Abstract
The efficiency of vertical axis wind turbines highly depends on the aerodynamic performance of wind blades. In this paper we use modern design optimization approach to improve the wind blade performance. Design parameters include the airfoil thickness and camber. The design toolbox includes a Navier-Stokes solver, a genetic algorithm, and a response surface method. The blade performance is evaluated using a Navier-Stokes solver. A sliding mesh technique is employed to handle the rotating motion of blades. The response surface (RS) methodology, kriging method, and radial basis neural network will be applied to build a surrogate model to computationally effectively explore the relationship between design variables and power performance. A real-coded genetic algorithm (GA) is carried out to obtain optimized solutions from RS function. Our preliminary results show that increasing the blade thickness can increase the blade performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
