IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v294y2024ics0360544224007084.html
   My bibliography  Save this article

Research on high fidelity modelling and optimum designing of an adaptive cycle engine's starting process

Author

Listed:
  • Zhen, Man
  • Dong, Xuezhi
  • Shao, Dong
  • Liu, Xiyang
  • Tan, Chunqing

Abstract

An adaptive cycle engine is an evolutional aero-engine that can achieve low fuel consumption and high efficiency by adjusting the thermodynamic cycle; however, few studies have been conducted on adaptive cycle engine performance at low speeds. A high-fidelity ground starting model of an adaptive cycle engine is established by correcting the low speed characteristics of the components, while considering the effects of rotor inertia, volume, combustion efficiency, and the thermal inertia of the combustor and turbine. By employing a physically enhanced prediction method, three operating states of the compressor at low speeds are obtained: compressor, stirrer, and turbine state. The matching mechanism of the adaptive cycle engine and the detailed influence of the variable geometries on the engine's performance during the starting process are explored. The study shows that the third bypass duct has little effect on the engine starting time, and opening the mode select valve can reduce the starting time. Compared with the initial settings, the starting time decreases by 3.98 s after optimization with the variable geometries. The detailed impact of the variable geometries on the engine's starting performance provides an engineering reference value for the control strategies.

Suggested Citation

  • Zhen, Man & Dong, Xuezhi & Shao, Dong & Liu, Xiyang & Tan, Chunqing, 2024. "Research on high fidelity modelling and optimum designing of an adaptive cycle engine's starting process," Energy, Elsevier, vol. 294(C).
  • Handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224007084
    DOI: 10.1016/j.energy.2024.130936
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544224007084
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2024.130936?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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).
    2. Mohammadian, Poorya Keshavarz & Saidi, Mohammad Hassan, 2019. "Simulation of startup operation of an industrial twin-shaft gas turbine based on geometry and control logic," Energy, Elsevier, vol. 183(C), pages 1295-1313.
    3. Yu, Youhong & Chen, Lingen & Sun, Fengrui & Wu, Chih, 2007. "Neural-network based analysis and prediction of a compressor's characteristic performance map," Applied Energy, Elsevier, vol. 84(1), pages 48-55, January.
    4. Kim, Jeong Ho & Kim, Tong Seop, 2019. "A new approach to generate turbine map data in the sub-idle operation regime of gas turbines," Energy, Elsevier, vol. 173(C), pages 772-784.
    5. Guan, Cong & Theotokatos, Gerasimos & Zhou, Peilin & Chen, Hui, 2014. "Computational investigation of a large containership propulsion engine operation at slow steaming conditions," Applied Energy, Elsevier, vol. 130(C), pages 370-383.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Du, Wei & Li, Yanjun & Shi, Jianxin & Sun, Baozhi & Wang, Chunhui & Zhu, Baitong, 2023. "Applying an improved particle swarm optimization algorithm to ship energy saving," Energy, Elsevier, vol. 263(PE).
    3. Aygun, Hakan, 2022. "Thermodynamic, environmental and sustainability calculations of a conceptual turboshaft engine under several power settings," Energy, Elsevier, vol. 245(C).
    4. Balerna, Camillo & Lanzetti, Nicolas & Salazar, Mauro & Cerofolini, Alberto & Onder, Christopher, 2020. "Optimal low-level control strategies for a high-performance hybrid electric power unit," Applied Energy, Elsevier, vol. 276(C).
    5. Tammo Zobel & Andreas Ritter & Christopher H. Onder, 2023. "The Faster the Better? Optimal Warm-Up Strategies for a Micro Combined Heat and Power Plant," Energies, MDPI, vol. 16(10), pages 1-24, May.
    6. Larsen, Ulrik & Pierobon, Leonardo & Baldi, Francesco & Haglind, Fredrik & Ivarsson, Anders, 2015. "Development of a model for the prediction of the fuel consumption and nitrogen oxides emission trade-off for large ships," Energy, Elsevier, vol. 80(C), pages 545-555.
    7. Yazar, Isil & Yavuz, Hasan Serhan & Yavuz, Arzu Altin, 2017. "Comparison of various regression models for predicting compressor and turbine performance parameters," Energy, Elsevier, vol. 140(P2), pages 1398-1406.
    8. Omar Mohamed & Ashraf Khalil, 2020. "Progress in Modeling and Control of Gas Turbine Power Generation Systems: A Survey," Energies, MDPI, vol. 13(9), pages 1-26, May.
    9. Mirko Grljušić & Ivan Tolj & Gojmir Radica, 2017. "An Investigation of the Composition of the Flow in and out of a Two-Stroke Diesel Engine and Air Consumption Ratio," Energies, MDPI, vol. 10(6), pages 1-20, June.
    10. Kim, Sangjo & Kim, Kuisoon & Son, Changmin, 2020. "A new transient performance adaptation method for an aero gas turbine engine," Energy, Elsevier, vol. 193(C).
    11. Qiang, Xiaoqing & Lu, Yao & Li, Jian, 2024. "Bleed air CFD modelling in aerodynamic simulation of A heavy duty gas turbine compressor," Energy, Elsevier, vol. 299(C).
    12. Li, Zhihui & Liu, Yanming, 2017. "Blade-end treatment for axial compressors based on optimization method," Energy, Elsevier, vol. 126(C), pages 217-230.
    13. Aygun, Hakan & Erkara, Seref & Turan, Onder, 2022. "Comprehensive exergo- sustainability analysis for a next generation aero engine," Energy, Elsevier, vol. 239(PD).
    14. Guan, Cong & Theotokatos, Gerasimos & Zhou, Peilin & Chen, Hui, 2014. "Computational investigation of a large containership propulsion engine operation at slow steaming conditions," Applied Energy, Elsevier, vol. 130(C), pages 370-383.
    15. Seong Won Moon & Tong Seop Kim, 2020. "Advanced Gas Turbine Control Logic Using Black Box Models for Enhancing Operational Flexibility and Stability," Energies, MDPI, vol. 13(21), pages 1-23, October.
    16. Jia, Xingyun & Zhou, Dengji, 2024. "Multi-variable anti-disturbance controller with state-dependent switching law for adaptive cycle engine," Energy, Elsevier, vol. 288(C).
    17. Kagan Ayaz, S. & Caliskan, Hakan & Altuntas, Onder, 2023. "Environmental and second law analysis of a turbojet engine operating with different fuels," Energy, Elsevier, vol. 285(C).
    18. Guan, Jin & Lv, Xiaojing & Spataru, Catalina & Weng, Yiwu, 2021. "Experimental and numerical study on self-sustaining performance of a 30-kW micro gas turbine generator system during startup process," Energy, Elsevier, vol. 236(C).
    19. Chaczykowski, M. & Osiadacz, A.J. & Uilhoorn, F.E., 2011. "Exergy-based analysis of gas transmission system with application to Yamal-Europe pipeline," Applied Energy, Elsevier, vol. 88(6), pages 2219-2230, June.
    20. Shen, Wenkai & Liu, Li & Hu, Qiming & Liu, Guichuang & Wang, Jiwei & Zhang, Ning & Wu, Shaohua & Qiu, Penghua & Song, Shaowei, 2021. "Combustion characteristics of ignition processes for lean premixed swirling combustor under visual conditions," Energy, Elsevier, vol. 218(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:294:y:2024:i:c:s0360544224007084. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.