Open Access
Issue
EPJ Web Conf.
Volume 361, 2026
ASPOWERCN 2024 – The 8th Joint Conference of Aerospace Propulsion and the 44th Aerospace Propulsion Technology Information Society (APTIS) Technical Conference
Article Number 06001
Number of page(s) 11
Section Engine Intake and Exhaust
DOI https://doi.org/10.1051/epjconf/202636106001
Published online 13 April 2026
  1. Donald L Simon. An overview of the NASA aviation safety program propulsion health monitoring element[C]//36th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Reston, VA: AIAA Press, 2000: 1–11. [Google Scholar]
  2. Liu Jinlin, Zeng Fanming. Calculation method for the requirement index weight of the marine power plant based on fuzzy AHP [J]. Journal of Dalian Maritime University, 2012, 4: 35–38. [Google Scholar]
  3. Liu Weibo. Study on the integrated condition assessment for main power plant of a certain type warship based on analytical hierarchy process [D]. Dalian: Dalian Maritime University, 2013. [Google Scholar]
  4. Luo Heng, Zhang Jingqiao, Liu Dongmin, et al. A technical conditions evaluation method for power system with analytical hierarchy process [J]. Ship Science and Technology, 2017, 39(2): 79–82. [Google Scholar]
  5. Yuan Jilai, Zhang Zhishu, Chen Zhongguang, et al. Research on the steady state performance adjustment of turbofan engine using AHP [J]. Aeronautical Science & Technology, 2016, 27(05): 33–37. [Google Scholar]
  6. Yang Yang, Wan Liyong. Application of analytic hierarchy process in multi-dimensional risk assessment of aeroengine system [J]. Aeroengine, 2022, 48(3):1–6. [Google Scholar]
  7. Zhang Wei, Cai Yuanhu, Su Sanmai, et al. Quantitative analysis and numerical simulation of optimization of a propulsion system [J]. Journal of Aerospace Power, 2010, 25(11): 2450–2456. [Google Scholar]
  8. Wang Peng, Chen Yingchun, Si Jiangtao, et al. Technology evaluation and choice of civil aircraft engine based on analytic hierarchy process [J]. Aeroengine, 2016, 42(5): 98–102. [Google Scholar]
  9. Wang Bing, Ji Zifei. Theory of Aerospace Propulsion [M]. Beijing: Science Press, 2018: 26–31. [Google Scholar]
  10. Farokhi S. Aircraft Propulsion [M]. Hoboken: John Wiley & Sons, 2014: 154–163. [Google Scholar]
  11. Wang Tuanjie, Li Benwei, Yu Fulei, et al. Index parameters demonstration method turbofan engine performance [J]. Journal of Naval Aeronautical and Astronautical University, 2014 (6): 511–516. [Google Scholar]
  12. Walsh P., Fletcher P. Gas turbine performance [M]. New Jersey: Wiley-Blackwell, 2004: 31–40. [Google Scholar]
  13. Mattingly D., Heiser H., Boyer M., et al. Aircraft engine design [M]. VA: AIAA Press, 2018: 81–105. [Google Scholar]
  14. JI Zifei, HAN Wenjun, LI Ruijun, et al. Determination of design margins for aeroengine performance targets with component uncertainties under consideration [J]. Aeroengine, 2022, 48(6):34–41. [Google Scholar]
  15. Anderson D R. An Introduction to Management Science: Quantitative Approaches to Decision Making [M]. Stamford: Cengage Learning, 2015: 522–530. [Google Scholar]
  16. Thakker A., Jarvis J., Buggy M., et al. 3DCAD conceptual design of the next-generation impulse turbine using the Pugh decision-matrix [J]. Materials and Design, 2009, 30(7):2676–2684. [Google Scholar]
  17. Cervone F. Applied digital library project management: Using Pugh matrix analysis in complex decision-making situations[J]. Oclc Systems & Services, 2009, 25(4):228–232. [Google Scholar]
  18. Guler K., Petrisor D. A Pugh Matrix based product development model for increased small design team efficiency[J]. Cogent Engineering, 2021, 8(1):1923383. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.