2025 AIChE Annual Meeting

(292g) Analytical Modeling of Splash in Metal Additive Manufacturing

Authors

Wei Huang - Presenter, Key Laboratory for Green Chemical Technology of Ministry of Education, School of Chemical Engineering & Technology, Tianjin University
Hamid Garmestani, Georgia Institute of Technology
Steven Y. Liang, Georgia Institute of Technology
Additive Manufacturing (AM), commonly known as 3D printing, has revolutionized the production of complex geometries and customized parts across various industries. Among the numerous AM techniques, powder bed fusion (PBF) processes, such as selective laser melting (SLM) and electron beam melting (EBM), are widely used for their ability to produce high-density, high-strength metal components. However, these processes are not without challenges, one of which is the phenomenon of "splash" or spatter generation during the melting of powder particles. Splash refers to the ejection of molten or partially molten particles from the melt pool, which can lead to defects such as porosity, surface roughness, and inhomogeneous microstructures, ultimately compromising the mechanical properties and dimensional accuracy of the final product.

Understanding and controlling splash is critical for optimizing the AM process and ensuring the quality of printed parts. While experimental observations provide valuable insights into splash behavior, they are often limited by the high-speed dynamics and small scales involved. Analytical modeling offers a complementary approach, enabling researchers to predict and analyze splash phenomena based on fundamental physical principles. This paper presents a comprehensive analytical model to describe the splash mechanism in PBF-based AM processes, focusing on the interplay between laser-powder interactions, melt pool dynamics, and the ejection of particles.

The proposed model is built on a multi-physics framework that integrates heat transfer, fluid dynamics, and particle dynamics. The heat transfer component accounts for the absorption of laser energy by the powder bed, the subsequent melting of particles, and the formation of the melt pool. The fluid dynamics component describes the behavior of the molten metal, including Marangoni convection, capillary forces, and vaporization-induced recoil pressure, which are key drivers of melt pool instability and splash formation. The particle dynamics component captures the ejection, trajectory, and re-deposition of spattered particles, considering factors such as inertia, drag forces, and gravitational effects.

The model is validated against experimental data obtained from high-speed imaging and post-process characterization of AM parts. The results demonstrate that the model accurately predicts the conditions under which splash occurs, including the influence of laser power, scan speed, powder layer thickness, and material properties. For instance, higher laser power and lower scan speeds are found to increase the likelihood of splash due to greater energy input and prolonged melt pool instability. Similarly, materials with lower surface tension and higher thermal conductivity exhibit a higher propensity for splash formation.

The analytical model also provides insights into strategies for mitigating splash. By optimizing process parameters, such as reducing laser power density or increasing scan speed, it is possible to minimize splash and improve the quality of the final product. Additionally, the model highlights the importance of powder characteristics, such as particle size distribution and morphology, in controlling splash behavior.

In conclusion, this study presents a robust analytical framework for understanding and predicting splash in AM processes. The model not only enhances our fundamental understanding of the underlying physics but also offers practical guidelines for process optimization. By reducing defects associated with splash, the proposed approach contributes to the advancement of AM technologies, enabling the production of high-quality, reliable components for critical applications in aerospace, automotive, and biomedical industries. Future work will extend the model to include multi-material systems and explore the role of ambient conditions, such as inert gas flow, in splash dynamics.