Impact of Boundary Parameters Accuracy on Modeling of Directed Energy Deposition Thermal Field

Within the large Additive Manufacturing (AM) process family, Directed Energy Deposition (DED) can be used to create low-cost prototypes and coatings, or to repair cracks. In the case of M4 HSS (High Speed Steel), a reliable computed temperature field during DED process allows the optimization of the substrate preheating temperature value and other process parameters. Such optimization is required to avoid failure during the process, as well as high residual stresses. If 3D DED simulations provide accurate thermal fields, they also induce huge computation time, which motivates simplifications. This article uses a 2D Finite Element (FE) model that decreases the computation cost through dividing the CPU time by around 100 in our studied case, but it needs some calibrations. As described, the identification of a correct data set solely based on local temperature measurements can lead to various sets of parameters with variations of up to 100%. In this study, the melt pool depth was used as an additional experimental measurement to identify the input data set, and a sensitivity analysis was conducted to estimate the impact of each identified parameter on the cooling rate and the melt pool dimension.