Abstract
This paper presents a nonlinear stochastic model for prediction of fatigue crack damage in metallic materials. The model structure allows estimation of the current damage state and prediction of the remaining service life based on the underlying principle of Gauss-Markov processes without solving the extended Kalman filter equation in the Wiener integral setting or the Kolmogorov forward equation in the Ito integral setting. The model results have been verified with experimentally-generated statistical data of time-dependent fatigue cracks for 2024-T3 and 7075-T6 aluminum alloys.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
