3D Modeling of the Solidification Structure Evolution and of the Inter Layer/Track Voids Formation in Metallic Alloys Processed by Powder Bed Fusion Additive Manufacturing

Abstract

A fully transient discrete-source 3D Additive Manufacturing (AM) process model was coupled with a 3D stochastic solidification structure model to simulate the grain structure evolution quickly and efficiently in metallic alloys processed through Electron Beam Powder Bed Fusion (EBPBF) and Laser Powder Bed Fusion (LPBF) processes. The stochastic model was adapted to rapid solidification conditions of multicomponent alloys processed via multi-layer multi-track AM processes. The capabilities of the coupled model include studying the effects of process parameters (power input, speed, beam shape) and part geometry on solidification conditions and their impact on the resulting solidification structure and on the formation of inter layer/track voids. The multi-scale model assumes that the complex combination of the crystallographic requirements, isomorphism, epitaxy, changing direction of the melt pool motion and thermal gradient direction will produce the observed texture and grain morphology. Thus, grain size, morphology, and crystallographic orientation can be assessed, and the model can assist in achieving better control of the solidification microstructures and to establish trends in the solidification behavior in AM components. The coupled model was previously validated against single-layer laser remelting IN625 experiments performed and analyzed at National Institute of Standards and Technology (NIST) using LPBF systems. In this study, the model was applied to predict the solidification structure and inter layer/track voids formation in IN718 alloys processed by LPBF processes. This 3D modeling approach can also be used to predict the solidification structure of Ti-based alloys processes by EBPBF.

A 3D Multiscale Model for Prediction of the Microstructure Evolution in Ti6Al4V Components Produced by Laser Powder Bed Fusion

“…Recent advancements and difficulties related to controlling the Ti6Al4V microstructures of parts produced using various Additive Manufacturing (AM) techniques were examined in [1]. The present simulation tool was developed by linking a transient macro-model with a microstructure model [2][3][4][5][6][7]. By connecting a transient macro-model with a microstructure model [2][3][4][5][6][7], the current simulation tool was created.…”

“…The present simulation tool was developed by linking a transient macro-model with a microstructure model [2][3][4][5][6][7]. By connecting a transient macro-model with a microstructure model [2][3][4][5][6][7], the current simulation tool was created. The macro-model calculates the temperature distribution within the melt pool, which varies with time.…”

“…The National Institute of Standards and Technology (NIST) conducted laser remelting benchmark experiments on IN625 alloy using LBPF equipment [11]. These experiments were utilized to verify the IOP Publishing doi:10.1088/1757-899X/1281/1/012002 2 simulation tool's accuracy, as demonstrated in [6], and subsequently employed to anticipate the effect of crucial process parameters on the microstructure morphology on IN718 alloy [7]. The simulation tool is capable of assessing the impact of the deposition of multiple layers and tracks within a layer, as well as the subsequent layers, on the formation of the microstructure of the entire component.…”