Understanding the bi-modal fatigue behavior of the case-hardened M50NiL steel

The gears used in aircraft engines are typically made from high-strength steels reinforced by thermochemical treatments (TCT). These treatments increase surface fatigue strength through microstructural modifications, enhancing hardness and adding compressive residual stresses. In some cases, the combination of material, TCT, and applied stress can lead to a bi-modal fatigue behavior, notably in failures at the gear tooth root. This work investigates the bi-modal fatigue response of M50NiL case-hardened steel by characterizing and analyzing crack initiation mechanisms to propose a relevant fatigue modeling approach. A comprehensive experimental fatigue test campaign was carried out on notched specimens under plane bending and on gear specimens using a Single Tooth Bending Fatigue (STBF) method. The resulting Wöhler diagram shows significant scatter in fatigue life for several stress levels, suggesting a bi-modal behavior with two distinct populations. Fractographic analyses confirmed the competition between two different crack initiation mechanisms depending on stress level and number of cycles to failure. A statistical analysis using a mixture model also indicates that a bi-modal distribution best represents the results. Accordingly, a probabilistic model is proposed to describe the bi-modal fatigue behavior from a global perspective, based on the maximum applied hot-spot surface stress for a fixed stress ratio. Finally, a complementary local stress analysis shows that the combined effect of stress and material property distributions significantly influences local maximum stress variation. Correcting for these factors reduces scatter in the bi-modal stress levels. • Tooth-root bending tests on case-hardened gears and notched specimens. • Bi-modal fatigue behavior arising from competing crack-initiation mechanisms. • Proposed competing-risk model to predict bi-modal lifetimes and regime transitions. • Understanding the hardness and stress gradient influence using a local approach. • Local fatigue analysis reduces the scatter in the bi-modal stress levels.