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Volume 17 Issue 1
Feb.  2010
数据统计

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Ming-ji Huang, Xiu-ping Dong,  and Guo-quan Liu, 3D Modeling of the preparation process of metal rubber material, Int. J. Miner. Metall. Mater., 17(2010), No. 1, pp. 75-79. https://doi.org/10.1007/s12613-010-0113-2
Cite this article as:
Ming-ji Huang, Xiu-ping Dong,  and Guo-quan Liu, 3D Modeling of the preparation process of metal rubber material, Int. J. Miner. Metall. Mater., 17(2010), No. 1, pp. 75-79. https://doi.org/10.1007/s12613-010-0113-2
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3D Modeling of the preparation process of metal rubber material

  • 通讯作者:

    Ming-ji Huang    E-mail: huangmingji@263.net

  • Based on the analysis of the preparation of metal rubber (MR) and two pivotal hypotheses, the uniform distribution and the unaltered topological structure of wires in the radial direction of columns in the punch process, a 3D parametrical model was established based on four approaches: helix-making, planar roughcast-weaving, planar roughcast-rolling, and 3D roughcast punching. In the modeling process, 5 lattice types of weave patterns in planar roughcast were put forward, and 10 quantificational modeling parameters were picked up to exclusively define the column MR component structure. The wire distribution was visualized by CAD techniques. The important performance parameter of column MR components (relative density ρ) can be forecasted by modeling computing, which provides the necessary foundation for the design and optimization of MR materials.
  • 3D Modeling of the preparation process of metal rubber material

    + Author Affiliations
    • Based on the analysis of the preparation of metal rubber (MR) and two pivotal hypotheses, the uniform distribution and the unaltered topological structure of wires in the radial direction of columns in the punch process, a 3D parametrical model was established based on four approaches: helix-making, planar roughcast-weaving, planar roughcast-rolling, and 3D roughcast punching. In the modeling process, 5 lattice types of weave patterns in planar roughcast were put forward, and 10 quantificational modeling parameters were picked up to exclusively define the column MR component structure. The wire distribution was visualized by CAD techniques. The important performance parameter of column MR components (relative density ρ) can be forecasted by modeling computing, which provides the necessary foundation for the design and optimization of MR materials.
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