Bayesian Inverse Uncertainty Quantification of a MOOSE-based Melt Pool Model for Additive Manufacturing using Experimental Data
Additive Manufacturing (AM) technology is being increasingly adopted in a wide variety of application areas because of its ability to rapidly produce, prototype, and customize designs. AM techniques has significant opportunities in nuclear materials with accelerated fabrication process and reduced cost. High-fidelity modeling and simulation of AM processes is being developed at the Idaho National […]