Document Type : Research Paper


1 Mechanical Engineering Dept., Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Perak, Malaysia.

2 Centre for Automotive Research and Electric Mobility (CAREM), Universiti Teknologi PETRONAS, 32610 Seri Iskandar, Perak, Malaysia.


This research work presents a gas turbine performance investigation. Researchers have put efforts into this field of study; however, the influence of the concurrence of variable inlet guide vane (VIGV) drift, fouling, and erosion on the three-shaft gas turbine’s performance during part-load operation has remained unexplored. Therefore, this study addresses this gap. First the gas turbine design point and off-design performance model have been developed by utilizing the original engine manufacturer data provided. The accuracy of the models was validated, and the maximum mean absolute percentage error of the design point performance model is shown at exhaust temperature prediction, it is about 1.74%. The off-design performance model was also validated with the power output versus ambient temperature and efficiency versus operating curves. At each operational point, the power output versus ambient temperature error from the validation data was 0.02%, while the efficiency versus ambient temperature error was 4.5%. After the validation, the engine model was subjected to the concurrence of variable inlet guide vane drift, fouling, and erosion conditions to simulate the degradation state. The results show that the highest isentropic efficiency deviation due to component faults occurred in the upstream components, specifically in the low-pressure compressor’s (LPC) isentropic efficiency. The deviation recorded due to the concurrence of VIGV drift at -6.5° and 100% fouling severity is -11.47%, whereas 9.65% is the LPC isentropic efficiency deviation recorded when VIGV drift at -6.5° and erosion at 100% severity level simultaneously occurred. In addition, the effects of the faults above on gas path measurements were simulated, and the highest measurement deviation was observed when simultaneous LPC fouling and -6.5% VIGV drift occurred. Among the measurements, the highest deviation was observed in the exhaust temperature and thermal efficiency, about 9.23% and -7.35%, respectively.

Graphical Abstract


  • Effects of drift, fouling, and erosion on gas turbine efficiency and output are investigated.
  • Fouling impacts upstream, while erosion affects downstream components in gas turbines.
  • Research findings support ML-based fault detection for optimal turbine maintenance.


