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Optimization of turbine blade cooling with the aim of overall turbine performance enhancement | ||
| Energy Equipment and Systems | ||
| مقاله 6، دوره 5، شماره 1، خرداد 2017، صفحه 71-83 اصل مقاله (1.77 M) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ees.2017.60850 | ||
| نویسندگان | ||
| Seyyed Morteza Mousavi* ؛ Amir Nejat؛ Farshad Kowsary | ||
| School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran | ||
| چکیده | ||
| In the current work, different methods for optimization of turbine blade internal cooling are investigated, to achieve higher cyclic efficiency and output power for a typical gas turbine. A simple two-dimensional model of C3X blade is simulated and validated with available experimental data. The optimization process is performed on this model with two different methods. The first method is a popular method used in previous works with two objectives i.e. the minimization of the maximum temperature and the maximum temperature gradient on the blade. A new method is hereby proposed for optimization of turbine blade cooling, in which the coolant mass flow rate is minimized subject to maximum temperature, and maximum temperature gradient remains lower than certain values. The overall turbine performance is estimated by a simple comparative thermodynamic analysis of the reference design and the representative results obtained from the first and second method of optimization. It is concluded that while the first method of optimization allows higher TIT for a typical turbine, the turbine output power and efficiency could be lower than the reference design, due to high coolant mass flow rate in these candidate points. However, the optimum design point of the second method has higher power output and efficiency compared to all other designs (including reference design) at all values of compressor pressure ratio. It is shown that implementation of the second optimization method can increase the efficiency and the output power of a typical turbine 4.68% and 17% respectively. | ||
| کلیدواژه‌ها | ||
| Gas Turbine؛ CFD؛ Optimization؛ Genetic Algorithm؛ Thermodynamic analysis | ||
| مراجع | ||
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