Improved Heat Transfer in Guar Gel Composites Reinforced with Randomly Distributed Glass Microspheres

Improved heat transfer in composites consisting of guar gel matrix and randomly distributed glass microspheres is extensively studied to predict the effective thermal conductivity of composites using the finite element method. In the study, the proper and probabilistic three-dimensional random distribution of microspheres in the continuous matrix is automatically generated by a simple and efficient random sequential adsorption algorithm which is developed by considering the correlation of three factors including particle size, number of particles, and particle volume fraction controlling the geometric configuration of random packing. Then the dependences of the effective thermal conductivity of composite materials on some important factors are investigated numerically, including the particle volume fraction, the particle spatial distribution, the number of particles, the nonuniformity of particle size, the particle dispersion morphology and the thermal conductivity contrast between particle and matrix. The related numerical results are compared with theoretical predictions and available experimental results to assess the validity of the numerical model. These results can provide good guidance for the design of advanced microsphere reinforced composite materials.

Automated summary

Improved heat transfer in composites consisting of guar gel matrix and randomly distributed glass microspheres is studied using a finite element method. A random sequential adsorption algorithm is developed to generate the three-dimensional random distribution of microspheres in the matrix. The numerical results investigate the dependence of the effective thermal conductivity on various factors and are compared with theoretical predictions and experimental data.