Abstract
In this paper, a parallelized 3D cellular automaton computational model is developed to predict grain morphology for solidification of metal during the additive manufacturing process. Solidification phenomena are characterized by highly localized events, such as the nucleation and growth of multiple grains. As a result, parallelization requires careful treatment of load balancing between processors as well as interprocess communication in order to maintain a high parallel efficiency. We give a detailed summary of the formulation of the model, as well as a description of the communication strategies implemented to ensure parallel efficiency. Scaling tests on a representative problem with about half a billion cells demonstrate parallel efficiency of more than 80% on 8 processors and around 50% on 64; loss of efficiency is attributable to load imbalance due to near-surface grain nucleation in this test problem. The model is further demonstrated through an additive manufacturing simulation with resulting grain structures showing reasonable agreement with those observed in experiments.
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Acknowledgements
Gregory J. Wagner and Wing Kam Liu acknowledge the support by the National Science Foundation (NSF) Cyber-Physical Systems (CPS) under Grant No. 359 CPS/CMMI-1646592. Yanping Lian, Wentao Yan, and Wing Kam Liu acknowledge the support by Center for Hierarchical Materials Design (CHiMaD) under Grant No. 70NANB14H012. Stephen Lin acknowledges the support by the NSF Graduate Research Fellowship under Grant No. DGE-1324585.
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Lian, Y., Lin, S., Yan, W. et al. A parallelized three-dimensional cellular automaton model for grain growth during additive manufacturing. Comput Mech 61, 543–558 (2018). https://doi.org/10.1007/s00466-017-1535-8
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DOI: https://doi.org/10.1007/s00466-017-1535-8