1
Mechanical Engineering, Babol Noshirvani university of Technology
2
Mechanical Engineering, Babol Noshirvani university of technology
Abstract
The aim of this study is to optimize performance functions of turbofan engines considering the off-design model of turbofan engine as well as employing multi-objective genetic algorithm. The design variables including high-pressure compressor pressure ratio, low-pressure compressor pressure ratio, fan pressure ratio and bypass ratio are calculated in such a way that the corresponding functions of specific thrust at take-off, as well as thrust specific fuel consumption, propulsive, thermal, and overall efficiencies while cruising are at their best performance conditions. The optimization is done using the modified NSGA II which is among the best multi-objective genetic algorithm methods. The obtained results of Multi-objective optimization will be a set of vectors among from which the designer may choose one depending on the conditions. The study of off-design model of turbofan engine is the significance of this study which has not been considered in similar studies.
Khodadadi, M., Kazemi, A., & Gorji, M. (2014). Optimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm. International Journal of Engineering, 27(6), 961-970.
MLA
M Khodadadi; Admin Kazemi; Mofid Gorji. "Optimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm". International Journal of Engineering, 27, 6, 2014, 961-970.
HARVARD
Khodadadi, M., Kazemi, A., Gorji, M. (2014). 'Optimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm', International Journal of Engineering, 27(6), pp. 961-970.
VANCOUVER
Khodadadi, M., Kazemi, A., Gorji, M. Optimal Thermodynamic Design of Turbofan Engines using Multi-objective Genetic Algorithm. International Journal of Engineering, 2014; 27(6): 961-970.
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