Dependence of effective thermal conductivity of composite materials on the size of filler particles

被引:10
|
作者
Chauhan, Deepti [1 ]
Singhvi, Nilima [1 ]
Singh, Ramvir [1 ]
机构
[1] Univ Rajasthan, Dept Phys, Thermal Phys Lab, Jaipur 302055, Rajasthan, India
关键词
Effective thermal conductivity; polymer composites; correction factor s; size of filler; artificial neural network technique; POLYMER COMPOSITES; POROUS MATERIALS; NEURAL-NETWORKS; DIFFUSIVITY; PREDICTION;
D O I
10.1177/0731684413490540
中图分类号
TB33 [复合材料];
学科分类号
摘要
A well-known Maxwell's model for evaluation of effective thermal conductivity has been modified incorporating a correction factor s. It is an important quantity, which influences the effective thermal conductivity of composite materials together with other parameters like volume fraction and thermal conductivities of the constituents. Parameter estimation technique is used to determine the value of s. Optimized value of s is used in the modified Maxwell's model to estimate effective thermal conductivity of composite materials. The effective thermal conductivity of composite materials using an artificial neural network approach has also been calculated. Materials of different sizes of filler particles/matrix have been considered for calculation of the effective thermal conductivity. Results obtained using modified Maxwell's model and artificial neural network technique have been compared with the experimental results available in the literature which shows a good fit.
引用
收藏
页码:1323 / 1330
页数:8
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