Effects of martensitic phase transformation on fatigue indicator parameters determined by a crystal plasticity model

Fatigue indicator parameters are a powerful tool for materials design. These parameters represent the potency of various microstructures to incubate fatigue cracks in metal alloys and are useful in ranking deleterious microstructural features on which to focus process improvements. These fatigue indicator parameters are generally a function of irreversible plastic strain; however, for alloys with solid-state phase transformations (such as Nitinol), reversible transformation strains occur along with plastic strain. This article addresses the question of whether modeling a reversible transformation will affect the predicted value of a fatigue indicator parameter. For Nitinol, the effects of a reversible phase transformation on the fatigue indicator parameter and fatigue life are studied for a polygranular microstructure with and without an inclusion. The crystal mechanics of both plasticity and phase transformations are modeled using the finite element method. It is shown that the usage of a crystal-mechanics-based phase transformation model affects the values of fatigue indicator parameters, the shape of predicted strain-life curves, the distribution of fatigue indicator parameter values in the microstructure, and also the rank ordering of deleterious microstructural features.

Automated summary

Fatigue indicator parameters play a crucial role in materials design by evaluating the potential of various microstructures to initiate fatigue cracks in metal alloys. This study explores the impact of reversible phase transformation on the predicted values of fatigue indicator parameters for Nitinol, a alloy with solid-state phase transformations. The crystal mechanics of both plasticity and phase transformations are modeled using the finite element method. The findings show that a crystal-mechanics-based phase transformation model influences the values of fatigue indicator parameters, the shape of strain-life curves, the distribution of fatigue indicator parameter values, and the ranking of deleterious microstructural features.