Numerical Simulation of Thermal Conductivity of Nanofluids

The recent first-principle model shows a dual-phase-lagging heat conduction in nanofluids at the macroscale. The macroscopic heat-conduction behavior and the thermal conductivity of nanofluids are determined by their molecular physics and microscale physics. We examine numerically effects of particle-fluid thermal conductivity ratio, particle volume fraction, shape, aggregation, and size distribution on macroscale thermal properties for nine types of nanofluids, without considering the interfacial thermal resistance and dynamic processes on particle-fluid interfaces and particle-particle contacting surfaces. The particle radius of gyration and non-dimensional particle-fluid interfacial area in the unit cell are two very important parameters in characterizing the effect of particles’ geometrical structures on thermal conductivity of nanofluids. Nanofluids containing cross-particle networks have conductivity which practically reaches the Hashin-Shtrikman bounds. Moreover, particle aggregation influences the effective thermal conductivity only when the distance between particles is less than the particle dimension. Uniformly-sized particles are desirable for the conductivity enhancement, although to a limited extent.