Stochastic measure of fatigue crack damage for health monitoring of ductile alloy structures

    Research output: Contribution to journalArticle

    14 Citations (Scopus)

    Abstract

    This paper models a stochastic measure of fatigue crack damage in ductile alloys that are commonly encountered in structures and machinery components of complex mechanical systems such as land, air, ocean, and space vehicles. The constitutive equations of the damage measure are built upon the physics of fracture mechanics and are substantiated by Karhunen-Loeve decomposition of fatigue test data where statistical orthogonality of the estimated measure and the resulting estimation error is demonstrated in a Hilbert space setting. The non-stationary probability distribution (PDF) function of the damage estimate is generated in a closed form without numerically solving stochastic differential equations in the Wiener integral or Itô integral setting. The model of crack damage measure allows real-time execution of decision algorithms for health monitoring, risk assessment, and life prediction of mechanical structures on inexpensive platforms such as a Pentium processor. The stochastic model of fatigue crack damage measure is in good agreement with experimental data sets for 2024-T3 and 7075-T6 aluminum alloys.

    Original languageEnglish (US)
    Pages (from-to)245-263
    Number of pages19
    JournalStructural Health Monitoring
    Volume3
    Issue number3
    DOIs
    StatePublished - Jan 1 2004

    Fingerprint

    Fatigue
    Health
    Monitoring
    Hilbert spaces
    Stochastic models
    Constitutive equations
    Fracture mechanics
    Risk assessment
    Error analysis
    Probability distributions
    Machinery
    Distribution functions
    Aluminum alloys
    Differential equations
    Physics
    Fatigue of materials
    Cracks
    Mechanics
    Aluminum
    Decomposition

    All Science Journal Classification (ASJC) codes

    • Biophysics
    • Mechanical Engineering

    Cite this

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    abstract = "This paper models a stochastic measure of fatigue crack damage in ductile alloys that are commonly encountered in structures and machinery components of complex mechanical systems such as land, air, ocean, and space vehicles. The constitutive equations of the damage measure are built upon the physics of fracture mechanics and are substantiated by Karhunen-Loeve decomposition of fatigue test data where statistical orthogonality of the estimated measure and the resulting estimation error is demonstrated in a Hilbert space setting. The non-stationary probability distribution (PDF) function of the damage estimate is generated in a closed form without numerically solving stochastic differential equations in the Wiener integral or It{\^o} integral setting. The model of crack damage measure allows real-time execution of decision algorithms for health monitoring, risk assessment, and life prediction of mechanical structures on inexpensive platforms such as a Pentium processor. The stochastic model of fatigue crack damage measure is in good agreement with experimental data sets for 2024-T3 and 7075-T6 aluminum alloys.",
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    Stochastic measure of fatigue crack damage for health monitoring of ductile alloy structures. / Ray, Asok.

    In: Structural Health Monitoring, Vol. 3, No. 3, 01.01.2004, p. 245-263.

    Research output: Contribution to journalArticle

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