Three-Dimensional (3-D) Crack Growth Life Prediction for Probabilistic Risk Analysis of Turbine Engine Metallic Components
Department of Defense
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Fracture Analysis Consultants, Inc.
121 Eastern Heights Drive, Ithaca, NY, -
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AbstractABSTRACT: The Air Force has been placing increased emphasis on probabilistic methods for predictions of design reliability of fracture critical engine components, including metallic turbine engine blades and disks. Current state-of-the-practice for these methods typically include a significant amount of conservatism in crack initiation and fatigue crack growth and inspection design criteria due to uncertainties in material properties, fatigue performance, crack growth analysis, stress analysis, residual stresses, damage mechanisms, and nondestructive inspection, among others. We propose to develop and demonstrate a new probabilistic life prediction methodology that will significantly reduce uncertainty and conservatism by employing an accurate mechanics based crack growth analysis. We will combine an existing high fidelity 3D crack growth simulator (FRANC3D) with an existing probabilistic life prediction code (DARWIN). Both codes are recognized as being the most mature and the most capable codes in their areas of specialization (high fidelity crack modeling and probabilistic life prediction , respectively). The new methodology is expected to reduce conservatism in probabilistic life predictions, thus extending component lives or inspection intervals. The proposed effort includes the involvement of a major engine OEM. BENEFIT: Current probabilistic methodologies for setting fatigue lives and inspection intervals for metallic engine components include a significant amount of conservatism due to uncertainties in the, among other things, crack growth analysis. The proposed effort will combine a high fidelity crack growth simulator (FRANC3D) with a probabilistic fatigue life calculator (DARWIN). The resulting tool and methodology is expected to reduce conservatism in probabilistic life predictions, thus increasing the predicted mean time to failure. For a constant relative probability of failure this will extend the allowable component life and inspection intervals. Extending component fatigue lives and inspection intervals will yield significant costs saving over the lifetime of the engine. The resulting methodology can be used in non-engine applications such as airframes, land and sea based turbines, and terrestrial vehicles.
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