M. J. Caton, J. M. Larsen, Air Force Research Laboratory, Wright-Patterson AFB, OH; S. K. Jha, Universal Technology Corporation, Dayton, OH
Recent fatigue studies of numerous aerospace alloys have revealed competing failure modes under relevant loading conditions contributing to dual-fatigue lifetime distributions. It has been observed that inherent fatigue life variability is often composed of a population of life-limited specimens that experience immediate crack initiation and a population of long-life specimens that demonstrate a significant crack initiation period. The life-limited population is well described by the variability in small and long crack growth rates. Alloys demonstrating this phenomenon include Ni-base superalloys, Ti alloys, Al alloys, and gamma-TiAl. Recognizing the competition of these distinctly different mechanisms enables reduced uncertainty in life prediction methods and has significant implications for damage prognosis and life-management practices for fracture critical components. The framework for applying probabilistic life prediction methods for aerospace structures will be presented.
Summary: Recent fatigue studies of numerous aerospace alloys have revealed competing failure modes under relevant loading conditions contributing to dual-fatigue lifetime distributions. It has been observed that inherent fatigue life variability is often composed of a population of life-limited specimens that experience immediate crack initiation and a population of long-life specimens that demonstrate a significant crack initiation period. The life-limited population is well described by the variability in small and long crack growth rates. Alloys demonstrating this phenomenon include Ni-base superalloys, Ti alloys, Al alloys, and gamma-TiAl. Recognizing the competition of these distinctly different mechanisms enables reduced uncertainty in life prediction methods and has significant implications for damage prognosis and life-management practices for fracture critical components. The framework for applying probabilistic life prediction methods for aerospace structures will be presented.
