Amirkabir University of Technology Amirkabir Journal of Mechanical Engineering 2008-6032 53 Issue 5 (Special Issue) 2021 07 23 Improving the power coefficient of the Darrieus vertical axis wind turbine with the aid of morphing airfoils Improving the power coefficient of the Darrieus vertical axis wind turbine with the aid of morphing airfoils 3227 3240 4240 10.22060/mej.2021.18974.6931 FA Mohsen Kazemi Department of mechanical engineering , faculty of engineering , Ferdowsi University of Mashhad , Mashhad , Iran Amirhossein Fardi Department of mechanical engineering , faculty of engineering , Ferdowsi University of Mashhad , Mashhad , Iran Mohammad Javad Maghrebi Department of mechanical engineering , faculty of engineering , Ferdowsi University of Mashhad , Mashhad, Iran Journal Article 2020 09 08 With the advent of smart materials in recent years, the aviation industry and airfoils have undergone many changes. Research into the use of smart materials in aircraft wings to increase their performance and then the use of smart materials in wind turbine airfoils has begun. In this study, computational fluid dynamics and unsteady Reynolds-Averaged Navier-Stokes equations for a three-bladed Darrieus wind turbine equipped with a morphing airfoil were used to determine the optimum blade cross-section. 250 airfoils were generated by random control points, in Gambit software, they were unstructured and generated as a sliding mesh then they were simulated in 2D Ansys by using pressure-implicit with splitting of operators algorithm. Control points and power coefficient were used for artificial neural network training and the genetic algorithm was used to optimize the power coefficient. In this study, the base airfoil is NACA0015. The results of that have been very effective. For determining the optimal cross-section of the turbine at a full round, the power coefficient of Darrieus wind turbine with the optimal cross-section increased by 42%, and the blade section (airfoil) was also drawn. For determining the optimal cross-section in each of the four zones of the rotor), the most efficient sections (airfoils) in four-zone were obtained, increasing the turbine power coefficient by 60% was the result of this optimization. With the advent of smart materials in recent years, the aviation industry and airfoils have undergone many changes. Research into the use of smart materials in aircraft wings to increase their performance and then the use of smart materials in wind turbine airfoils has begun. In this study, computational fluid dynamics and unsteady Reynolds-Averaged Navier-Stokes equations for a three-bladed Darrieus wind turbine equipped with a morphing airfoil were used to determine the optimum blade cross-section. 250 airfoils were generated by random control points, in Gambit software, they were unstructured and generated as a sliding mesh then they were simulated in 2D Ansys by using pressure-implicit with splitting of operators algorithm. Control points and power coefficient were used for artificial neural network training and the genetic algorithm was used to optimize the power coefficient. In this study, the base airfoil is NACA0015. The results of that have been very effective. For determining the optimal cross-section of the turbine at a full round, the power coefficient of Darrieus wind turbine with the optimal cross-section increased by 42%, and the blade section (airfoil) was also drawn. For determining the optimal cross-section in each of the four zones of the rotor), the most efficient sections (airfoils) in four-zone were obtained, increasing the turbine power coefficient by 60% was the result of this optimization. https://mej.aut.ac.ir/article_4240_fd272fe04b7d4e68effd01bddcc6bb34.pdf