• Title/Summary/Keyword: Compressor Map Identification

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A Study on Compressor Map Identification using Artificial Intelligent Technique and Performance Deck Data (인공지능 및 성능덱 데이터를 이용한 압축기 성능도 식별에 관한 연구)

  • Ki Ja-Young;Kong Chang-Duck;Lee Chang-Ho
    • Journal of the Korean Society of Propulsion Engineers
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    • v.9 no.4
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    • pp.81-88
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    • 2005
  • In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.

A Study on Compressor Map Identification using Artificial Intelligent Technique and Performance Deck Data (인공지능 및 성능덱 데이터를 이용한 압축기 성능도 식별에 관한 연구)

  • Kong Chang-Duck;Ki Ja-Young;Lee Chang-Ho
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2005.11a
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    • pp.149-153
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    • 2005
  • In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

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