Fatigue Behavior and Modeling of Superelastic NiTi Under Variable Amplitude Loading

NiTi (also known as Nitinol) is an almost equiatomic alloy of nickel and titanium and has many applications in various industries, such as biomedical, automotive, and aerospace. NiTi shape memory alloys undergo martensitic phase transformations under both thermal and mechanical loading and exhibit unique properties, such as superelasticity (SE) and shape memory effects (SME). Modeling the fatigue behavior of this alloy is very challenging due to the unique mechanical response of the material. Moreover, there are very limited studies on the fatigue behavior of this alloy under more realistic loading conditions, such as variable amplitude loading and multiaxial loading. In this study, strain-controlled cyclic experiments have been conducted in different conditions to study the variable amplitude fatigue behavior of superelastic NiTi. Nonzero mean strain/stress behavior of superelastic NiTi is investigated, and it is demonstrated that the classical fatigue models for mean strain/stress correction do not appropriately model the nonzero mean strain/stress fatigue behavior of superelastic NiTi. It is shown that, despite common metals (e.g., steel, aluminum, and titanium alloys), mean strain also affects the fatigue behavior of superelastic NiTi, as the resulting mean stress does not fully relax under cyclic load. Two energy-based fatigue models have been proposed based on the results in this study and provide acceptable correlation with experimental observations. The models proposed in this research, account for the effects of mean strain/stress and variations in cyclic deformation. The variations in the cyclic deformation can be due to several factors, such as slight changes in chemical composition, heat treatment processes, texture, etc. The predicted fatigue lives using the proposed fatigue model fall within scatter bands of 1.5 times the experimental life for constant amplitude loading. Analyses also show that the proposed total fatigue toughness parameter, ΣWt, together with the Rainflow cycle counting technique can accurately predict the fatigue life under more realistic loading condition, such as two-step (i.e. high-low and low-high) and variable amplitude load-paths