A nonlinear stochastic model of fatigue crack dynamics

Asok Ray, Sekhar Tangirala

    Research output: Contribution to journalArticle

    24 Citations (Scopus)

    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 Itô 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.

    Original languageEnglish (US)
    Pages (from-to)33-40
    Number of pages8
    JournalProbabilistic Engineering Mechanics
    Volume12
    Issue number1
    StatePublished - Jan 1997

    Fingerprint

    Stochastic models
    cracks
    Extended Kalman filters
    Model structures
    Service life
    Markov processes
    damage
    Aluminum alloys
    service life
    Kalman filters
    predictions
    aluminum alloys
    Fatigue cracks

    All Science Journal Classification (ASJC) codes

    • Mechanical Engineering
    • Safety, Risk, Reliability and Quality

    Cite this

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    A nonlinear stochastic model of fatigue crack dynamics. / Ray, Asok; Tangirala, Sekhar.

    In: Probabilistic Engineering Mechanics, Vol. 12, No. 1, 01.1997, p. 33-40.

    Research output: Contribution to journalArticle

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    AB - 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 Itô 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.

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