A coupled heat source model that combined a Gauss surface with cylindrical volumetric was introduced to simulate temperature field distribution and melt pool characteristics using finite element simulation (FEM) method for the deep narrow pools formed in laser powder bed fusion (L-PBF) aiming at commercial pure titanium (CP-Ti). For comparison, same simulations double ellipsoid were also perfor...

The recent explosion of machine learning (ML) and artificial intelligence (AI) shows great potential in the breakthrough metal additive manufacturing (AM) process modeling, which is an indispensable step to derive process-structure-property relationship. However, success conventional tools data science primarily attributed unprecedented large amount labeled data-sets (big data), can be either o...

This paper presents an investigation of the rapid variations in temperature metal melt pool for Additive Manufacturing (AM) processes. The is created by scanning a high-power laser beam across powder bed. Rapid heating and cooling processes are involved layer-by-layer fabrication part. Recent advances Machine Learning Deep algorithms provide efficient ways to analyze large sets data search corr...