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

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

*Corresponding author for this work

Research output: Contribution to journalArticle

4 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)879-894
Number of pages16
JournalComputational Mechanics
Volume64
Issue number3
DOIs
StatePublished - Sep 15 2019

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Keywords

  • Additive manufacturing
  • Directed energy deposition
  • Finite element methods
  • GPU acceleration
  • High performance computing

ASJC Scopus subject areas

  • Computational Mechanics
  • Ocean Engineering
  • Mechanical Engineering
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Applied Mathematics

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