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http://dx.doi.org/10.5139/JKSAS.2015.43.4.326

Multi-Objective Optimization of Turbofan Engine Performance Using Particle Swarm Optimization  

Choi, Jaewon (Department of Aerospace and Mechanical Engineering, Korea Aerospace University, Technology Planning Division, Defense Agency for Technology and Quality)
Chung, Wonchul (Department of Aerospace and Mechanical Engineering, Korea Aerospace University)
Sung, Hong-Gye (School of Aerospace and Mechanical Engineering, Korea Aerospace University)
Publication Information
Journal of the Korean Society for Aeronautical & Space Sciences / v.43, no.4, 2015 , pp. 326-333 More about this Journal
Abstract
A turbo fan engine performance analysis program combined with a particle swarm optimization(PSO) has been developed to optimize the major design parameters of the combat aircraft gas turbine engine. The optimized parameters includes bypass ratio, fan pressure ratio, high pressure compression ratio and burner exit temperature. The objective parameters have been determined using a multi-objective function consisting of the net thrust and specific fuel consumption along a weight function. The basic model for the combat aircraft gas turbine engine has been selected as the F404 turbofan engine which is widely used in the combat aircraft, F-18 and Korean high level training aircraft, T-50. The optimal conditions of four parameters have been obtained for various design conditions.
Keywords
Turbo Fan Engine; Particle Swarm Optimization; Net Thrust; Specific Fuel Consumption;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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1 Homaifar, A., Lai, H.Y and McCormick, E., "System optimization of turbofan engines using genetic algorithms", Applied Mathematical Modelling, 1994, Vol. 18, No. 2, pp.72-83.   DOI   ScienceOn
2 Asako, T., Miyagawa, H., Miyata, S. and Kudo, K., "Conceptual design of aircraft engine using multidisciplinary design optimization technique", 23rd Congress of International Council of the Aeronautical Sciences, ICAS, 2002, Toronto, Canada.
3 Atashkari, K., Nariman-Zadeh, N., Pilechi, A., Jamali, A. and Yao, X., "Thermo- dynamic Pareto optimization of turbojet engines using multi-objective genetic algorithms", International Journal of Thermal Sciences, Vol. 44, No. 11, 2005, pp. 14-24.
4 J. Kennedy, R. Eberhart, 1995, Particle Swarm Optimization, Proceedings of IEEE International Conference onf Neural Networks, vol. 4, pp. 1942-1948, 1995
5 Seyed Ehsan Shakib, Majid Amidpour, Cyrus Aghanajafi, "Simulation and optimization of multi effect desalination coupled to a gas turbine plant with HRSG consideration", Desalination, 2012, pp. 366-376
6 M. Sadeghierad, A. Darabi, H. Lesani, H. Monsef, "Optimal design of the generator of microturbine using genetic algorithm and PSO", Electrical Power and Energy Systems, 2010, PP. 804-808
7 Weiping Zhang, Peifeng Niu, Guoqiang Li, Pengfei Li, "Forecasting of turbine heat rate with online least squares support vector machine based on gravitational search algorithm", Knowledge-Based Systems, 2013, pp. 34-44
8 Jack D. Mattingley, Elements of Gas Turbine Propulsion, McGraw-Hill, 2005
9 Won Choi, Ilwoo Lee, Junho Yang, "The Performance Modeling of a Low Bypass Turbofan Engine with Afterburner for Supersonic Aircraft", Journal of the Korean Society for Aeronautical & Space Sciences, Vol. 39, No. 3, 2011, pp. 269-278   DOI
10 Czitrom, Veronica, "One-Factor-at-a-Time versus Designed Experiments", Academic journal article from The American Statistician, Vol. 53, No. 2, 1999
11 Sangbok Lee, Taekyu Lim, Taesung Rho, "Design Optimization of Liquid Rocket Engine Using Genetic Algorithms", KSPE, Vol. 16, No. 2, 2005, pp. 25-33.
12 Jaewon Choi, Wonchul Chung, Hong-Gye Sung, "Performance Optimization of an Aircraft Turbofan Gas Turbine Engine using Particle Swarm Optimization", SASE Spring Conference, 2014.