-
CiteScore
0.13
Impact Factor
IECE Transactions on Intelligent Unmanned Systems, 2024, Volume 1, Issue 1: 24-30

Free to Read | Research Article | 17 July 2024
by
1 Northwestern Polytechnical University, Xi’an 710100, Shaanxi, China
* Corresponding Author: Luo Zhe, [email protected]
Received: 23 May 2024, Accepted: 05 July 2024, Published: 17 July 2024  
Abstract
This paper provides a comprehensive review of the application of computer simulation in analyzing the performance of gas turbine engines. It introduces a novel three-tiered approach to simulate jet engine performance, enhancing understanding and optimization of design parameters. Utilizing a specialized computer simulation program, the study investigates the thermodynamic cycle at the design point and assesses performance at off-design points. Results underscore the pivotal role of computer simulation techniques in refining the design and efficiency of turbofan engines, offering significant insights into the development of more advanced gas turbine systems.

Keywords
Performance simulation
Design performance
Off-design performance
Gas turbine engine

Funding
This work was supported without any funding.

Cite This Article
APA Style
Zhe, L. (2024). Enhancing Aero Engine Design Through Advanced Computer Simulation Techniques. IECE Transactions on Intelligent Unmanned Systems, 1(1), 24–30. https://doi.org/10.62762/TIUS.2024.424921

References
  1. El-Sayed, A. F., & El-Sayed, A. F. (2016). Shaft Engines Turboprop, Turboshaft, and Propfan. Fundamentals of Aircraft and Rocket Propulsion, 531-588.
    [Google Scholar]

  2. [Google Scholar]

  3. [Google Scholar]
  4. El-Sayed, A. F., & El-Sayed, A. F. (2016). Classifications of aircrafts and propulsion systems. Fundamentals of Aircraft and Rocket Propulsion, 1-89.
    [Google Scholar]
  5. McKinney, J. S. (2002). Simulation of turbofan engine. National Technical Information Service.
    [Google Scholar]
  6. Fishbach, L. H. (1972). GENENG II: A Program for Calculating Design and Off-Design Performance of Two-and Three-Spool Turbofans with as Many as Three Nozzles. National Aeronautics and Space Administration;[For sale for Federal Scientific and Technical Information, Springfield, Virginia 22151].
    [Google Scholar]
  7. Sellers, J. F., & Daniele, C. J. (1975). DYNGEN: A program for calculating steady-state and transient performance of turbojet and turbofan engines (Vol. 7901). National Aeronautics and Space Administration.
    [Google Scholar]
  8. Matz, D. (1983). CFM56-2-C2 Steady State Performance Computer Program User’s Manual [Z]. General Electric Technical Information Series.
    [Google Scholar]
  9. Chappell, M. A., & McLaughlin, P. W. (1993). Approach of modeling continuous turbine engine operation from startup to shutdown. Journal of Propulsion and Power, 9(3), 466-471.
    [Google Scholar]
  10. Editorial board of Aeroengine Design Manual. Aeroengine Design Manual: Volume 5[Z]. Beijing: Aviation Industry Press,2021.
    [Google Scholar]
  11. Fang, F. A. N. G., Tan, W., & Liu, J. Z. (2005). Tuning of coordinated controllers for boiler-turbine units. Acta Automatica Sinica, 31(2), 291-296.
    [Google Scholar]
  12. Fang, F., Jizhen, L., & Wen, T. (2004). Nonlinear internal model control for the boiler-turbine coordinate systems of power unit. PROCEEDINGS-CHINESE SOCIETY OF ELECTRICAL ENGINEERING, 24(4), 195-199.
    [Google Scholar]
  13. Lv, Y., Fang, F. A. N. G., Yang, T., & Romero, C. E. (2020). An early fault detection method for induced draft fans based on MSET with informative memory matrix selection. ISA transactions, 102, 325-334.
    [Google Scholar]
  14. Fang, F., & Wu, X. (2020). A win–win mode: The complementary and coexistence of 5G networks and edge computing. IEEE Internet of Things Journal, 8(6), 3983-4003.
    [Google Scholar]
  15. Lv, Y., Lv, X., Fang, F., Yang, T., & Romero, C. E. (2020). Adaptive selective catalytic reduction model development using typical operating data in coal-fired power plants. Energy, 192, 116589.
    [Google Scholar]
  16. Fang, F., & Xiong, Y. (2014). Event-driven-based water level control for nuclear steam generators. IEEE Transactions on Industrial electronics, 61(10), 5480-5489.
    [Google Scholar]
  17. Liu, J., Zeng, D., Tian, L., Gao, M., Wang, W., Niu, Y., & Fang, F. (2015). Control strategy for operating flexibility of coal-fired power plants in alternate electrical power systems. Proceedings of the CSEE, 35(21), 5385-5394.
    [Google Scholar]
  18. Wang, N., Fang, F., & Feng, M. (2014, May). Multi-objective optimal analysis of comfort and energy management for intelligent buildings. In The 26th Chinese control and decision conference (2014 CCDC) (pp. 2783-2788). IEEE.
    [Google Scholar]

Article Metrics
Citations:

Crossref

0

Scopus

0

Web of Science

0
Article Access Statistics:
Views: 352
PDF Downloads: 8

Publisher's Note
IECE stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions
Institute of Emerging and Computer Engineers (IECE) or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
IECE Transactions on Intelligent Unmanned Systems

IECE Transactions on Intelligent Unmanned Systems

ISSN: 2998-9140 (Online)

Email: [email protected]

Portico

Portico

All published articles are preserved here permanently:
https://www.portico.org/publishers/iece/

Copyright © 2024 Institute of Emerging and Computer Engineers Inc.