Meso-mechanics-based microstructural modelling approach to predict low cycle fatigue properties in additively manufactured alloys

Grain, grain boundaries, voids, alloying elements and other anomalies have an important impact on the stress distribution at the sub-grain meso level which consequently affect the strain controlled low cycle fatigue (LCF) in additively manufactured (AM) alloys. In alloys AM materials yielding with large stress-strain gradients tends to form around voids and other defects, thus inducing preferential crack nucleation sites and accelerating fatigue failure of the substrate. In order to investigate the effects of these microscopic features on the LCF performance in AM alloys, this paper proposes an idealized grain/grain boundary model using Voronoi tessellation technique and to quantify the effects of different features such as randomly distributed internal pores and hard interstitial on the LCF performance. The proposed method is an important meso-scale continuum damage modelling approach that can be developed to study and analyze the LCF properties with the consideration of microscopic features.

Automated summary

Grain, grain boundaries, voids, alloying elements and other anomalies have a significant impact on the stress distribution at the sub-grain meso level in additively manufactured alloys, affecting the strain controlled low cycle fatigue. This paper proposes an idealized grain/grain boundary model using Voronoi tessellation technique to quantify the effects of different features on the LCF performance.