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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。
In order to investigate the thermal expansion properties of continuous fiber reinforced composites, a stochastic perturbation model was developed by considering the distribution of fibers in the cross section of the unidirectional composites and the real periodic boundary conditions of the stochastic model. For high fiber volume Random stochastic model, a stochastic perturbation method (RDM) is proposed. The maximum fiber volume fraction that can be processed by this method is not less than 65%. The thermal expansion performance of M40J / TDE-85 was predicted by this stochastic model, and the thermal expansion coefficient of the composite was tested with high accuracy. The results show that the predicted results are in good agreement with the experimental results, and the stochastic model is also able to predict the thermal expansion coefficient of the composites well. The random perturbation model can be used to predict the thermal expansion of composites quickly and accurately, which is convenient for material research and engineering application.