Additive manufacturing unlocks near-net-shape production of bulk metallic glass (BMG) components with complex geometries. Nevertheless, their durability under multiaxial cyclic loadings remains largely unexplored and poorly understood. In this work, the multiaxial fatigue behaviour of selective laser melting (SLM) fabricated Zr-based BMG with composition Zr 59 . 3 Cu 28 . 8 Nb 1 . 5 Al 10 . 4 is investigated. In multiaxial fatigue experiments, 17 specimens with approximately 0.46% porosity were subjected to stress-controlled cyclic loadings, including both proportional and non-proportional loading paths. The fracture morphology and multiaxial fatigue mechanisms were systematically analysed using SEM micrographs. To evaluate the fatigue life of 3D-printed BMGs while accounting for manufacturing-induced defects, we conducted defect-based computational simulations using representative volume element (RVE) models incorporating a single pore defect. Parametric studies were carried out to examine the influence of pore location on multiaxial fatigue life performance. Based on the FEM simulation results, a modified non-local Dang Van criterion is proposed for predicting the multiaxial fatigue life. In the critical plane model, a non-proportional correction coefficient is introduced based on the principal stress at the critical location in the vicinity of the defect to enhance the prediction accuracy. The results demonstrate that the proposed model can predict the multiaxial fatigue life of 3D-printed BMG with satisfactory accuracy. • Multiaxial fatigue tests on SLM-fabricated Zr-based BMG were performed under proportional and non-proportional loading conditions. • Fracture morphologies and underlying multiaxial fatigue mechanisms were systematically examined. • Defect-sensitive simulations were carried out using RVE models incorporating a single pore defect. • A modified non-local Dang Van criterion is developed to predict the multiaxial fatigue life of BMGs. • The combined experimental and numerical results show that 94% of the predicted fatigue lives fall within the 2 σ scatter bands.
Ma et al. (Tue,) studied this question.