A Bayesian defect-based physics-guided neural network model for probabilistic fatigue endurance limit evaluation

Accurate fatigue assessment of material plagued by defects is of utmost importance to guarantee safety and service continuity in engineering components. This study shows how state-of-the-art semi-empirical models can be endowed with additional defect descriptors to probabilistically predict the occurrence of fatigue failures by exploiting...

Sub-size specimen testing for near-threshold fatigue crack behaviour of additively manufactured Ti-6Al-4V

Sub-size specimen testing offers a potentially elegant solution to accompany fatigue life assessments in determining vital fatigue parameters such as effective fatigue crack growth propagation thresholds (ΔK_th,eff). Additively manufactured parts stand to benefit from this in potential build-by-build fatigue validation without...