A computationally efficient hybrid model for simulating the additive manufacturing process of metals

Additive manufacturing (AM) suffers from residual stress formation and part distortion. One way to improve AM is to use optimal process parameters that yield residual stress distribution that is less detrimental. A finite element analysis (FEA) based model can be used as a design tool to determine optimal process parameters. Being a design tool, such a model should not only predict the residual stress formation and part distortion accurately but should be capable of performing the simulation in a reasonable time as well. However, the traditional FEA models are either accurate but computationally very expensive as in the case of process-based models that captures the evolution of the temperature and stress/strain field or very fast but often inaccurate as in the case of inherent strain based (IST) based models which comprise a series of quasi-static stress-analyses. In this study, we demonstrate that a model that is both accurate and computationally less expensive can be developed by adopting a hybrid approach in which the spatial and temporal resolution of the field solutions over different regions of the part are selectively controlled depending on the expected levels of stress gradients in these regions. The new model, called Additive FEA Hybrid (AFEA-H) model, uses a previously reported Additive FEA (AFEA) framework [1] to combine a process-based model that has a high spatial and temporal resolution with an IST based model that has a low resolution. Numerical simulations performed for a few example problems demonstrate that the AFEA-H method can enhance the computational efficiency substantially without compromising solution accuracy.