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GPU/CPU parallel computation of material damage

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Abstract

In this paper compute unified device architecture programming and open multiprocessing are used for the graphics processing unit and central processing unit parallel computation of material damage. The material damage is evaluated by a multilevel finite element analysis within material domains reconstructed from a high-resolution micro-focus X-ray computed tomography system. An effective computational method is investigated for solving the linear equations of finite element analysis. Numerical results show an encouraging trend in reducing the computation cost for the digital diagnosis of material damage.

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Acknowledgments

This work was in part supported by National Science Foundation CMMI-0721625, ECCS-1039563, IIP-1445355, and the University of Michigan-Dearborn Undergraduate Fellowship.

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Authors and Affiliations

  1. University of Michigan, Dearborn, MI, USA

    Jie Shen, Diego Vela, Ankita Singh, Kexing Song, Guoshang Zhang & Bradon LaFreniere

  2. Shanghai University of Engineering Science, Shanghai, P.R. China

    Jie Shen & Hao Chen

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  1. Jie Shen
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  2. Diego Vela
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  3. Ankita Singh
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  4. Kexing Song
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  5. Guoshang Zhang
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  7. Hao Chen
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Correspondence to Jie Shen.

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Shen, J., Vela, D., Singh, A. et al. GPU/CPU parallel computation of material damage. Engineering with Computers 31, 647–660 (2015). https://doi.org/10.1007/s00366-014-0367-9

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  • DOI: https://doi.org/10.1007/s00366-014-0367-9

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