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

被引:0
|
作者
Mojtaba Mozaffar
Ebot Ndip-Agbor
Stephen Lin
Gregory J. Wagner
Kornel Ehmann
Jian Cao
机构
[1] Northwestern University,Department of Mechanical Engineering
来源
Computational Mechanics | 2019年 / 64卷
关键词
Additive manufacturing; Directed energy deposition; GPU acceleration; Finite element methods; High performance computing;
D O I
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中图分类号
学科分类号
摘要
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.
引用
收藏
页码:879 / 894
页数:15
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