Abstract

Nowadays, optimization methods have been considered as a practical tool to improve the performance of turbo-machines. For this purpose, the numerical study of the aerodynamic flow of the NASA Rotor-67 axial compressor has been investigated, and the results of this three-dimensional simulation show good agreement with experimental data. Then, the blade stacking line is changed using lean and sweep for Rotor-67 to improve the compressor performance. The third-order polynomial is selected to generate the lean and sweep changes from the hub to the shroud. The compressor flow field is solved by a Reynolds averaged Navier-Stokes solver. The genetic algorithm, coupled with the artificial neural networks, is implemented to find the optimum values for blade lean and sweep. Considering the three objective functions of pressure ratio, mass flow rate, and isentropic efficiency, the optimized rotor is obtained using the optimization algorithm. Two geometries are obtained using the optimization algorithm. The results of the optimized compressor include improving the isentropic efficiency, pressure ratio, and mass flow equal to 0.57%, 0.93%, and 1.8%, respectively. After compressor optimization, the effect of the changes in the compressor performance parameters is studied on a single spool turbojet engine. The engine is modeled by analyzing the Brayton thermodynamic cycle of the assumed turbojet engine under design point operating conditions. Results show that for the best test case, the engine with the optimized rotor, the thrust, and SFC are improved by 1.86% and 0.21%, respectively.

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