A physical-statistical model for predicting the effective thermal conductivity of nanofluids is proposed. The volumetric unit of nanofluids in the model consists of solid, liquid, and gas particles and is treated as a system made up of regular geometric figures, spheres, filling the volumetric unit by layers. The model assumes that connections between layers of the spheres and between neighbouring spheres in the layer are represented by serial and parallel connections of thermal resistors, respectively. This model is expressed in terms of thermal resistance of nanoparticles and fluids and the multinomial distribution of particles in the nanofluids. The results for predicted and measured effective thermal conductivity of several nanofluids (Al2O3/ethylene glycol-based and Al2O3/water-based; CuO/ethylene glycol-based and CuO/water-based; and TiO2/ethylene glycol-based) are presented. The physical-statistical model shows a reasonably good agreement with the experimental results and gives more accurate predictions for the effective thermal conductivity of nanofluids compared to existing classical models.
Physical-Statistical Model of Thermal Conductivity of Nanofluids
