Demonstration of advanced life-prediction and state-awareness technologies necessary for prognosis of turbine engine disks

Stephan M. Russ; Andrew H. Rosenberger; James M. Larsen; Robert B. Berkley; David Carroll; Bradford A. Cowles; Richard A. Holmes; Jerrol W. Littles Jr.; Richard G. Pettit; John J. Schirra

doi:10.1117/12.540404

21 July 2004 Demonstration of advanced life-prediction and state-awareness technologies necessary for prognosis of turbine engine disks

Stephan M. Russ, Andrew H. Rosenberger, James M. Larsen, Robert B. Berkley, David Carroll, Bradford A. Cowles, Richard A. Holmes, Jerrol W. Littles Jr., Richard G. Pettit, John J. Schirra

Author Affiliations +

Proceedings Volume 5394, Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III; (2004) https://doi.org/10.1117/12.540404
Event: NDE for Health Monitoring and Diagnostics, 2004, San Diego, CA, United States

Abstract

This paper summarizes a spin test of an IN100 minidisk that demonstrated advanced fatigue crack growth predictive tools under dwell fatigue and the ability to infer the damage state from state-awareness sensed data. The test was performed at elevated temperature in a partial vacuum and was a major success. The advantages of employing 3D fracture mechanics tools were clearly demonstrated when the prediction using the advanced analysis technique produced a crack growth lifetime 10 times greater than the standard 2D tools and well within a factor of two of the test result. However, when the effect of the partial vacuum was also taken into account, the predictions more closely resembled the test results. Another success was demonstrated when the "blade-tip" time-of-arrival sensors detected deflections of 50 microns and greater at temperature. Using the 3D analysis tools, a transfer function was created that related blade-tip deflection to crack size. The crack size was tracked in near real time for the final 150 cycles. This test represented significant demonstrations of both 3D fracture mechanics tools and state-awareness sensing. Both are advanced technologies that will eventually impact the life management of turbine engines.

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Stephan M. Russ, Andrew H. Rosenberger, James M. Larsen, Robert B. Berkley, David Carroll, Bradford A. Cowles, Richard A. Holmes, Jerrol W. Littles Jr., Richard G. Pettit, and John J. Schirra "Demonstration of advanced life-prediction and state-awareness technologies necessary for prognosis of turbine engine disks", Proc. SPIE 5394, Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems III, (21 July 2004); https://doi.org/10.1117/12.540404

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