Prediction of dynamic behavior of a single shaft gas turbine using narx models

Hamid Asgari, Emmanuel Ory

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    1 Citation (Scopus)

    Abstract

    Gas turbines are internal combustion engines widely used in industry as main source of power for aircrafts, turbo-generators, turbo-pumps and turbo-compressors. Modelling these engines can help to improve their design and manufacturing processes, as well as to facilitate their operability and maintenance. These eventually lead to manufacturing of gas turbines with lower costs and higher efficiency at the same time. The models may also be employed to unfold nonlinear dynamics of these systems. The aim of this study is to predict the dynamic behavior of a single shaft gas turbine by using open-loop and closed-loop NARX models, which are subsets of artificial neural networks. To set up these models, datasets of significant variables of the gas turbine are used for training, test and validation processes. For this purpose, a comprehensive code is developed in MATLAB programming environment. In addition to the openloop model, a closed-loop model is set up for multi-step prediction. The results of this study demonstrate the capability of the NARX models in reliable prediction of gas turbines' dynamic behaviors over different operational ranges.

    Original languageEnglish
    Title of host publicationTurbo Expo: Power for Land, Sea, and Air
    Subtitle of host publicationVolume 6: Ceramics and Ceramic Composites; Coal, Biomass, Hydrogen, and Alternative Fuels; Microturbines, Turbochargers, and Small Turbomachines
    PublisherAmerican Society of Mechanical Engineers (ASME)
    Number of pages10
    ISBN (Electronic)978-0-7918-8499-7
    DOIs
    Publication statusPublished - 2021
    MoE publication typeA4 Article in a conference publication
    EventASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition, GT 2021 - Virtual, Online
    Duration: 7 Jun 202111 Jun 2021

    Conference

    ConferenceASME Turbo Expo 2021: Turbomachinery Technical Conference and Exposition, GT 2021
    CityVirtual, Online
    Period7/06/2111/06/21

    Keywords

    • Artificial neural network
    • Black-box model
    • Dynamic behavior
    • Gas turbine
    • Modelling
    • NARX model
    • Simulation

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