ISSN: 1546-962X
CODEN: JAIOAD
Published Online: 30
August 2004
Page Count: 16
A Software Framework for Probabilistic Fatigue Life Assessment of Gas Turbine Engine Rotors
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.
Keywords:
fatigue crack growth, damage tolerance, software, gas turbine engines, probabilistic methods, reliability, hard alpha, life scatter
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