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    张阳, 聂玉峰, 武亚涛. 基于数字图像处理和有限元预测纳米颗粒增强聚合物基复合材料的弹性模量[J]. 机械工程材料, 2014, 38(9): 99-102.
    引用本文: 张阳, 聂玉峰, 武亚涛. 基于数字图像处理和有限元预测纳米颗粒增强聚合物基复合材料的弹性模量[J]. 机械工程材料, 2014, 38(9): 99-102.
    ZHANG Yang, NIE Yu-feng, WU Ya-tao. Prediction for Elastic Modulus of Particle-Reinforced Polymer Nanocomposite Based on Digital Image Processing and Finite Element[J]. Materials and Mechanical Engineering, 2014, 38(9): 99-102.
    Citation: ZHANG Yang, NIE Yu-feng, WU Ya-tao. Prediction for Elastic Modulus of Particle-Reinforced Polymer Nanocomposite Based on Digital Image Processing and Finite Element[J]. Materials and Mechanical Engineering, 2014, 38(9): 99-102.

    基于数字图像处理和有限元预测纳米颗粒增强聚合物基复合材料的弹性模量

    Prediction for Elastic Modulus of Particle-Reinforced Polymer Nanocomposite Based on Digital Image Processing and Finite Element

    • 摘要: 运用数字图像处理技术, 对有机粘土纳米颗粒增强聚丙烯复合材料的微观形貌进行处理, 获取有机粘土纳米颗粒的形状及其在聚丙烯基体中的分布情况, 进而建立充分反映其微观结构的二维代表体积元(RVE)模型; 对该模型用有限元方法进行拉伸模拟, 通过计算模型的平均应力和应变, 预测了复合材料的弹性模量, 并对其内部的应力和应变分布进行了分析。结果表明: 弹性模量的计算结果与试验结果差异较小, 验证了借助数字图像处理和有限元分析技术预测纳米颗粒增强聚合物基复合材料弹性模量是可行的。

       

      Abstract: The digital image processing technology was used to obtain the shape of organoclay nanoparticles and distribution of the nanoparticles on PP matrix from the SEM image of PP/organoclay particle-reinforced nanocomposite. Then a 2D RVE(representative volume element)model could fully reflecting the microstructure of the composites was built.The stretching simulation process was carried out by finite element method, the elastic modulus of the composite was predicted by calculating the average stress and strain, and the distribution of the stress and strain in the composite were also analyzed. The results show that the calculation results fit well with the experiment ones. The method through the digital image processing and finite element analysis is reliable for predicting elastic modulus of particle-reinforced polymer nanocomposite.

       

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