The data driven surrogate model based dynamic design of aero-engine fan systems

Zhu, Yun-Peng and Yuan, Jie and Lang, Z. Q. and Schwingshackl, C. W. and Salles, Loic and Kadirkamanathan, V.; (2021) The data driven surrogate model based dynamic design of aero-engine fan systems. In: Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers(ASME), Virtual, Online. ISBN 978-0-7918-8422-5 (https://doi.org/10.1115/GT2020-14272)

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Abstract

High cycle fatigue failures of fan blade systems due to vibrational loads are of great concern in the design of aero engines, where energy dissipation by the relative frictional motion in the dovetail joints provides the main damping to mitigate the vibrations. The performance of such a frictional damping can be enhanced by suitable coatings. However, the analysis and design of coated joint roots of gas turbine fan blades are computationally expensive due to strong contact friction nonlinearities and also complex physics involved in the dovetail. In this study, a data driven surrogate model, known as the Nonlinear in Parameter AutoRegressive with eXegenous input (NP-ARX) model, is introduced to circumvent the difficulties in the analysis and design of fan systems. The NP-ARX model is a linear input-output model, where the model coefficients are nonlinear functions of the design parameters of interest, such that the Frequency Response Function (FRF) can be directly obtained and used in the system analysis and design. A simplified fan bladed disc system is considered as the test case. The results show that by using the data driven surrogate model, an efficient and accurate design of aero-engine fan systems can be achieved. The approach is expected to be extended to solve the analysis and design problems of many other complex systems.

ORCID iDs

Zhu, Yun-Peng, Yuan, Jie ORCID logoORCID: https://orcid.org/0000-0002-2411-8789, Lang, Z. Q., Schwingshackl, C. W., Salles, Loic and Kadirkamanathan, V.;
  • Item type:Book Section
    ID code:76014
    Dates:
    Date
    Event
    11 January 2021
    Published
    25 September 2020
    Published Online
    6 August 2020
    Accepted
    Subjects:Technology > Mechanical engineering and machinery
    Department:UNSPECIFIED
    Depositing user: Pure Administrator
    Date deposited:06 Apr 2021 08:43
    Last modified:11 Nov 2024 15:24
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/76014
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