复合材料热膨胀性能预报的随机扰动模型与实验验证

Random disturbing model and experimental verification for thermal expansion property prediction of composite

  • 摘要: 为了探究连续纤维增强的复合材料的热膨胀性能,综合考虑了单向复合材料横截面上纤维的分布情况以及随机模型的真实周期性边界条件等,发展了一种随机扰动模型;并针对高纤维体积分数的随机模型,提出了随机扰动法(RDM),此方法可以处理的最大纤维体积分数不小于65%。利用本随机模型对M40J/TDE-85的热膨胀性能进行了预测,同时对该复合材料的热膨胀系数进行了高精度测试。结果表明,预测结果与试验结果吻合良好,同时也证明本随机模型能较好地预测复合材料的热膨胀系数。利用本随机扰动模型可迅速准确地预测出复合材料的热膨胀性能,便于材料研究和工程应用。

     

    Abstract: To study the thermal expansion property of long fibre reinforced unidirectional (UD) composite, a new method was developed to create fibre random distribution models. In all the models, the fibre distribution state and the real periodic boundary condition have been taken into account. For models with high fibre volume fraction, a method called RDM (random disturbing method) was developed, which can generate models with fibre volume fraction not less than 65%. Random models generated by RDM were used to forecast the thermal expansion coefficient of M40J/TDE-85, and the thermal expansion coefficients of this composite were tested with high precision. The predicted results agree well with the experimental data, which shows that this random model can be used to predict the thermal expansion coefficients of UD composite correctly. It is rapid and precise to adopt this random model to predict the thermal expansion property of composite, and it would be convenient for materials study and engineering application.

     

/

返回文章
返回