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Meeting 2026 TMS Annual Meeting & Exhibition
Symposium Additive Manufacturing Modeling, Simulation and Artificial Intelligence
Presentation Title Integrated Melt Pool Dynamics and Defect Prediction in Additive Manufacturing of Inconel 625
Author(s) Mohammad Younes Araghi, Shuozhi Xu
On-Site Speaker (Planned) Mohammad Younes Araghi
Abstract Scope Laser Powder Bed Fusion (LPBF) and Directed Energy Deposition (DED) are at the forefront of additive manufacturing (AM) for high-performance alloys like Inconel 625. In this work, we simulate melt pool dynamics, thermal gradients, and solidification behavior during multi-layer LPBF and DED processes. Our approach focuses on understanding the interplay between process parameters—such as laser power, scan speed, and hatch spacing—and their impact on defect formation, including keyhole porosity, lack-of-fusion, and surface roughness. By systematically varying simulation conditions and analyzing melt pool profiles, we identify parameter windows that minimize defect risk and optimize layer quality. Additionally, the model is extended to compare powder- and wire-fed DED strategies, providing insights into deposition efficiency and microstructural control. This study establishes a digital workflow for predicting and mitigating defects in AMed Inconel 625 components, thereby supporting the design of more reliable, high-performance AM parts.
Proceedings Inclusion? Planned:
Keywords Additive Manufacturing, Computational Materials Science & Engineering, Modeling and Simulation

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