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

ZHANG Yang; NIE Yu-feng; WU Ya-tao

Materials and Mechanical Engineering > 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.

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

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Received Date: December 24, 2013

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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.
- digital image,
- representative volume element model,
- nanoparticle,
- composite,
- finite element

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[1]	WETZEL B, HAUPERT F, ZHANG M Q. Epoxy nanocomposites with high mechanical and tribological performance［J］.Composites Science and Technology,2003,63:2055-2067.
[2]	JANCAR J, DOUGLAS J F, STARR F W, et al. Current issues in research on structure-property relationships in polymer nanocomposites［J］.Polymer,2010,51:3321-3343.
[3]	IWAHORI Y, ISHIWATA S, SUMIZAWA T, et al. Mechanical properties improvements in two-phase and three-phase composites using carbon nano-fiber dispersed resin［J］.Composites-part A: applied Science and Manufacturing,2005,36(10):1430-1439.
[4]	UDDIN M F, SUN C T. Strength of unidirectional glass/epoxy composite with silica nanoparticle-enhanced matrix［J］.Composites Science and Technology, 2008, 68 (7/8):1637-1643.
[5]	谢桂兰, 张平, 龚曙光, 等.结晶聚合物基纳米复合材料多层次结构及有效性能预测［J］.高分子材料科学与工程, 2005,21(4):23-27.
[6]	王振清, 雷红帅, 王晓强, 等.纳米TiO2颗粒弱界面增强树脂基复合材料宏观力学行为有限元模拟［J］.复合材料学报, 2013,30(1):236-243.
[7]	HBAIED K, WANG Q X, CHIA Y H J, et al. Modelling stiffness of polymer/clay nanocomposites［J］.Polymer,2007,48:901-909.
[8]	丁秀丽, 李耀旭, 王新.基于数字图像的土石混合物体力学性质的颗粒流模拟［J］.岩石力学与工程学报, 2010,29(3):477-484.
[9]	何春霞, 肖声明, 陆德荣, 等.纳米SiC/PTFE复合材料微观结构SEM图像处理及分析［J］.武汉科技大学学报, 2011, 34(1):23-27.
[10]	杨智勇, 韩建民, 李卫京, 等.颗粒增强铝基复合材料均质假设有限元计算的有效性［J］.机械工程材料, 2009,33(11):35-38.
[11]	卞凯, 姜传海, 栾卫志.TiB2/Al复合材料喷丸后微区残余应力的有限元模拟［J］.机械工程材料, 2011,35(1):86-88.
[12]	KANIT T, FOREST S, GALLIET I, et al. Determination of the size of the representative volume element for random composites: statistical and numerical approach［J］.International Journal of Solids and Structures,2003,40(13/14):3647-3679.
[13]	DONG Y, BHATTACHARYYA D, HUNTER P J. Experimental characterization and object-oriented finite element modelling of polypropylene/organoclay nanocomposites［J］.Composites Science and Technology,2008,60:2864-2875.
[14]	杨松, 邵龙潭, 郭晓霞, 等.基于混凝土裂纹数字图像的有限元网格生成［J］.计算力学学报, 2012, 29(4): 635-640.
[15]	ZENG Q H, YU A B, LU G Q. Multiscale modeling and simulation of polymer nanocomposites［J］.Progress in Polymer Science,2008,33:191-269.

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