Mesoscopic Simulation of Core-Shell Composite Powder Materials by Selective Laser Melting.

Materials (Basel)

Institute of Manufacturing Engineering, Huaqiao University, Xiamen 361021, China.

Published: November 2023

Mechanical ball milling is used to produce multi-materials for selective laser melting (SLM). However, since different powders have different particle size distributions and densities there is particle segregation in the powder bed, which affects the mechanical properties of the printed part. Core-shell composite powder materials are created and used in the SLM process to solve this issue. Core-shell composite powder materials selective laser melting (CS-SLM) has advanced recently, expanding the range of additive manufacturing applications. Heat storage effects and heat transfer hysteresis in the SLM process are made by the different thermophysical characteristics of the core and the shell material. Meanwhile, the presence of melt flow and migration of unmelted particles in the interaction between unmelted particles and melt complicates the CS-SLM molding process. It is still challenging to investigate the physical mechanisms of CS-SLM through direct experimental observation of the process. In this study, a mesoscopic melt-pool dynamics model for simulating the single-track CS-SLM process is developed. The melting characteristics of nickel-coated tungsten carbide composite powder (WC@Ni) were investigated. It is shown that the powder with a smaller particle size is more likely to form a melt pool, which increases the temperature in the area around it. The impact of process parameters on the size of the melt pool and the distribution of the reinforced particles in the melt pool was investigated. The size of the melt pool is significantly affected more by changes in laser power than by changes in scanning speed. The appropriate control of the laser power or scanning speed can prevent enhanced particle aggregation. This model is capable of simulating CS-SLM with any number of layers and enables a better understanding of the CS-SLM process.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10650416PMC
http://dx.doi.org/10.3390/ma16217005DOI Listing

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