Improved grain structure prediction in metal additive manufacturing using a dynamic kinetic Monte Carlo framework
This work describes a Dynamic Kinetic Monte Carlo numerical modeling framework that can
predict the microstructure of metals during powder bed fusion (PBF) and directed energy
deposition (DED) additive manufacturing (AM) while considering significant variations in
thermal history and heat accumulation that occur during the build. Although the conventional
Kinetic Monte Carlo (KMC) method is well-established, it does not accommodate variation in
the spatial domains of the melt pool (MP) and heat affected zone (HAZ) with time. Thus, the …
predict the microstructure of metals during powder bed fusion (PBF) and directed energy
deposition (DED) additive manufacturing (AM) while considering significant variations in
thermal history and heat accumulation that occur during the build. Although the conventional
Kinetic Monte Carlo (KMC) method is well-established, it does not accommodate variation in
the spatial domains of the melt pool (MP) and heat affected zone (HAZ) with time. Thus, the …
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