A Software Framework for Probabilistic Fatigue Life Assessment of Gas Turbine Engine Rotors

    Volume 1, Issue 8 (September 2004)

    ISSN: 1546-962X

    CODEN: JAIOAD

    Published Online: 30 August 2004

    Page Count: 16


    McClung, RC
    Senior Program Manager, Principal Engineer, Program Director, and Institute Scientist, Southwest Research Institute, San Antonio, TX

    Enright, MP
    Senior Program Manager, Principal Engineer, Program Director, and Institute Scientist, Southwest Research Institute, San Antonio, TX

    Millwater, HR
    Assistant Professor, University of Texas at San Antonio, San Antonio, TX

    Leverant, GR
    Senior Program Manager, Principal Engineer, Program Director, and Institute Scientist, Southwest Research Institute, San Antonio, TX

    Hudak, SJ
    Senior Program Manager, Principal Engineer, Program Director, and Institute Scientist, Southwest Research Institute, San Antonio, TX

    (Received 4 November 2002; accepted 24 October 2003)

    Abstract

    An enhanced life management process based on probabilistic damage tolerance methods has been developed to address material anomalies in titanium rotating components of gas turbine engines. Related methods are being used as tools to investigate the impact of engine monitoring and usage variability on prognosis for field readiness and life management. This paper begins with an overview of the process of probabilistic damage tolerant design, using the DARWIN® computer program to illustrate the interplay between various random variables and the conventional elements of structural design and life prediction. Special attention is then given to the initial distribution of material anomalies, scatter in fatigue crack growth data, and variability in complex mission histories. The significance of each source of variability for different applications is discussed.


    Paper ID: JAI11563

    DOI: 10.1520/JAI11563

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    Author
    Title A Software Framework for Probabilistic Fatigue Life Assessment of Gas Turbine Engine Rotors
    Symposium Probabilistic Aspects of Life Prediction, 2002-11-06
    Committee E08