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Acceleration strategies for explicit finite element analysis of metal powder-based additive manufacturing processes using graphical processing units

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Abstract

Metal powder-based Additive Manufacturing (AM) processes are increasingly used in industry and science due to their unique capability of building complex geometries. However, the immense computational cost associated with AM predictive models hinders the further industrial adoption of these technologies for time-sensitive applications, process design with uncertainties or real-time process control. In this work, a novel approach to accelerate the explicit finite element analysis of the transient heat transfer of AM processes is proposed using Graphical Processing Units. The challenges associated with this approach are enumerated and multiple strategies to overcome each challenge are discussed. The performance of the proposed algorithms is evaluated on multiple test cases. Speed-ups of about 100 ×–150 × compared to an optimized single CPU core implementation for the best strategy were achieved.

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Acknowledgements

The authors acknowledge the support by the National Institute of Standards and Technology (NIST)—Center for Hierarchical Materials Design (CHiMaD) under Grant No. 70NANB14H012, and the National Science Foundation (NSF)—Cyber-Physical Systems (CPS) under Grant No. CPS/CMMI-1646592. Stephen Lin is supported by the National Science Foundation Graduate Research Fellowship under Grant No. DGE-1324585.

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Author notes

  1. Mojtaba Mozaffar and Ebot Ndip-Agbor have contributed equally to this work.

Authors and Affiliations

  1. Department of Mechanical Engineering, Northwestern University, Evanston, IL, 60208, USA

    Mojtaba Mozaffar, Ebot Ndip-Agbor, Stephen Lin, Gregory J. Wagner, Kornel Ehmann & Jian Cao

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  1. Mojtaba Mozaffar
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  2. Ebot Ndip-Agbor
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Correspondence to Jian Cao.

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Mozaffar, M., Ndip-Agbor, E., Lin, S. et al. Acceleration strategies for explicit finite element analysis of metal powder-based additive manufacturing processes using graphical processing units. Comput Mech 64, 879–894 (2019). https://doi.org/10.1007/s00466-019-01685-4

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