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

doi:10.1007/s00466-019-01685-4

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 journal › Article › peer-review

9 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 language	English (US)
Pages (from-to)	879-894
Number of pages	16
Journal	Computational Mechanics
Volume	64
Issue number	3
DOIs	https://doi.org/10.1007/s00466-019-01685-4
State	Published - Sep 15 2019

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

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.",

keywords = "Additive manufacturing, Directed energy deposition, Finite element methods, GPU acceleration, High performance computing",

author = "Mojtaba Mozaffar and Ebot Ndip-Agbor and Stephen Lin and Wagner, {Gregory J.} and Kornel Ehmann and Jian Cao",

note = "Funding Information: 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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doi = "10.1007/s00466-019-01685-4",

language = "English (US)",

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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 journal › Article › peer-review

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AU - Ndip-Agbor, Ebot

AU - Lin, Stephen

AU - Wagner, Gregory J.

AU - Ehmann, Kornel

AU - Cao, Jian

N1 - Funding Information: 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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Acceleration strategies for explicit finite element analysis of metal powder-based additive manufacturing processes using graphical processing units

Abstract

Keywords

ASJC Scopus subject areas

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