10.1007/s40095-017-0248-2

Transition turbulence model calibration for wind turbine airfoil characterization through the use of a Micro-Genetic Algorithm

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  • S. Mauro*1,
  • R. Lanzafame1,
  • M. Messina1,
  • D. Pirrello1,
  1. Department of Civil Engineering and Architecture, University of Catania, Catania, 95125, IT
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Published in Issue 2017-10-17

How to Cite

Mauro, S., Lanzafame, R., Messina, M., & Pirrello, D. (2017). Transition turbulence model calibration for wind turbine airfoil characterization through the use of a Micro-Genetic Algorithm. International Journal of Energy and Environmental Engineering, 8(4 (December 2017). https://doi.org/10.1007/s40095-017-0248-2
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Abstract

Abstract The aerodynamic characterization of airfoils is of crucial importance for the design and optimization of wind turbines. The present paper tries to provide an engineering methodology for the improvement of the accuracy and reliability of 2D airfoil computational fluid dynamics models, by coupling the ANSYS Fluent solver and a Micro-Genetic Algorithm. The modeling strategy provided includes meshing optimization, solver settings, comparison between different turbulence models and, mainly, the calibration of the local correlation parameters of the transition turbulence model by Menter, which was found to be the most accurate model for the simulation of transitional flows. Specifically, the Micro-Genetic Algorithm works by generating populations of the missing local correlation parameters. In doing so, it is possible to search for the minimization of the error in lift calculations. For each specific Reynolds number, the calibration was carried out only at the Angle of Attack where the lift drop occurs and the airfoil completely stalls. This new idea allowed for a relatively rapid and good calibration as demonstrated by the experimental–numerical comparisons presented in this paper. Only the experimental stall angle and the relative lift coefficient were, therefore, necessary for obtaining a good calibration. The calibration was made using the widely known S809 profile data. The correlation parameters, obtained as so, were subsequently used for testing on the NACA 0018 airfoil with satisfactory results. Therefore, the calibration obtained using the S809 airfoil data appeared to be reliable and may be used for the simulation of other airfoils. This can be done without the need for further wind tunnel experimental data or recalibrations. The proposed methodology will, therefore, be of essential help in obtaining accurate aerodynamic coefficients data. This will drastically improve the capabilities of the 1D design codes at low Reynolds numbers thanks to the possibility of generating accurate databases of 2D airfoil aerodynamic coefficients. The advantages of the proposed calibration will be helpful in the generation of more accurate 3D wind turbine models as well. The final objective of the paper was thus to obtain a fine and reliable calibration of the transition turbulence model by Menter. This was specifically made for an accurate prediction of the aerodynamic coefficients of any airfoil at low Reynolds numbers and for the improvements of 3D rotor models.

Keywords

  • CFD transition modeling,
  • Airfoil characterization,
  • Wind turbines,
  • Genetic algorithm
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