Randomized trial evaluates melt pool evolution in metallic structures, highlighting its implications for manufacturing optimization.
Directed Energy Deposition (DED) is a metal additive manufacturing process widely used for near-net-shape fabrication, repair of high-value components, and production of large-scale metallic structures. The quality of DED-built parts strongly depends on the thermal history, melt pool geometry, and layer-by-layer heat accumulation during deposition. Therefore, numerical simulation is an effective tool for understanding the process physics and supporting parameter selection before experimental manufacturing. In this study, a three-dimensional multiphysics model was developed to simulate the DED process using COMSOL Multiphysics. The model couples heat transfer, laminar fluid flow, and solid mechanics to evaluate the thermal and physical behavior of deposited metallic layers. A moving Gaussian laser heat source was implemented to represent laser-material interaction, while the governing equations of energy, momentum, and mass conservation were solved to predict temperature distribution and melt pool formation. A symmetric computational domain consisting of a base plate and three deposited powder layers was designed. Steel AISI 4340 was selected as the model material, and its thermophysical properties were incorporated into the simulation. The results show that the proposed model can capture the transient temperature distribution and melt pool evolution during successive layer deposition. The findings indicate that heat accumulation from previously deposited layers significantly affects the thermal field and melt pool characteristics in subsequent layers. The simulation also demonstrates that a coupled multiphysics approach provides deeper insight into the interaction between laser heating, melt pool development, and thermal deformation. The developed model can be used as a practical framework for understanding DED process behavior and supporting future process parameter optimization studies.
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Peyman Ansari (2026) studied this question.
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