• About
    • Login
    View Item 
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    •   Institutional Repository Home
    • Electronic Theses and Dissertations
    • Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of Institutional RepositoryCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsDepartmentThis CollectionBy Issue DateAuthorsTitlesSubjectsDepartment

    My Account

    LoginRegister

    Multi-Axial Fatigue Crack Growth Uncertainty Quantification and Risk Management

    Wolfe, Kevin Adam
    : https://etd.library.vanderbilt.edu/etd-08312012-155252
    http://hdl.handle.net/1803/14053
    : 2012-10-05

    Abstract

    The modeling and risk management of fatigue crack growth is a problem of critical importance in any mechanical system. The work presented in this study demonstrates two efficient methods for the modeling of non-planar fatigue crack growth and also the quantification of uncertainty in the model prediction. Discretization errors, both temporal and spatial, are considered for each model. The model parameters for crack growth models typically are obtained via experimental data. A methodology is presented here to calibrate those parameters when experimental errors are considered. The consideration of experimental errors leads to a more realistic approximation of the model parameters. A methodology for model calibration and validation using multiple sources of information is accomplished through a Bayesian network approach. Finally, natural variability, data uncertainty and model uncertainty are considered to provide an informed framework for risk management decision making with respect to inspection scheduling and fidelity.
    Show full item record

    Files in this item

    Icon
    Name:
    Wolfe.pdf
    Size:
    7.323Mb
    Format:
    PDF
    View/Open

    This item appears in the following collection(s):

    • Electronic Theses and Dissertations

    Connect with Vanderbilt Libraries

    Your Vanderbilt

    • Alumni
    • Current Students
    • Faculty & Staff
    • International Students
    • Media
    • Parents & Family
    • Prospective Students
    • Researchers
    • Sports Fans
    • Visitors & Neighbors

    Support the Jean and Alexander Heard Libraries

    Support the Library...Give Now

    Gifts to the Libraries support the learning and research needs of the entire Vanderbilt community. Learn more about giving to the Libraries.

    Become a Friend of the Libraries

    Quick Links

    • Hours
    • About
    • Employment
    • Staff Directory
    • Accessibility Services
    • Contact
    • Vanderbilt Home
    • Privacy Policy