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A New Equilibrium Distribution Function of the Lattice Boltzmann Method

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High Performance Computing and Applications (HPCA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9576))

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Abstract

According to the conventional Maxwell distribution function, a new equilibrium distribution function based on a discrete velocity model (D2Q13) is proposed. A parallel lattice Boltzmann algorithm based on this new function is used for simulating the lid-driven cavity flow. The experimental results validate the correctness of the new equilibrium distribution function.

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Acknowledgments

This work was supported by National Nature Science Foundation of China (No. 91330116).

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Authors and Affiliations

  1. School of Computer Engineering and Science, Shanghai University, Shanghai, 200444, China

    Wei Xu, Wenhao Zhu & Wu Zhang

  2. School of Communication and Information Engineering, Shanghai University, Shanghai, 200444, China

    Zhixiang Liu

  3. High Performance Computing Center, Shanghai University, Shanghai, 200444, China

    Zhixiang Liu & Wu Zhang

Authors
  1. Wei Xu
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  2. Zhixiang Liu
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  3. Wenhao Zhu
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  4. Wu Zhang
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Corresponding author

Correspondence to Wu Zhang .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Shanghai University, Shanghai, China

    Jiang Xie

  2. Chemical and Petroleum Engineering, University of Calgary, Calgary, Alberta, Canada

    Zhangxin Chen

  3. Mathematics Department, University of Wyoming, Laramie, Wyoming, USA

    Craig C. Douglas

  4. School of Computer Engineering, Shanghai University, Shanghai, China

    Wu Zhang

  5. Mathematics and Informatics, South China Agricultural University, Guangzhou, China

    Yan Chen

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© 2016 Springer International Publishing Switzerland

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Xu, W., Liu, Z., Zhu, W., Zhang, W. (2016). A New Equilibrium Distribution Function of the Lattice Boltzmann Method. In: Xie, J., Chen, Z., Douglas, C., Zhang, W., Chen, Y. (eds) High Performance Computing and Applications. HPCA 2015. Lecture Notes in Computer Science(), vol 9576. Springer, Cham. https://doi.org/10.1007/978-3-319-32557-6_22

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  • DOI: https://doi.org/10.1007/978-3-319-32557-6_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32556-9

  • Online ISBN: 978-3-319-32557-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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