to experimental data for selected airfoil test cases. The results show that the response surfaces generated through the current data-driven approach as well as the full polar prediction methodology show better agreement with experimental results compared to those obtained using numerical simulations-based extrapolation schemes. For airfoil types that might be under-represented in the database (such as symmetrical airfoils), the prediction results can be erroneous, especially at very high Reynolds numbers that are not in the constructed database. In the power-law based polar prediction methodology, utilizing a reference Reynolds number that is closer to the target value provides more accurate predictions for both lift and drag polars.
19 Sep 20231st Revision Received
19 Sep 2023Assigned to Editor
19 Sep 2023Submission Checks Completed
19 Sep 2023Review(s) Completed, Editorial Evaluation Pending
07 Nov 2023Reviewer(s) Assigned