SBIR/STTR Award attributes
The research objective of the proposed work is to enhance the Phase I development on solidification science-based additive manufacturing (AM) ICME for multi-scale, microstructure modeling, which utilizes thermodynamic and kinetic models and a cellular automata (CA) framework. The dynamics of solidification interface velocity will be modeled using the interface response function theory to predict the inhomogeneities caused by phase selection phenomena. The evolution of the solidification front will be traced within the CA grid to predict the solidification grain growth and orientation and the sub-grain morphology and texture. The thermodynamic and kinetic modeling will be combined with melt-pool scale residual stress predictions to assess the susceptibility to solidification or liquation cracking. The AM solidification profile and melt-pool physics data will be utilized to predict the occurrence or mitigation of defects such as buckling, keyhole, porosity, and lack-of-fusion. The as-built microstructure data will be utilized as input to phenomenological models in order to predict the mechanical anisotropy. Methodical experimentation using scaled part geometries will be utilized to calibrate the ICME models and create material, processing, and microstructure property relationships for 316L and IN625. Hardware prototypes will be delivered for two notional parts identified by the US Navy.
