Journal of the Korean Society for Aeronautical & Space Sciences (한국항공우주학회지)

The Korean Society for Aeronautical and Space Sciences (한국항공우주학회)
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Multi-Objective Optimization of Turbofan Engine Performance Using Particle Swarm Optimization

Particle Swarm Optimization을 이용한 터보팬 엔진 다목표 성능 최적화 연구

  • 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)
  • Received : 2014.12.14
  • Accepted : 2015.03.19
  • Published : 2015.04.01
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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.

최적화 프로그램과 연동시키기 위한 터보팬 엔진 성능해석 프로그램을 개발하고, 최적화 기법인 Particle Swarm Optimization을 이용하여 전투기 엔진의 주요 설계변수인 바이패스비, 팬 압축비, 고압압축기 압축비 및 버너출구온도에 대한 성능 최적화를 수행하였다. 최적화 목표는 순추력과 비연료소모율을 다목표 함수로 설정하였으며, 두 개의 목표에 대해 가중치를 주어 각 가중치별 최적 설계점을 도출하였다. 기본 모델은 F-18 전투기와 T-50 고등훈련기에 쓰이고 있는 F404 터보팬 엔진을 선정하여 분석을 수행하였다. 본 연구 결과로 네 개의 변수에 대한 최적 조건을 도출하고, 다양한 설계조건에 대한 최적 설계점 추이를 분석하였다.

Keywords

References

  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. https://doi.org/10.1016/0307-904X(94)90162-7
  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 https://doi.org/10.5139/JKSAS.2010.39.3.269
  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.