Main Subjects

  1. Li, S. S. Zhong, and L. Lin, Novel gas turbine fault diagnosis method based on performance deviation model, J. Propuls. Power, 33 (2017) 730–739. 10.2514/1.B36267
  2. Towoju, Impact of Cooling Fluid Temperature on the Structural Integrity of Gas Turbine Stator Blades, Eng. Technol. J., 41 (2023)1-9.
  3. J. Abdulah, M. Z. Khalifa, and A. J. O. Hanfesh, Reducing vibrations generated in a gas turbine model MS9001E used in south Baghdad power plant station by improving the design of bearings with damper , Eng. Technol. J., 39 (2021) 1454-1462.
  4. Merrington, O. K. Kwon, G. Goodwin, and B. Carlsson, Fault detection and diagnosis in gas turbines, Proc. ASME Turbo. Expo., 5 (1990)1-10.
  5. I.H Saravanamuttoo and A.N Lakshminarasimha, A preliminary assessment of compressor fouling, American Society of Mechanical Engineer, 1985.
  6. K. Mishra, Fouling and Corrosion in an Aero Gas Turbine Compressor, J. Fail. Anal. Prev., 15 (2015) 837–845.
  7. S. Diakunchak, Performance deterioration in industrial gas turbines, Proc. ASME Turbo. Expo., 4 (1991)1-8.
  8. Singh Grewal, M. Gas turbine engine performance deterioration modelling and analysis supervisor, cranfield institute of technologyschool of mechanical engineering ph.d thesis,1988.
  9. Gmbh, GasTurb 13 Design and Off-Design Performance of Gas Turbines, 85221 Dachau, Max Feldbauer Weg 5, Germany, 2018.
  10. North Atlantic Treaty Organisation, Performance Prediction and Simulation of Gas Turbine Engine Operation for Aircraft , Marine , Vehicular , and Power Generation, Estimation et simulation des performances du fonctionnement, 2007.
  11. Tahan, E. Tsoutsanis, M. Muhammad, and Z. A. Abdul Karim, Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review, Appl. Energy, 198 (2017) 122–144.
  12. Haglind, Variable geometry gas turbines for improving the part-load performance of marine combined cycles - Gas turbine performance, Energy, 35 (2010) 562–570.
  13. H. Kim, T. W. Song, T. S. Kim, and S. T. Ro, Dynamic simulation of full start-up procedure of heavy-duty gas turbines, J. Eng. Gas Turbines Power, 124 (2002) 510–516.
  14. Bringhenti, C, Tomita, JT, de Sousa Ju´nior, F, and Barbosa, JR. 2006.Gas Turbine Performance Simulation Using an Optimized Axial Flow Compressor, Proceedings of the ASME Turbo Expo 2006: Power for Land, Sea, and Air. Turbomachinery, Parts A and B. Barcelona, Spain. Vol. 6, pp. 1941-1948. ASME.
  15. M. Salilew, Z. A. A. Abdul Karim, T. A. Lemma, A. D. Fentaye, and K. G. Kyprianidis, Predicting the Performance Deterioration of a Three-Shaft Industrial Gas Turbine, Entropy, 24 (2022) 1052.
  16. W. Song, T. S. Kim, J. H. Kim, and S. T. Ro,Performance prediction of axial flow compressors using stage characteristics and simultaneous calculation of interstage parameters, Proc. Inst. Mech. Eng. A: J. Power Energy, 215 (2001) 89-98.
  17. Salar, S. M. Hosseini, B. R. Zangmolk and A. K. Sedigh, Improving Model-Based Gas Turbine Fault Diagnosis Using Multi-Operating Point Method, 2010 Fourth UKSim European Symposium on Computer Modeling and Simulation, Pisa, Italy, 2010, 240-247.
  18. Tsalavoutas, K. Mathioudakis, A. Stamatis, and M. Smith, Identifying faults in the variable geometry system of a gas turbine compressor, J. Turbomach., 123 (2001) 33-39.
  19. Stamatis, A., Mathioudakis, K. and Papailiou, K. D. Adaptive simulation of Gas Turbine performance, Proceedings of the ASME Turbo Expo, 1989.
  20. Cruz-Manzo, S. Maleki, V. Panov, and Y. E. Zhang, Performance analysis of a twin-shaft gas turbine with fault in the variable stator guide vane system of the axial compressor, The Future of Gas Turbine Technology 9th International Gas Turbine Conference, Brussels, Belgium, 2018.
  21. M. Y Razak and M. S. Dosanjh, Application of an advanced performance monitoring system to detect an implanted fault on a twin spool aero derived gas turbine, Amsterdam, The Netherlands, 2002.
  22. Enyia, I. Thank-God, D. Igbong, and J. Diwa, Industrial gas turbine on-line compressor washing for power generation, Int. J. Eng. Res. Technol., 4 (2015) 500-506.
  23. J .Ajoko‏, Performance monitoring of industrial gas turbine, Int. J. Eng. Sci. Invention, 3 (2014) 62–68.
  24. M. Salilew, Z. A. A. Abdul Karim, T. A. Lemma, A. D. Fentaye, and K. G. Kyprianidis, Three Shaft Industrial Gas Turbine Transient Performance Analysis, Sensors, 23 (2023) 1767.
  25. Molla Salilew, Z. Ambri Abdul Karim, and T. Alemu Lemma, Investigation of fault detection and isolation accuracy of different Machine learning techniques with different data processing methods for gas turbine, Alex. Eng. J., 61 (2022) 12635–12651.
  26. Razak, A. M. Y. Industrial gas turbines: performance and operability, Woodhead Pub, 2007.
  27. B. Hashmi, T. A. Lemma, and Z. A. A. Karim, Investigation of the combined effect of variable inlet guide vane drift, fouling, and inlet air cooling on gas turbine performance, Entropy, 21 (2019) 1186.
  28. Razak, A. M. Y. 2013. Gas turbine performance modelling, analysis and optimization,Woodhead Publishing Limited, pp.423-514.
  29. kurkz, Design-Point Calculations of Industrial Gas Turbines, ASME, 2020.
  30. I. Ao, L. Gelman, D. W. L. Hukins, A. Hunter, A. Korsunsky, and International Association of Engineers, Design and Off-Design Operation and Performance Analysis of a Gas Turbine, Proceedings of the World Congress on Engineering. London, 2, 2018
  31. H. Gao and Y. Y. Huang, Modeling and simulation of a aero turbojet engine with GasTurb, 2011 Int. Conf. Intell. Sci. Inf. Eng., 2011, 295-298.
  32. S. Jasmani, Y. G. Li, and Z. Ariffin, Measurement selections for multicomponent gas path diagnostics using analytical approach and measurement subset concept, J. Eng. Gas Turbines Power, 133 (2011) 111701.
  33. Z. Chen, X. D. Zhao, H. C. Xiang, and E. Tsoutsanis, A sequential model-based approach for gas turbine performance diagnostics, Energy, 220 (2021) 119657.
  34. Kurzke, J. 2007.About Simplifications in Gas Turbine Performance Calculations. Proceedings of the ASME Turbo Expo 2007: Power for Land, Sea, and Air. Turbo Expo 2007. Montreal, Canada,Vol.3 1, pp. 493-501, ASME.
  35. P. Boyce , C. B. Meher-Homji, and A. N. Lakshminarasimha Modeling and Analysis of Gas Turbine Performance Deterioration, J. Eng. Gas Turbines Power, 116 (1994) 46-52.
  36. Efstratios Ntantis, Capability Expansion of Non-Linear Gas Path Analysis, PhD Thesis, Cranfield University, 2008.
  37. Qingcai, S. Li, Y. Cao, and N. Zhao, Full and Part-Load Performance Deterioration Analysis of Industrial Three-Shaft Gas Turbine Based on Genetic Algorithm, Proceedings of ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition, South Korea, 2016.
  38. Mohammadi ,M. Montazeri-Gh, Simulation of full and part-load performance deterioration of industrial two-shaft gas Turbine, J. Eng. Gas Turbines Power, 136 (2014) 9.
  39. M. Salilew, Z. A. A. Abdul Karim, T. A. Lemma, A. D. Fentaye, and K. G. Kyprianidis, The Effect of Physical Faults on a Three-Shaft Gas Turbine Performance at Full- and Part-Load Operation, Sensors, 22 (2022) 7150,