In order to estimate the precise performance of the existing gas turbine engine, the component maps with more realistic performance characteristics are needed. Because the component maps are the engine manufacturer’s propriety obtained from very expensive experimental tests, they are not provided to the customers, generally. Therefore, because the engineers, who are working the performance simulation, have been mostly relying on component maps scaled from the similar existing maps, the accuracy of the performance analysis using the scaled maps may be relatively lower than that using the real component maps. Therefore, a component map generation method using experimental data and the genetic algorithms are newly proposed in this study. The engine test unit to be used for map generation has a free power turbine type small turboshaft engine. In order to generate the performance map for compressor of this engine, after obtaining engine performance data through experimental tests, and then the third order equations, which have relationships with the mass flow function, the pressure ratio, and the isentropic efficiency as to the engine rotational speed, were derived by using the genetic algorithms. A steady-state performance analysis was performed with the generated maps of the compressor by the commercial gas turbine performance analysis program GASTURB (Kurzke, 2001). In order to verify the proposed scheme, the experimental data for verification were compared with performance analysis results using traditional scaled component maps and performance analysis results using a generated compressor map by genetic algorithms (GAs). In comparison, it was found that the analysis results using the generated map by GAs were well agreed with experimental data. Therefore, it was confirmed that the component maps can be generated from the experimental data by using GAs and it may be considered that the more realistic component maps can be obtained if more various conditions and accurate sensors would be used.
Skip Nav Destination
e-mail: cdgong@mail.chosun.ac.kr
e-mail: habari@paran.com
e-mail: setgods@hotmail.com
Article navigation
January 2006
Technical Papers
Component Map Generation of a Gas Turbine Using Genetic Algorithms
Changduk Kong,
Changduk Kong
Department of Aerospace Engineering,
e-mail: cdgong@mail.chosun.ac.kr
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Korea
Search for other works by this author on:
Seonghee Kho,
Seonghee Kho
Department of Aerospace Engineering,
e-mail: habari@paran.com
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Korea
Search for other works by this author on:
Jayoung Ki
Jayoung Ki
Department of Aerospace Engineering,
e-mail: setgods@hotmail.com
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Korea
Search for other works by this author on:
Changduk Kong
Department of Aerospace Engineering,
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Koreae-mail: cdgong@mail.chosun.ac.kr
Seonghee Kho
Department of Aerospace Engineering,
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Koreae-mail: habari@paran.com
Jayoung Ki
Department of Aerospace Engineering,
Chosun University
, #375 Seosuk-dong, Dong-gu, Gwangju 501-759, Koreae-mail: setgods@hotmail.com
J. Eng. Gas Turbines Power. Jan 2006, 128(1): 92-96 (5 pages)
Published Online: March 1, 2004
Article history
Received:
October 1, 2003
Revised:
March 1, 2004
Citation
Kong, C., Kho, S., and Ki, J. (March 1, 2004). "Component Map Generation of a Gas Turbine Using Genetic Algorithms." ASME. J. Eng. Gas Turbines Power. January 2006; 128(1): 92–96. https://doi.org/10.1115/1.2032431
Download citation file:
Get Email Alerts
Experimental Identification Of Blade Tip Rub Forces At Engine Relevant Temperatures And Speeds
J. Eng. Gas Turbines Power
Study Of Tandem Rotor Dual Wake Interaction With Downstream Stator Under Unsteady Numerical Approach
J. Eng. Gas Turbines Power
Experimental Design Validation of a Swirl-Stabilized Burner With Fluidically Variable Swirl Number
J. Eng. Gas Turbines Power (April 2025)
Experimental Characterization of a Bladeless Air Compressor
J. Eng. Gas Turbines Power (April 2025)
Related Articles
Nonlinear Multiple Points Gas Turbine Off-Design Performance Adaptation Using a Genetic Algorithm
J. Eng. Gas Turbines Power (July,2011)
Components Map Generation of Gas Turbine Engine Using Genetic Algorithms and Engine Performance Deck Data
J. Eng. Gas Turbines Power (April,2007)
Improved Multiple Point Nonlinear Genetic Algorithm Based Performance Adaptation Using Least Square Method
J. Eng. Gas Turbines Power (March,2012)
Off-Design Performance Investigation of a Low Calorific Value Gas Fired Generic-Type Single-Shaft Gas Turbine
J. Eng. Gas Turbines Power (May,2008)
Related Proceedings Papers
Related Chapters
Outlook
Closed-Cycle Gas Turbines: Operating Experience and Future Potential
The Special Characteristics of Closed-Cycle Gas Turbines
Closed-Cycle Gas Turbines: Operating Experience and Future Potential
Thermodynamic Performance
Closed-Cycle Gas Turbines: Operating Experience and Future Potential