Reducing uncertainty in fatigue life limits of turbine engine alloys

Abstract In probabilistic design of materials for fracture-critical components in modern military turbine engines, a typical maximum design target risk (DTR) is 5 × 10−8 component failures/engine flight hour. This metric underscores the essential role of safety in a design process that simultaneously strives to achieve performance, efficiency, reliability, and affordability throughout the life cycle of the engine. Traditionally, the design and life management approaches for engine materials have typically relied on extensive testing programs to produce large databases of fatigue data, from which statistically based life limits are derived by extrapolation from the mean fatigue behavior. However, we have found that the statistical behavior of fatigue lifetimes under a given test condition often exhibits a bimodal form, and that the trends in mean vs. minimum fatigue lifetime typically respond differently to loading or to microstructural variables. Under such circumstances, the underlying life-limiting mechanisms appear to exhibit a probabilistic microstructural hierarchy in fatigue resistance that is controlled by susceptibility of local microstructural neighborhoods to early damage and the growth of small cracks. These findings suggest that significant opportunities may exist for reductions in uncertainty in materials life-cycle prediction and management, if such hierarchies can be understood and controlled. This paper explores the potential implications of these findings, and a number of possible approaches are suggested for incorporating the insights of life-limiting fatigue into methods of integrated computational materials engineering (ICME) to support optimized life-cycle design of materials and components in turbine engines. Benefits of this approach appear to include substantial improvements in model accuracy, coupled with reduced requirements for materials testing, potentially leading to a significant reduction in the time and cost to develop, validate, transition, and implement new, more fatigue resistant alloys.