EXPERIMENTAL STUDY AND NUMERICAL OPTIMIZATION OF SS 316L DED WITH MELT POOL VALIDATION AND THERMAL HISTORY EVALUATION

Directed Energy Deposition (DED) is one of the most important techniques for metal additive manufacturing (MAM). There are still several ongoing challenges linked with this manufacturing technique; mainly the simulation of the DED process when comparing the simulated results with real-world measurements. This paper discusses the simulation of DED utilizing experimental measurements and optimized numerical analysis. Due to its accuracy and diverse usage, the Goldak double ellipsoidal heat source model is applied in this study. However, to ensure reliable output, accurate parameters need to be developed in advance. Several experiments for a wide range of machine parameters are first conducted for Stainless Steel 316L (SS 316L) to gather preliminary data for single-track depositions. Optimized predictive models for the melt pool characteristics are then generated through regression analysis followed by validating them through a new set of experiments. Next, the geometry of the single-track profile is constructed and verified through a curve-fitting process. The newly generated predictive models, single-track profile geometry, and heat source modeling are all interlinked together into a Finite Element Analysis (FEA) framework to solve the transient thermal analysis of DED. The birth-and-death technique is implemented to evaluate the microstructure and thermal history of the deposited material, which is also beneficial in determining melt pool dimensions that cannot be measured experimentally. The accuracy of the FEA is evidenced by the close matching of its output with the experimental results.