EUROPEAN CONGRESS AND EXHIBITION ON ADVANCED MATERIALS AND PROCESSES - EUROMAT 2021

Modeling powder-based additive manufacturing technologies, specifically selective laser melting, is a great challenge due to the complex, interrelated phenomena that occur during the process, on multiscale space-time. This phenomena range from laser interaction with the powder particles and the melt, to melt pool formation, solidification, and microstructure evolution. Fully predictive simulations of AM processes will require linking melt pool models to other models, including those predicting the powder deposition and microstructure formation[1]. Such models would provide a thermodynamically coherent description of the process and thus a well-informed microstructure prediction.

This study presents a parallel CFD-DEM approach to multiphysics modeling of selective laser melting process. The Extended Discrete Element Method(XDEM)[2], an advanced numerical tool based on the discrete-continuous concept, is investigated to distinctly resolve the particles in the powder bed, featuring the powder deposition, powder distribution, and heat, mass, and momentum exchange with the melt pool. Moreover, XDEM considers conduction and radiation heat transfer between the particles and resolves laser radiation and phase change of each particle distinctively. In the CFD model, a Volume of Fluid (VOF) method is used to track the melt pool's shape evolution due to surface tension and Marangoni forces. The laser is considered an interfacial volumetric heat source based on Continuum Surface Force(CSF). The CFD-DEM coupling presents a temperature distribution throughout the solidified track, and this information will bed fed into a Kinetic Monte Carlo model of microstructure evolution.

References:

[1] Cook, P.S. and Murphy, A.B., 2020. Simulation of melt pool behaviour during additive manufacturing: Underlying physics and progress. Additive Manufacturing, 31, p.100909.

[2]Donoso, A.A.E. and Peters, B., 2018. Exploring a multiphysics resolution approach for additive manufacturing. JOM, 70(8), pp.1604-1610.