Prediction of compressor nominal characteristics of a turboprop engine using artificial neural networks for build standard assessment
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C. Jagadish Babu
Abstract
Compressor characteristics of a single spool turboprop engine have been studied in this paper. It has been brought outhow constant power lines in the compressor characteristics of these compressors make them different from others. Constant speed lines and constant power lines have also been highlighted. A novel method of modeling of compressorof a single spool turboprop engine has also been studied in this paper. Application of neural networks in prediction of compressor characteristics has been investigated. Multilayer Perceptron feed forward neural network has been considered with different transfer functions to assess the potential capability of network in extrapolation and interpolation. Effectiveness of prediction with and without engine bleed valve open and anti-ice valve open situations have been assessed. Network Predictionshas been compared with engine test data to assess the accuracy of prediction and to quantify the build variation in the manufacture of engines. Capability of network with limited test data to predict the complete performance has also been assessed and presented in this paper.
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Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Employment or leadership: None declared.
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Honorarium: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
References
1. Mattingly, JD, Heiser, HW, Pratt, DT. Aircraft engine design. AIAA education series. Reston, VA: AIAA, Inc; 2002.10.2514/4.861444Suche in Google Scholar
2. El-Sayed, AF. Aircraft propulsion and gas turbine engines. Boca Raton: CRC Press; 2017.Suche in Google Scholar
3. Saravanamuttoo, HIH. Modern turboprop engines. Prog. Aerosp. Sci. 1987;24:225–248. https://doi.org/10.1016/0376-0421(87)90008-x.Suche in Google Scholar
4. Babu, CJ, Kumaresan, DA, Kumar, V, Ragupathy, R, Mishra, RK. Analysis and prevention of failures in a turboprop engine. J Fail Anal Prev. https://doi.org/10.1007/s11668-019-00727-6.Suche in Google Scholar
5. MIL-E-5007 D/E (AS). Military specification for engines, aircrafts, turbojet and turbofan. United States: US Military Specs/Standards/Handbooks, Department of Defence, United States; 1983.Suche in Google Scholar
6. Boyce, MP. Gas turbine engineering handbook, 2nd ed. Houston, TX: Gulf Professional Publishing; 2002.Suche in Google Scholar
7. FAA Advisory Circular AC 33.87-1. Calibration Test, endurance test and teardown inspection for turbine engine certification. USA: Department of Transportation; 2006.Suche in Google Scholar
8. Yu, Y, Chen, L, Sun, F, Wu, C. Neural-network based analysis and prediction of a compressor’s characteristic performance map. Appl Energy 2007 Jan 1;84(1):48–55. https://doi.org/10.1016/j.apenergy.2006.04.005.Suche in Google Scholar
9. Mist’e, GA, Benini, E. Improvements in off design aeroengine performance prediction using analytic compressor map interpolation. Int. J. Turbo Jet-Engines. 2012 Jun 28;29(2):69–77. https://doi.org/10.1515/tjj-2012-0012.10.1515/tjj-2012-0012Suche in Google Scholar
10. Kong, C, Lim, S. Study on fault diagnostics of a turboprop engine using inverse performance model and artificial intelligent methods. Int J Turbo Jet Engines 2011;28(4):255–64. https://doi.org/10.1515/tjj.2011.060.Suche in Google Scholar
11. Azzam, M, Haag, JC, Jeschke, P. Application concept of artificial neural networks for turbomachinery design. Comput Assist Methods Eng Sci 2017;16(2):143–160.Suche in Google Scholar
12. Ghorbanian, K, Gholamrezaei, M. An artificial neural network approach to compressor performance prediction. Appl Energy 2009;86:7–8. https://doi.org/10.1016/j.apenergy.2008.06.006.Suche in Google Scholar
13. M Gholamrezaei, Ghorbanian, K. Compressor map generation using feed-forward neural network and rig data. J Power Energy 2010;224:97–108. https://doi.org/10.1243/09576509JPE792.Suche in Google Scholar
14. Fei, J, Zhao, N, Shi, Y, Feng, Y, Wang, Z. Compressor performance prediction using a novel feed-forward neural network based on Gaussian kernel function. Adv Mech Eng 2016;8(1):1687814016628396.10.1177/1687814016628396Suche in Google Scholar
