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 dimensions, 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 into 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, multi-physics 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.
- Develop process windows for new and existing alloys used in laser powder bed fusion and direct energy deposition processes that are extended to multi-layer
- Understand the role of laser power, scan speed, scan pattern and powder sizes on melt pool dynamics and related defects; and re-coater design and speed on powder packing and spreading
- Predict and influence microstructure based on thermal gradients and cooling rates in melt pool
Why Is It Important?
The status quo in additive manufacturing simulation software, especially for laser powder bed fusion processes (L-PBF), is focused on thermo-mechanical simulations that help with part-scale modelling such as thermal distortions, residual stresses and generation of support structures. While useful, information about melt pool dynamics and related defects such as balling and porosity is usually outside the realm of such approaches. It is also important to keep in mind that fluid flow, heat transfer and surface tension within the melt pool affect the thermal gradients and cooling rates, which in turn influence the microstructure evolution.
Using CFD and discrete element method modelling, it is possible to simulate at the powder and melt pool scales. The relevant physics that are implemented include viscous flows, heat transfer, solidification, phase change, recoil pressure, shield gas pressure, surface tension, moving objects, powder compaction, particle-particle and particle-object interactions. Such an approach enables successful development of process windows for alloys and helps provide insights into microstructure evolution, which is of interest to both AM machine manufacturers and end users of AM technology.
Successful case studies on development of process parameters, onset of balling defects, and microstructure evolution for varying scan patterns are discussed in detail.