Akademik Veri Yönetim Sistemi
Tezin Türü: Yüksek Lisans
Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Makina Mühendisliği Bölümü, Türkiye
Tezin Onay Tarihi: 2015
Öğrenci: MEHMET YALILI
Danışman: MEHMET HALUK AKSEL
Özet:The multi-objective design of hydraulic turbines using computational fluid dynamics software has been an important subject in turbomachinery area recently. Researches focus especially on obtaining higher turbine efficiency by the improvement of runner shapes. Thus in the present study, a multi-objective shape optimization procedure was applied to improve the runner blade shapes of a small Francis turbine named as GAMM turbine which was selected from the literature. CFD computations as well as blade generation and optimization steps were conducted using different modules of numerical software NUMECA/FINETM. Optimization of the runner shape was based on increasing overall efficiency at a single point which is the best efficiency point (BEP) of the turbine by applying problem constraints and specified boundary conditions. As design variables, camber curve at each primary section and lean curve defining the tangential location of the blades were selected. During the optimization, Artificial Neural Networks (ANN) and Genetic Algorithms (GA) were used for generating approximate model and for the optimization algorithm, respectively. Results showed that 0.73% improvement in total efficiency and 4.64% improvement in torque developed was obtained. Moreover, by considering the static pressure distribution along the turbine blades, the optimized turbine was observed to be cavitation free while running at the best efficiency point.