Abstract
AbstractPowder bed fusion additive manufacturing (PBFAM) of metals has the potential to enable new paradigms of product design, manufacturing and supply chains while accelerating the realization of new technologies in the medical, aerospace, and other industries. Currently, wider adoption of PBFAM is held back by difficulty in part qualification, high production costs and low production rates, as extensive process tuning, post‐processing, and inspection are required before a final part can be produced and deployed. Physics‐based modeling and predictive simulation of PBFAM offers the potential to advance fundamental understanding of physical mechanisms that initiate process instabilities and cause defects. In turn, these insights can help link process and feedstock parameters with resulting part and material properties, thereby predicting optimal processing conditions and inspiring the development of improved processing hardware, strategies and materials. This work presents recent developments of our research team in the modeling of metal PBFAM processes spanning length scales, namely mesoscale powder modeling, mesoscale melt pool modeling, macroscale thermo‐solid‐mechanical modeling and microstructure modeling. Ongoing work in experimental validation of these models is also summarized. In conclusion, we discuss the interplay of these individual submodels within an integrated overall modeling approach, along with future research directions.
Highlights
Widespread adoption of metal powder bed fusion additive manufacturing (PBFAM) processes such as selective laser melting (SLM) or electron beam melting (EBM) is mainly held back by reliable part qualification, high production costs and low production rate
Our ongoing research work focuses on the development of such an alternative, high-fidelity melt pool model, which differs from the smoothed particle hydrodynamics (SPH) model described above by the following main aspects: (i) evaporation, i.e., the phase transition from liquid to vapor/gas phase is explicitly resolved, and the associated pressure jump and heat transfer across the liquid-gas interface follow consistently from the balances of mass, momentum and energy instead of employing the phenomenological models (4) and (5); (ii) an Eulerian discretization scheme is applied, which requires a tracking scheme for the position of the liquid-gas interface; (iii) a truly incompressible instead of weakly incompressible flow is considered in the liquid and gas phase
Beyond the insights gained from these individual models, their interplay in an integral modeling approach will be a central aspect of future research
Summary
Powder bed fusion additive manufacturing (PBFAM) of metals has the potential to enable new paradigms of product design, manufacturing and supply chains while accelerating the realization of new technologies in the medical, aerospace, and other industries. Physics-based modeling and predictive simulation of PBFAM offers the potential to advance fundamental understanding of physical mechanisms that initiate process instabilities and cause defects. These insights can help link process and feedstock parameters with resulting part and material properties, thereby predicting optimal processing conditions and inspiring the development of improved processing hardware, strategies and materials. This work presents recent developments of our research team in the modeling of metal PBFAM processes spanning length scales, namely mesoscale powder modeling, mesoscale melt pool modeling, macroscale thermo-solid-mechanical modeling and microstructure modeling.
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