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Development of Parallelized Idealized Explicit FEM Using GPU
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- IKUSHIMA Kazuki
- Graduate School of Engineering, Osaka Prefecture University
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- ITOH Shinsuke
- Graduate School of Engineering, Osaka Prefecture University
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- SHIBAHARA Masakazu
- Graduate School of Engineering, Osaka Prefecture University
Bibliographic Information
- Other Title
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- GPUを用いた並列化理想化陽解法FEMの開発
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Description
Numerical simulations such as Finite Element Method (FEM) are widely used as tool of structural analyses in both design and production. However, in the application of FEM to welding problems, the simulation scale is usually limited to the welding joint level. Only a few large-scale welding analyses are performed on existing research because welding is transient problem and show strong nonlinearity. In such cases, it is necessary to use static implicit FEM to achieve an accurate analysis, but the larger analysis scale requires larger memory consumption and computing time. Thus, we previously proposed Idealized Explicit FEM (IEFEM) to achieve shorter computing time and lower memory consumption.<br>Since IEFEM is based on dynamic explicit FEM, it is possible to perform the calculation for each degree of freedom (DOF) and element. Such characteristic indicates that IEFEM is suitable for parallelization. Then, in this study, we developed parallelized IEFEM using a graphics processing unit (GPU). The usefulness and validity of the developed method are considered by analyzing a 3-dimensional multi-pass moving heat source problem, which is very difficult to analyze with commercial FEM software because of its analytical scale. As a result, it is found that parallelized IEFEM accelerated by a GPU can analyze a large-scale problem having over 1,000,000 DOFs on a single PC.
Journal
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- QUARTERLY JOURNAL OF THE JAPAN WELDING SOCIETY
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QUARTERLY JOURNAL OF THE JAPAN WELDING SOCIETY 31 (1), 23-32, 2013
JAPAN WELDING SOCIETY
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Keywords
Details 詳細情報について
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- CRID
- 1390001204725339008
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- NII Article ID
- 130004445726
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- COI
- 1:CAS:528:DC%2BC3sXlvVans7s%3D
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- ISSN
- 24348252
- 02884771
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- Text Lang
- ja
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- Article Type
- journal article
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed