Abstract
The current study aims to amplify the predictive ability of the numerical model developed for a gas turbine engine-based power plants by process of regeneration and intercooling. Artificial neural networks (ANN) and adaptive neuro-fuzzy interface systems (ANFIS) are the two techniques mainly concentrated in this study which were not properly implemented previously. The performance parameters namely, specific power (SP), thermal efficiency (η), and enthalpy based specific fuel consumption (EBSFC) of a Turboprop engine were predicted using thermodynamic parameters namely, pressure ratio (PR), nozzle pressure ratio (NPR), turbine inlet temperature (TIT), for constant regeneration (R), and intercooling (E) efficiencies. The results showed that a high regression result R 2 of 0.9831 and 0.9899 was found for the ANFIS model for η for training and testing, respectively. Also, the ANFIS model resulted in best performance of the performance characteristics when compared to ANN.
-
Research ethics: Not applicable.
-
Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Competing interests: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: Not applicable.
Nomenclature
- ANN
-
artificial neural network
- ANFIS
-
adaptive neuro fuzzy interference system
- EBSFC
-
engine brake specific fuel consumption (kg/h/kW)
- I-R
-
intercooling and regeneration
- p a
-
ambient pressure (N/m2)
- M/M 0
-
flight Mach number
- NPR
-
nozzle pressure ratio
- PR
-
pressure ratio
- TIT
-
turbine inlet temperature (K)
- η
-
thermal efficiency
- SP
-
specific power (kW/kg/s)
References
1. McDonald, CF, Massardo, AF, Rodgers, C, Stone, A. Recuperated gas turbine aeroengines, part II: engine design studies following early development testing. Aircraft Eng Aero Technol 2008;80:280–94. https://doi.org/10.1108/00022660810873719.Suche in Google Scholar
2. McDonald, CF, Wilson, DG. The utilization of regenerative and recuperative cycles for high efficiency gas turbines in the 21st century. J Appl Therm Eng 1996;16:635–53. https://doi.org/10.1016/1359-4311(95)00078-X.Suche in Google Scholar
3. McDonald, CF, Langworthy, RA. Advanced regenerative gas turbine for lightweight and high performance, ASME paper 1971-GT-67; 1971.Suche in Google Scholar
4. Andriani, R, Ghezzi, U. Influence of heat recovery and intercooling on Turboprop engine behaviour. Int J Turbo Jet Engines 2008;25:259–67. https://doi.org/10.1515/TJJ.2008.25.4.259.Suche in Google Scholar
5. Andriani, R, Ghezzi, U. Main performances of a Turboprop engine with heat exchange and intercooling. In: 2nd EUCASS – European Conference for Aerospace Sciences. Bruxelles; 2007.Suche in Google Scholar
6. Çay, Y, Çiçek, A, Kara, F, Saǧiroǧlu, S. Prediction of engine performance for an alternative fuel using artificial neural network. Appl Therm Eng 2012;37:217–25. https://doi.org/10.1016/j.applthermaleng.2011.11.019.Suche in Google Scholar
7. Kapusuz, M, Ozcan, H, Ahmad, J. Research of performance on a spark ignition engine fueled by alcohol – gasoline blends using artificial neural networks. Appl Therm Eng 2015;91:525–34. https://doi.org/10.1016/j.applthermaleng.2015.08.058.Suche in Google Scholar
8. Deh Kiani, MK, Ghobadian, B, Tavakoli, T, Nikbakht, AM, Najafi, G. Application of artificial neural networks for the prediction of performance and exhaust emissions in SI engine using ethanol – gasoline blends. Energy 2010;35:65–9. https://doi.org/10.1016/j.energy.2009.08.034.Suche in Google Scholar
9. Yu, HS, Arcakliog, E, Topgül, T, Arcaklioğlu, E. Comparative study of mathematical and experimental analysis of spark ignition engine performance used ethanol – gasoline blend fuel. Appl Therm Eng 2007;27:358–68. https://doi.org/10.1016/j.applthermaleng.2006.07.027.Suche in Google Scholar
10. Danaiah, P, Kumar, PR, Rao, YVH. Performance and emission prediction of a tert butyl alcohol gasoline blended spark ignition engine using artificial neural networks. Int J Ambient Energy 2013;36:37–41. https://doi.org/10.1080/01430750.2013.820147.Suche in Google Scholar
11. Tosun, E, Aydin, K, Merola, SS, Irimescu, A. Estimation of operational parameters for a direct injection turbocharged spark ignition engine by using regression analysis and artificial neural network. Therm Sci 2007;21:401–12. https://doi.org/10.2298/TSCI160302151T.Suche in Google Scholar
12. Cay, Y. Prediction of a gasoline engine performance with artificial neural network. Fuel 2013;111:324–31. https://doi.org/10.1016/j.fuel.2012.12.040.Suche in Google Scholar
13. Şahin, F. Effects of engine parameters on ionization current and modeling of excess air coefficient by artificial neural network. Appl Therm Eng 2015;90:94–101. https://doi.org/10.1016/j.applthermaleng.2015.06.100.Suche in Google Scholar
14. Çay, Y, Korkmaz, I, Çiçek, A, Kara, F. Prediction of engine performance and exhaust emissions for gasoline and methanol using artificial neural network. Energy 2013;50:177–86. https://doi.org/10.1016/j.energy.2012.10.052.Suche in Google Scholar
15. Najafi, G, Ghobadian, B, Tavakoli, T, Buttsworth, D, Yusaf, T, Faizollahnejad, M. Performance and exhaust emissions of a gasoline engine with ethanol blended gasoline fuels using artificial neural network. Appl Energy 2008;86:630–9. https://doi.org/10.1016/j.apenergy.2008.09.017.Suche in Google Scholar
16. Liu, W, Safdari, SM, Tlili, I, Maleki, A, Bach, QV. The effect of alcohol–gasoline fuel blends on the engines’ performances and emissions. Fuel 2020;276:117977. https://doi.org/10.1016/j.fuel.2020.117977.Suche in Google Scholar
17. Bietresato, M, Calcante, A, Mazzetto, F. A neural network approach for indirectly estimating farm tractors engine performances. Fuel 2015;143:144–54. https://doi.org/10.1016/j.fuel.2014.11.019.Suche in Google Scholar
18. Gürgen, S, Ünver, B, Altın, İ. Prediction of cyclic variability in a diesel engine fueled with n-butanol and diesel fuel blends using artificial neural network. Renew Energy 2018;117:538–44. https://doi.org/10.1016/j.renene.2017.10.101.Suche in Google Scholar
19. Yusaf, TF, Yousif, BF, Elawad, MM. Crude palm oil fuel for diesel-engines: experimental and ANN simulation approaches. Energy 2011;36:4871–8. https://doi.org/10.1016/j.energy.2011.05.032.Suche in Google Scholar
20. Vinay Kumar, D, Ravi Kumar, P, Kumari, MS. Prediction of performance and emissions of a biodiesel fueled lanthanum zirconate coated direct injection diesel engine using artificial neural networks. Procedia Eng 2013;64:993–1002. https://doi.org/10.1016/j.proeng.2013.09.176.Suche in Google Scholar
21. Oğuz, H, Sarıtas, I, Baydan, HE. Prediction of diesel engine performance using biofuels with artificial neural network. Expert Syst Appl 2010;37:6579–86. https://doi.org/10.1016/j.eswa.2010.02.128.Suche in Google Scholar
22. Andriani, R, Gamma, F, Ghezzi, U. Thermodynamic Analysis of a Turboprop Engine with Intercooling and Heat Recovery. Trans Japan Soc Aero Space Sci 2011;54:44–50. https://doi.org/10.2322/tjsass.54.44.Suche in Google Scholar
23. Yang, KT. Artificial neural networks (ANNs): a new paradigm for thermal science and engineering. J Heat Tran 2008;130:093001. https://doi.org/10.1115/1.2944238.Suche in Google Scholar
24. Quadros, JD, Zenginer, MY, Ozdemir, IB. Optimization of the bubble departure and lift-off boiling model using Taguchi method. Heat Tran Eng 2023;44:1816–32. https://doi.org/10.1080/01457632.2022.2162010.Suche in Google Scholar
25. Zenginer, MY, Quadros, JD, Ozdemir, IB. Determination of wall heat flux based on bubble departure and lift-off diameters for varying pressure and flow velocity conditions. Heat Tran Res 2023;54:85–101. https://doi.org/10.1080/01457632.2022.2162010.Suche in Google Scholar
26. Jang, JS. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 1993;23:665–8. https://doi.org/10.1109/21.256541.Suche in Google Scholar
27. Adetunji, O, Okwu, MO. A comparative study of artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) models in distribution system with nondeterministic inputs. Int J Eng Bus Manag 2018;10:1–17. https://doi.org/10.1109/21.256541.Suche in Google Scholar
28. Okwu, MO, Tartibu, LK. Sustainable supplier selection in the retail industry: a TOPSIS- and ANFIS-based evaluating methodology. Int J Eng Bus Manag 2020;12:1–14. https://doi.org/10.1177/1847979019899542.Suche in Google Scholar
29. Manjunath Patel, GC, Krishna, P, Vundavilli, PR, Parappagoudar, MB. Multi-objective optimization of squeeze casting process using genetic algorithm and particle swarm optimization. Arch Foundry Eng 2016;16:172–86. https://doi.org/10.1515/afe-2016-0073.Suche in Google Scholar
30. Jagadish Babu, C, Mathews, PS, Antonio, D, Mishra, RK. Prediction of compressor nominal characteristics of a Turboprop engine using artificial neural networks for build standard assessment. Int J Turbo Jet Engines 2023;40:11–20. https://doi.org/10.1515/tjj-2020-0015.Suche in Google Scholar
© 2024 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Experimental and numerical investigations on controlled parameter selection methods for kerosene-fueled scramjet
- Thrust-matching and optimization design of turbine-based combined cycle engine with trajectory optimization
- Parametric analysis of thermal cycle of a short take-off and vertical landing engine
- Conjugate heat transfer analysis on double-wall cooling configuration including jets impingement and film holes with conformal pins
- Research on the design method of mode transition control law for Ma6 external parallel TBCC engine
- A new schedule method for compact propulsion system model
- Numerical investigation on mixing of heated confined swirling coaxial jets with blockage
- Finite element based dynamic analysis of a porous exponentially graded shaft system subjected to thermal gradients
- Numerical study on aerodynamic performance of an intake duct affected by ground effect
- Influence of metal magnesium addition on detonation initiation in shock wave focusing Pulse Detonation Engine
- Probabilistic analysis of solid oxide fuel-cell integrated with gas turbine
- Improving thermal performance of turbine blade with combination of circular and oblong fins in a wedge channel: a numerical investigation
- Investigation on effect of injector orifice diameter on injector atomization and combustion characteristics of pulse detonation combustor
- Research on cascade control method for turboshaft engine with variable rotor speed
- The overall film cooling performance of crescent holes
- Air tab location effect on supersonic jet mixing
- Design and analysis of air intake of subsonic cruise vehicle with experimental validation
- Research on an optimization design method for a TBCC propulsion scheme
- Performance analysis of a gas turbine engine via intercooling and regeneration- Part 2
- Effects of bleed pressure on shock-wave/boundary-layer interactions in a transonic compressor stator with suction holes
- Effect of asymmetric leading edge on transition of suction side
Artikel in diesem Heft
- Frontmatter
- Experimental and numerical investigations on controlled parameter selection methods for kerosene-fueled scramjet
- Thrust-matching and optimization design of turbine-based combined cycle engine with trajectory optimization
- Parametric analysis of thermal cycle of a short take-off and vertical landing engine
- Conjugate heat transfer analysis on double-wall cooling configuration including jets impingement and film holes with conformal pins
- Research on the design method of mode transition control law for Ma6 external parallel TBCC engine
- A new schedule method for compact propulsion system model
- Numerical investigation on mixing of heated confined swirling coaxial jets with blockage
- Finite element based dynamic analysis of a porous exponentially graded shaft system subjected to thermal gradients
- Numerical study on aerodynamic performance of an intake duct affected by ground effect
- Influence of metal magnesium addition on detonation initiation in shock wave focusing Pulse Detonation Engine
- Probabilistic analysis of solid oxide fuel-cell integrated with gas turbine
- Improving thermal performance of turbine blade with combination of circular and oblong fins in a wedge channel: a numerical investigation
- Investigation on effect of injector orifice diameter on injector atomization and combustion characteristics of pulse detonation combustor
- Research on cascade control method for turboshaft engine with variable rotor speed
- The overall film cooling performance of crescent holes
- Air tab location effect on supersonic jet mixing
- Design and analysis of air intake of subsonic cruise vehicle with experimental validation
- Research on an optimization design method for a TBCC propulsion scheme
- Performance analysis of a gas turbine engine via intercooling and regeneration- Part 2
- Effects of bleed pressure on shock-wave/boundary-layer interactions in a transonic compressor stator with suction holes
- Effect of asymmetric leading edge on transition of suction side