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基于CUDA-GPU架构的超二次曲面离散单元并行算法

王嗣强 季顺迎

王嗣强, 季顺迎. 基于CUDA-GPU架构的超二次曲面离散单元并行算法[J]. 应用数学和力学, 2019, 40(7): 751-767. doi: 10.21656/1000-0887.390267
引用本文: 王嗣强, 季顺迎. 基于CUDA-GPU架构的超二次曲面离散单元并行算法[J]. 应用数学和力学, 2019, 40(7): 751-767. doi: 10.21656/1000-0887.390267
WANG Siqiang, JI Shunying. A Parallel Algorithm for Super-Quadric Discrete Elements Based on the CUDA-GPU Architecture[J]. Applied Mathematics and Mechanics, 2019, 40(7): 751-767. doi: 10.21656/1000-0887.390267
Citation: WANG Siqiang, JI Shunying. A Parallel Algorithm for Super-Quadric Discrete Elements Based on the CUDA-GPU Architecture[J]. Applied Mathematics and Mechanics, 2019, 40(7): 751-767. doi: 10.21656/1000-0887.390267

基于CUDA-GPU架构的超二次曲面离散单元并行算法

doi: 10.21656/1000-0887.390267
基金项目: 国家重点研发计划(2016YCF1401505);国家自然科学基金(11572067;11772085)
详细信息
    作者简介:

    王嗣强(1993—),男,博士生(E-mail: wangsiqiang@mail.dlut.edu.cn);季顺迎(1972—),男,教授,博士生导师(通讯作者. E-mail: jisy@dlut.edu.cn).

  • 中图分类号: O347.7;O373

A Parallel Algorithm for Super-Quadric Discrete Elements Based on the CUDA-GPU Architecture

Funds: The National Key R&D Program of China(2016YCF1401505); The National Natural Science Foundation of China(11572067;11772085)
  • 摘要: 大规模离散元的并行计算通常基于理想的球体单元,然而自然界或工业生产中普遍存在的是由非球形颗粒组成的复杂体系,其在不同空间尺度下的动力学行为及力学性质与球形颗粒具有显著差异.基于连续函数包络的超二次曲面单元能有效地构造非球形颗粒的几何形态,并通过非线性Newton迭代算法准确计算单元间的作用力.针对非球形颗粒间接触判断的复杂性及其大规模离散元计算的需求,该文发展了基于CUDA-GPU构架下超二次曲面单元并行算法.该方法在球形颗粒并行计算的基础上,通过核函数建立单元包围盒的粗判断列表及Newton迭代的细判断列表,并优化并行算法和内存访问模式以提高算法的计算效率.为检验超二次曲面并行算法的可靠性,对非球形颗粒的流动过程进行离散元模拟, 并与试验结果进行对比验证.在此基础上,进一步分析了颗粒单元不同长宽比和表面尖锐度对颗粒材料流动特性的影响,为非球形颗粒材料的大规模离散元模拟提供一种有效的数值方法.
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出版历程
  • 收稿日期:  2018-10-15
  • 修回日期:  2018-10-30
  • 刊出日期:  2019-07-01

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