Multi-physics process modeling

We develop multi-physics models for beam-induced metal processing, accelerating such models with machine learning/neural network substitutes designed for specific applications. We use statistical analysis of extensive simulation data to uncover the missing parameters and material properties from in-house benchmark experiments. 

Our current processes of interest include: