Choosing correct boundary conditions, flow field characteristics and employing right
thermal fluid properties can affect the simulation of convection heat transfer using
nanofluids. Nanofluids have shown higher heat transfer performance in comparison with
conventional heat transfer fluids. The suspension of the nanoparticles in nanofluids
creates a larger interaction surface to the volume ratio. Therefore, they can be
distributed uniformly to bring about the most effective enhancement of heat transfer
without causing a considerable pressure drop. These advantages introduce nanofluids as
a desirable heat transfer fluid in the cooling and heating industries. The thermal effects of
nanofluids in both forced and free convection flows have interested researchers to a great
extent in the last decade.
Investigating the interaction mechanisms happening between nanoparticles and base
fluid is the main goal of the study. These mechanisms can be explained via different
approaches through some theoretical and numerical methods. Two common approaches
regarding particle-fluid interactions are Eulerian-Eulerian and Eulerian-Lagrangian.
The dominant conceptions in each of them are slip velocity and interaction forces
respectively. The mixture multiphase model as part of the Eulerian-Eulerian approach
deals with slip mechanisms and somehow mass diffusion from the nanoparticle phase to
the fluid phase. The slip velocity can be induced by a pressure gradient, buoyancy, virtual
mass, attraction and repulsion between particles. Some of the diffusion processes can be
caused by the gradient of temperature and concentration. The discrete phase model (DPM) is a part of the Eulerian-Lagrangian approach. The
interactions between solid and liquid phase were presented as forces such as drag,
pressure gradient force, virtual mass force, gravity, electrostatic forces, thermophoretic
and Brownian forces. The energy transfer from particle to continuous phase can be
introduced through both convective and conduction terms on the surface of the particles.
A study of both approaches was conducted in the case of laminar and turbulent forced
convections as well as cavity flow natural convection. The cases included horizontal and
vertical pipes and a rectangular cavity. An experimental study was conducted for cavity
flow to be compared with the simulation results. The results of the forced convections
were evaluated with data from literature. Alumina and zinc oxide nanoparticles with
different sizes were used in cavity experiments and the same for simulations. All the
equations, slip mechanisms and forces were implemented in ANSYS-Fluent through some
The comparison showed good agreement between experiments and numerical results.
Nusselt number and pressure drops were the heat transfer and flow features of nanofluid
and were found in the ranges of the accuracy of experimental measurements. The findings
of the two approaches were somehow different, especially regarding the concentration
distribution. The mixture model provided more uniform distribution in the domain than
the DPM. Due to the Lagrangian frame of the DPM, the simulation time of this model
was much longer. The method proposed in this research could also be a useful tool for
other areas of particulate systems.