随机结构复合材料等效导热系数的理论预测

Theoretical prediction for effective thermal conductivity of composite materials with random structure

基于随机生成结构法创建了纤维随机排布的复合材料纤维体,采用链表数据结构实现了一种物理直观、不依赖网格划分的纤维体等效导热系数理论预测方法。将该方法用于酚醛浸渍碳烧蚀材料,研究了影响等效导热系数的相关因素。结论表明:复合材料的等效导热系数并非材料固有属性,纤维长度与试件尺度相近时,试件尺度会影响材料导热系数;单位空间的纤维根数与等效导热系数呈非线性正相关关系;但等效导热系数并非体积分数的单变量函数,还取决于纤维的连通性,有效长度愈小,则表明连通性愈好,等效导热系数愈大。

Based on the random generate-growth method,a theoretical method employing linked lists was implemented to predict the effective thermal conductivity of fiber-reinforced composite materials with random structure,which has the feature of physical intuition and independent of mesh.The fiber perform of like-PICA(Phenolic impregnated carbon ablator)was studied to reveal the relevant factors that can influence the effective thermal conductivity.The results show that the effective thermal conductivity is not an intrinsic property and it may be related with the specimen size when it is close to fiber length.There is a positive nonlinear correlation between the fiber quantity per volume and the effective thermal conductivity.However,the effective thermal conductivity is not a univariate function of volume fraction and the concept of the effective length is present to describe the connectivity of fiber perform,which is negative correlation with the effective thermal conductivity.