Simulation of metal additive manufacturing microstructures using kinetic Monte Carlo

By T. Rodgers, Jonathan Madison, V. Tikare. 2017

313 citations recorded by the source corpus.

Abstract Additive manufacturing (AM) is of tremendous interest given its ability to realize complex, non-traditional geometries in engineered structural materials. However, microstructures generated from AM processes can be equally, if not more, complex than their conventionally processed counterparts. While some microstructural features observed in AM may also occur in more traditional solidification processes, the introduction of spatially and temporally mobile heat sources can result in significant microstructural heterogeneity. While grain size and shape in metal AM structures are understood to be highly dependent on both local and global temperature profiles, the exact form of this relation is not well understood. Here, an idealized molten zone and temperature-dependent grain boundary mobility are implemented in a kinetic Monte Carlo model to predict three-dimensional grain structure in additively manufactured metals. To demonstrate the flexibility of the model, synthetic microstructures are generated under conditions mimicking relatively diverse experimental results present in the literature. Simulated microstructures are then qualitatively and quantitatively compared to their experimental complements and are shown to be in good agreement.

Subfields: Automotive Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/d442f376ebb1ae6e9926e741ab1935f156f8497e

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Citations in the corpus

Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches (2020, methodology): “Mesoscale models are used to predict the grain structure in MAM based on either the cellular automata (CA) [21–23] or the Monte Carlo method [24, 25].”
Microstructure modelling for metallic additive manufacturing: a review (2020, methodology): “New alloys that have been processed by AM includes, but not limited to, Al–Cu alloys (Wang et al. 2018; Martinez, Todd, and Mumtaz 2019), Al–Cu–Mg (Nie et al. 2018), Al–Cu–Mg–Si (Wang et al. 2018), Al–Zn–Si–Mg– Cu (Casati et al. 2019), Cu–Sn alloys (Mao et al. 2018; Tan et al. 2019), Cu-10Zn (Zhang ”
Prediction of microstructure, residual stress, and deformation in laser powder bed fusion process (2018, background): “[6] took the general Monte Carlo approach to predict three-dimensional grain structure in additively manufactured metals.”
Three-dimensional grain growth during multi-layer printing of a nickel-based alloy Inconel 718 (2019, methodology): “Some models neglect spatial variations in temperature gradients and solidification front velocities while coupling the grain growth model with heat transfer calculations [19,24].”