TSOUTSANIS, Elias, MESKIN, Nader, BENAMMAR, Mohieddine and KHORASANI, Khashayar (2014). A component map tuning method for performance prediction and diagnostics of gas turbine compressors. Applied Energy, 135, 572-585.
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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. © 2014 Elsevier Ltd.
Item Type: | Article |
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Additional Information: | cited By 15 |
Uncontrolled Keywords: | Aircraft propulsion; Compressibility of gases; Condition monitoring; Curve fitting; Engines; Forecasting; Gas compressors; Gas plants; Gas turbines; Gases; Multiobjective optimization; Turbine components, Component map; Engine performance models; Gas turbine diagnostics; Model Adaptation; Monitoring and diagnostics; Multi-objective optimization scheme; Performance prediction; Steady state and transients, Gas turbine power plants, map; multiobjective programming; numerical model; performance assessment; power plant; prediction; software; turbine |
Departments - Does NOT include content added after October 2018: | Faculty of Science, Technology and Arts > Department of Engineering and Mathematics |
Identification Number: | https://doi.org/10.1016/j.apenergy.2014.08.115 |
Page Range: | 572-585 |
Depositing User: | Elias Tsoutsanis |
Date Deposited: | 16 Aug 2017 15:40 |
Last Modified: | 18 Mar 2021 04:02 |
URI: | https://shura.shu.ac.uk/id/eprint/16181 |
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