15. Li, X, Ying, Y, Wang, Y, Li, J. A component map adaptation method for compressor modeling and diagnosis. Adv Mech Eng 2018;10:1687814018767165.10.1177/1687814018767165Suche in Google Scholar
16. Salamat, R. Gas path diagnostic for compressors [Doctoral Thesis]. UK: Cranfield University; 2012.Suche in Google Scholar
17. Naeem, M. Implication of Aero engine degradation on aero engine performance [PhD Thesis]. UK: Cranfield University; 1999.Suche in Google Scholar
18. Fei, T, Ji, L, Yi, W. Performance characteristic modeling for 2D compressor cascades. Int J Turbo Jet Engines 2022;39:367–82. https://doi.org/10.1515/tjj-2018-0033.Suche in Google Scholar
19. Li, Z, Yan-yan, L, Wei, L. Estimation of characteristic data of aircraft engine compressor based on developed modeling method. Int J Turbo Jet Engines 2020;37:319–26. https://doi.org/10.1515/tjj-2017-0025.Suche in Google Scholar
20. Gresh, T. Compressor performance: aerodynamics for the user Burlington MA, USA: Butterworth-Heinemann; 2018.Suche in Google Scholar
21. Mishra, RK. Fouling and corrosion in an aero gas turbine compressor. J Fail Anal Prev 2015;15(6):837–45. https://doi.org/10.1007/s11668-015-0023-8.Suche in Google Scholar
22. Mishra, RK, Bhat, RR, Chandel, S. Analysis of compressor surge in a military turbojet engine: a case study. Int J Turbo Jet Engines 2017;34(1):55–62. https://doi.org/10.1515/tjj-2015-0053.Suche in Google Scholar
23. Walsh, PP, Fletcher, P. Gas turbine performance. New Jersey, USA: John Wiley & Sons; 2004.10.1002/9780470774533Suche in Google Scholar
24. Hagan, MT, Demuth, HB, Beale, HD. Neural network design. New Jersey, USA: University of Colorado at Boulder; 2002.Suche in Google Scholar
© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Integration of a transonic high-pressure turbine with a rotating detonation combustor and a diffuser
- Prediction of compressor nominal characteristics of a turboprop engine using artificial neural networks for build standard assessment
- Study on inversion control for integrated helicopter/engine system with variable rotor speed based on state variable model
- Effects of casing angle on the performance of parallel hub axial annular diffuser
- Experimental research on the performance of the forward variable area bypass injector for variable cycle engines
- Film cooling characteristics on a grooved surface with different injection orientation angles
- Aero-thermal optimization of the rim seal cavity to enhance rotor platform thermal protection
- Numerical study of the parameters of a gas turbine combustion chamber with steam injection operating on distillate fuel
- An active fault-tolerant control strategy of aircraft engines based on multi-model predictive control
- Conjugate heat transfer analysis of a radially cooled nozzle guide vane in an aero gas turbine engine
- A new method to improve the real-time performance of aero-engine component level model
- Experimental and numerical investigation of expansion corner effects on isolator performance
Artikel in diesem Heft
- Frontmatter
- Integration of a transonic high-pressure turbine with a rotating detonation combustor and a diffuser
- Prediction of compressor nominal characteristics of a turboprop engine using artificial neural networks for build standard assessment
- Study on inversion control for integrated helicopter/engine system with variable rotor speed based on state variable model
- Effects of casing angle on the performance of parallel hub axial annular diffuser
- Experimental research on the performance of the forward variable area bypass injector for variable cycle engines
- Film cooling characteristics on a grooved surface with different injection orientation angles
- Aero-thermal optimization of the rim seal cavity to enhance rotor platform thermal protection
- Numerical study of the parameters of a gas turbine combustion chamber with steam injection operating on distillate fuel
- An active fault-tolerant control strategy of aircraft engines based on multi-model predictive control
- Conjugate heat transfer analysis of a radially cooled nozzle guide vane in an aero gas turbine engine
- A new method to improve the real-time performance of aero-engine component level model
- Experimental and numerical investigation of expansion corner effects on isolator performance
