随机短纤维增强复合材料弹性模量预测模型

Prediction model for elastic modulus of random short fiber reinforced composite

  • 摘要: 为了研究纤维增强复合材料的力学性能, 借助混合率构造的Reuss-Voigt模型以及三维纤维取向简化模型, 建立了随机短纤维复合材料弹性模量预测模型。利用该模型对玻璃纤维增强尼龙6(PA6)复合材料进行弹性模量预测, 其预测结果与拉伸实验结果误差值小于5%, 表明该预测模型具有较好的准确性。

     

    Abstract: To study the mechanical property of fiber reinforced composite, Reuss-Voigt model and 3D fiber orientation simplified model were utilized to develop the prediction model for elastic modulus of random short fiber reinforced composite (RSFRC). By virtue of this model, elastic modulus of glass fiber reinforced PA6 composite is predicted. The tolerance between calculated results and the tensile test values is less than 5%, which testified the good accuracy of the prediction model for elastic modus of RSFRC.

     

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