A scalable predictive model and validation for residual stress and distortion in selective laser melting

The unique thermal cycle of rapid melting, solidification, and melt-back in selective laser melting (SLM) induces steep residual stress gradients which lead to part distortion. However, it is extremely difficult to predict residual stress in SLM due to complex multi-physics phenomena and scale-up of millions of laser scans. This paper has developed a geometry scalable predictive model across microscale laser scan, mesoscale layer hatch, and macroscale part build-up to fast predict residual stress in different scanning strategies. The predictions were validated using the L-shaped bar and bridge structures. The geometry scalability law provides an effective tool for optimizing part designs.