We are pleased to announce that we have been invited to speak at the 3rd International Symposium Additive Manufacturing on January 29–31, 2019 in Dresden, Germany. Flow Science’s President & CEO Amir Isfahani, PhD, will be presenting, CFD modelling advances in Additive Manufacturing on January 31 at 12:10 pm during the Pre- and post-processing session of the conference.
Paree Allu, MS and Amir Isfahani, PhD
Laser processing technology has contributed to a rise of interest in metal additive manufacturing (AM) processes such as laser powder bed fusion and direct metal deposition. Although AM has been generating significant interest, challenges remain towards a more widespread adoption of this technology. These challenges include defects such as porosity and spatially non-uniform micro-structures that occur because of insufficient knowledge in process control. Computational fluid dynamics (CFD) modelling can help understand the effects of process parameters on the underlying physical phenomena such as laser-powder interaction, melt pool dynamics, phase change and solidification. With experimental studies successfully capturing melt pool temperatures and weld bead shapes, it is possible to calibrate numerical models to the experimental data. These numerical models, which are based on a rigorous solution of the conservation equations, can provide further insights on fluid convection in the melt pool, temperature gradients and solidification rates. In this presentation, case studies from industry and academia highlighting the successful use of CFD and numerical models in understanding powder bed fusion and direct energy deposition processes are discussed in detail. Furthermore, it is shown how process parameter optimization is used to control porosity formation, balling defects and microstructure evolution for several alloys. These high-fidelity, multiphysics CFD models provide a framework to better understand AM processes from the particle and melt pool scales. Using this information, it will be possible to accurately model additional aspects of AM processes such as thermal and residual stresses and distortions at the part scale.