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Energy and performance optimization of an adaptive cycle engine for next generation combat aircraft

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  • Aygun, Hakan
  • Cilgin, Mehmet Emin
  • Ekmekci, Ismail
  • Turan, Onder

Abstract

For next generation aircraft, Adaptive Cycle Engine (ACE) is a candidate to fulfill the multi-mission requirements of flight. This new concept is promising to complete deficiencies of conventional low by-pass mixed turbofan engines because the ACE model incorporates different thermodynamic cycles (turbojet and turbofan) on the same air vehicle system. Firstly, performance and design results of the ACE model are compared with those of fixed cycle low by-pass turbofan engine by using specific fuel consumption (SFC), specific thrust (ST), power and efficiency parameters. Moreover, verification of the newly developed ACE model is performed. Secondly, considering some design parameters, ST and SFC values of the ACE model are analyzed for double by-pass mode (DBM) and single by-pass mode (SBM). Considering performance analysis of the ACE, SFC value is determined as 17.85 g/kN.s at DBM and 42.18 g/kN.s at SBM. According to results of energy analysis, overall efficiency of the ACE is calculated as 23% for DBM and 9% for SBM whereas fixed cycle engine has 18% for military mode and 7% for afterburner mode. Finally, minimization of (SFC) is obtained with genetic algorithm approach. Based on the design variables such as by-pass ratio and turbine inlet temperature, minimum SFC value for the ACE model is calculated as 17.41 g/kN.s at DBM and 40.45 g/kN.s at SBM.

Suggested Citation

  • Aygun, Hakan & Cilgin, Mehmet Emin & Ekmekci, Ismail & Turan, Onder, 2020. "Energy and performance optimization of an adaptive cycle engine for next generation combat aircraft," Energy, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:energy:v:209:y:2020:i:c:s0360544220313682
    DOI: 10.1016/j.energy.2020.118261
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    References listed on IDEAS

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    1. Rosen, Marc A., 2002. "Assessing energy technologies and environmental impacts with the principles of thermodynamics," Applied Energy, Elsevier, vol. 72(1), pages 427-441, May.
    2. Baklacioglu, Tolga & Turan, Onder & Aydin, Hakan, 2015. "Dynamic modeling of exergy efficiency of turboprop engine components using hybrid genetic algorithm-artificial neural networks," Energy, Elsevier, vol. 86(C), pages 709-721.
    3. Turan, Onder, 2012. "Exergetic effects of some design parameters on the small turbojet engine for unmanned air vehicle applications," Energy, Elsevier, vol. 46(1), pages 51-61.
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    Cited by:

    1. Aygun, Hakan & Erkara, Seref & Turan, Onder, 2022. "Comprehensive exergo- sustainability analysis for a next generation aero engine," Energy, Elsevier, vol. 239(PD).
    2. Aygun, Hakan, 2022. "Thermodynamic, environmental and sustainability calculations of a conceptual turboshaft engine under several power settings," Energy, Elsevier, vol. 245(C).
    3. Balli, Ozgur & Karakoc, T. Hikmet, 2022. "Exergetic, exergoeconomic, exergoenvironmental damage cost and impact analyses of an aircraft turbofan engine(ATFE)," Energy, Elsevier, vol. 256(C).
    4. Balli, Ozgur & Caliskan, Hakan, 2021. "Turbofan engine performances from aviation, thermodynamic and environmental perspectives," Energy, Elsevier, vol. 232(C).
    5. Wang, Busheng & Xuan, Yimin, 2023. "An integrated model for energy management of aero engines based on thermodynamic principle of variable mass systems," Energy, Elsevier, vol. 276(C).

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