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

1 Citation (Scopus)

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

Fingerprint

3D printers
Powder metals
Powder
Manufacturing
Metals
Finite Element
Finite element method
Unit
Processing
Multiple Tests
Process Design
Predictive Model
Complex Geometry
Process Control
Accelerate
Process control
Program processors
Computational Cost
Heat Transfer
Process design

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

Cite this

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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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author = "Mojtaba Mozaffar and Ebot Ndip-Agbor and Stephen Lin and Wagner, {Gregory J} and Kornel Ehmann and Jian Cao",
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Acceleration strategies for explicit finite element analysis of metal powder-based additive manufacturing processes using graphical processing units. / Mozaffar, Mojtaba; Ndip-Agbor, Ebot; Lin, Stephen; Wagner, Gregory J; Ehmann, Kornel; Cao, Jian.

In: Computational Mechanics, Vol. 64, No. 3, 15.09.2019, p. 879-894.

Research output: Contribution to journalArticle

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T1 - Acceleration strategies for explicit finite element analysis of metal powder-based additive manufacturing processes using graphical processing units

AU - Mozaffar, Mojtaba

AU - Ndip-Agbor, Ebot

AU - Lin, Stephen

AU - Wagner, Gregory J

AU - Ehmann, Kornel

AU - Cao, Jian

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AB - 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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