Laminar-turbulent flow simulation for wind turbine profiles using the γ–Re˜θt transition model
Article first published online: 2 APR 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Volume 17, Issue 6, pages 901–918, June 2014
How to Cite
Khayatzadeh, P. and Nadarajah, S. (2014), Laminar-turbulent flow simulation for wind turbine profiles using the γ–Re˜θt transition model. Wind Energ., 17: 901–918. doi: 10.1002/we.1606
- Issue published online: 10 APR 2014
- Article first published online: 2 APR 2013
- Manuscript Accepted: 6 FEB 2013
- Manuscript Revised: 25 OCT 2012
- Manuscript Received: 7 MAR 2012
- wind turbine;
- laminar-turbulent boundary layer;
- k–ωSST turbulence model;
- γ– transition model
The accurate prediction of the laminar-turbulence transition process is fundamental in predicting the aerodynamic performance of wind turbine profiles. Fully turbulent flow simulations have been shown to over-predict the aerodynamic performance and thereby negatively impacting the design of airfoils in flow regimes where the possible presence of laminar flow could be exploited to improve the performance of wind turbine rotors. Correlation-based transition modelling offers a fully computational fluid dynamics compatible approach, where the model integrates completely with the existing turbulence model, allows for the prediction of various transition mechanisms, is applicable to three-dimensional flows and compatible to adjoint-based design optimization frameworks. The present paper addresses several modifications necessary for a robust transition model and investigates the accuracy of the model for a wide range of angles of attack and Reynolds numbers, which are necessary for a thorough validation of the correlation-based transition model for wind turbine profiles. The transition model was employed to predict the transition locations; and an assessment of the various transition mechanisms, Reynolds number effects, sectional characteristics and aerodynamic performance for the NLF(1)-0416 and S809 airfoils is presented with comparisons to experimental data and numerical solutions. Copyright © 2013 John Wiley & Sons, Ltd.