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    Component Map Generation of a Gas Turbine Using Genetic Algorithms

    Source: Journal of Engineering for Gas Turbines and Power:;2006:;volume( 128 ):;issue: 001::page 92
    Author:
    Changduk Kong
    ,
    Seonghee Kho
    ,
    Jayoung Ki
    DOI: 10.1115/1.2032431
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: 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.
    keyword(s): Pressure , Flow (Dynamics) , Gases , Engines , Compressors , Gas turbines , Equations , Genetic algorithms , Turbines , Sensors AND Errors ,
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      Component Map Generation of a Gas Turbine Using Genetic Algorithms

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    http://yetl.yabesh.ir/yetl1/handle/yetl/133720
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorChangduk Kong
    contributor authorSeonghee Kho
    contributor authorJayoung Ki
    date accessioned2017-05-09T00:19:55Z
    date available2017-05-09T00:19:55Z
    date copyrightJanuary, 2006
    date issued2006
    identifier issn1528-8919
    identifier otherJETPEZ-26894#92_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/133720
    description abstractIn 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.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleComponent Map Generation of a Gas Turbine Using Genetic Algorithms
    typeJournal Paper
    journal volume128
    journal issue1
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.2032431
    journal fristpage92
    journal lastpage96
    identifier eissn0742-4795
    keywordsPressure
    keywordsFlow (Dynamics)
    keywordsGases
    keywordsEngines
    keywordsCompressors
    keywordsGas turbines
    keywordsEquations
    keywordsGenetic algorithms
    keywordsTurbines
    keywordsSensors AND Errors
    treeJournal of Engineering for Gas Turbines and Power:;2006:;volume( 128 ):;issue: 001
    contenttypeFulltext
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