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Stochastic modeling of fatigue crack dynamics for risk analysis and remaining life prediction

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1 Author(s)
A. Ray ; Dept. of Mech. Eng., Pennsylvania State Univ., University Park, PA, USA

This paper presents a stochastic dynamic model of fatigue crack propagation in metallic materials which are commonly encountered in mechanical structures and machine components of complex systems. The (non-stationary) statistics of the crack growth process are obtained without solving stochastic differential equations in the Wiener integral or Ito integral setting. The crack propagation model thus allows real-time execution of decision algorithms for risk assessment and life prediction on inexpensive platforms (such as a Pentium processor). The model predictions are in close agreement with experimental data of fatigue crack statistics for 2024-T3 and 7075-T6 aluminum alloys

Published in:

American Control Conference, 1998. Proceedings of the 1998  (Volume:4 )

Date of Conference:

21-26 Jun 1998