A component map tuning method for performance prediction and diagnostics of gas turbine compressors

Elias Tsoutsanis, Nader Meskin*, Mohieddine Benammar, Khashayar Khorasani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

68 Citations (Scopus)
229 Downloads (Pure)

Abstract

In this paper, a novel compressor map tuning method is developed with the primary objective of improving the accuracy and fidelity of gas turbine engine models for performance prediction and diagnostics. A new compressor map fitting and modeling method is introduced to simultaneously determine the best elliptical curves to a set of compressor map data. The coefficients that determine the shape of the compressor map curves are analyzed and tuned through a multi-objective optimization scheme in order to simultaneously match multiple sets of engine performance measurements. The component map tuning method, that is developed in the object oriented Matlab Simulink environment, is implemented in a dynamic gas turbine engine model and tested in off-design steady state and transient as well as degraded operating conditions. The results provided demonstrate and illustrate the capabilities of our proposed method in refining existing engine performance models to different modes of the gas turbine operation. In addition, the excellent agreement between the injected and the predicted degradation of the engine model demonstrates the potential of the proposed methodology for gas turbine diagnostics. The proposed method can be integrated with the performance-based tools for improved condition monitoring and diagnostics of gas turbine power plants.

Original languageEnglish
Pages (from-to)572-585
Number of pages14
JournalApplied Energy
Volume135
Early online date25 Sept 2014
DOIs
Publication statusPublished - 15 Dec 2014

Keywords

  • Component map
  • Condition monitoring
  • Gas turbine
  • Model adaptation
  • Performance prediction

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • General Energy

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