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Study of flow and heat transfer features of nanofluids using multiphase models : eulerian multiphase and discrete Lagrangian approaches
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mahdavi, Mostafa |
| Copyright Year | 2016 |
| Abstract | v 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 user-defined functions. 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://repository.up.ac.za/bitstream/handle/2263/61309/Mahdavi_Study_2017.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |