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Fatigue crack growth is a stochastic process and different kinds of uncertainty physical variability, data uncertainty and modeling errors should be included within the analysis to more accurately represent the fatigue life of the component. This dissertation systematically identifies, quantifies, and incorporates different types of uncertainties within an overall probabilistic life prediction modeling approach. The uncertainty quantification (UQ) methodology is implemented with 3-dimensional planar and non-planar fatigue crack modeling, for structural components subjected to multi-axial, variable amplitude loading conditions. Included within the scope of this work are UQ methods for material properties and model parameters, as well as methods which focus on model error quantification including FEA discretization error and surrogate modeling error. Additionally, the uncertainty quantification and propagation methodology is developed to be computationally efficient to enable the component reliability assessment to be performed within a Monte Carlo Scheme. The proposed methodology is illustrated for application to a rotorcraft mast component. |
