Akademik Veri Yönetim Sistemi
Tezin Türü: Doktora
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Havacılık ve Uzay Mühendisliği Bölümü, Türkiye
Tezin Onay Tarihi: 2011
Öğrenci: MONİER ELFARRA
Danışman: NİLAY SEZER UZOL
Özet:The main purpose of this study is to aerodynamically design and optimize winglet, twist angle distribution and pitch angle for a wind turbine blade using CFD to produce more power. The RANS solver of Numeca Fine/Turbo was validated by two test cases, the NREL II and NREL VI blades. The results have shown a considerable agreement with measurements for both cases. Two different preconditioners have been implemented for the low Mach number flow. The results have shown the superiority of Merkle preconditioner over Hakimi one and Merkle was selected for further simulations. In addition to that, different turbulence models have been compared and the Launder – Sharma has shown the best agreement with measurements. Launder – Sharma was chosen for further simulations and for the design process. Before starting the design and optimization, different winglet configurations were studied. The winglets pointing towards the suction side of the blade have yielded higher power output. Genetic algorithm and artificial neural network were implemented in the design and optimization process. The optimized winglet has shown an increase in power of about 9.5 % where the optimized twist has yielded to an increase of 4%. Then the stall regulated blade has been converted into pitch regulated blade to yield more power output. The final design was produced by a combination of the optimized winglet, optimized twist andbest pitch angle for every wind speed. The final design has shown an increase in power output of about 38%.