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Abstract
The impact of the nanoparticles and ribs on the thermal performance of the rotating U-type cooling channel are investigated for turbulent forced convection flow of nanofluids. The nanofluids are provided by the inclusion of the nanoparticles of TiO2 and Al2O3 in water as the base fluid, namely, water/Al2O3 and water/TiO2 nanofluids mixtures. The simulations are performed for three-dimensional turbulent flow and heat transfer using an RNG k-ϵ turbulence model for Reynolds number range of 5000 to 20,000. To show the effectiveness of the ribs and nanofluids, three criteria are employed: heat transfer enhancement, pressure drop or power consumed, and the thermal performance factor. It is found that the contribution of turbulence promotion in heat transfer enhancement of the ribbed channel is more effective than that of enlarging the heat surface area. The results show that using ribs at the lowest Reynolds number and utilizing nanofluids at the highest one provide high heat transfer rate and thermal performance. At the middle Reynolds numbers, the effects of these two methods on heat transfer enhancement are relatively close to each other. In this case, if the pumping power is the main concern, using nanofluids is recommended due to providing a smaller pressure drop penalty.
NOMENCLATURE
| A | = | heat transfer surface area, m2 |
| Ac | = | heat transfer cross section area, m2 |
| Cp | = | heat capacity, kJ/kg-K |
| D | = | side of the channel cross section, m |
| df | = | equivalent diameter of the base fluid molecule, m |
| dnp | = | nanoparticle diameter, m |
| E | = | thermal performance, dimensionless |
| e | = | rib height, m |
| eijk | = | permutation symbol, dimensionless |
| f | = | friction coefficient, dimensionless |
| h | = | convection heat transfer coefficient, W/m2-K |
| k | = | turbulence kinetic energy, J/kg |
| kb | = | Boltzmann constant, 1.38066 × 10−23 J/K |
| L1 | = | length of the straight passes with bend region, m |
| L2 | = | length of the straight passes without bend region, m |
| M | = | molecular weight of the base fluid, kg/mol |
| N | = | Avogadro number, 6.022 × 1023 mol−1 |
| Nu | = | Nusselt number, dimensionless |
| NuDB | = | Nusselt number (Dittus–Boelter correlation), dimensionless |
| P | = | pressure, Pa |
| P | = | rib pitch, m |
| = | mean pressure, Pa | |
| PP | = | pumping power, W |
| (Pmax /ρ)* | = | scaled ratio of peak pressure to density |
| ΔP | = | pressure drop, Pa |
| Pr | = | Prandtl number, dimensionless |
| Prt | = | turbulent Prandtl number, dimensionless |
| q | = | total heat transfer rate, W |
| q | = | local heat flux, W/m2 |
| r | = | inner bend diameter, m |
| Re | = | Reynolds number, dimensionless |
| = | nanoparticles Reynolds number, dimensionless | |
| S | = | path length, m |
| T | = | temperature, K |
| t | = | time, s |
| = | time-averaged temperature, K | |
| T* | = | scaled bulk temperature, dimensionless |
| T0 | = | reference temperature, K |
| Tfr | = | freezing point of the base fluid, K |
| ΔTLMTD | = | log-mean temperature difference, K |
| = | time-averaged velocity component, m/s | |
| u | = | x-component of the fluid velocity, m/s |
| w | = | rib width, m |
| x, y, z | = | Cartesian coordinates, m |
| y+ | = | dimensionless wall distance |
Greek Symbols
| β | = | fraction of liquid volume travelling with a particle |
| ϵ | = | turbulent dissipation rate, J/kg-s |
| ϕ | = | nanoparticle volume concentration,% |
| Γ | = | averaged vorticity, 1/s |
| λ | = | thermal conductivity, W/m-K |
| Ω | = | angular velocity, rad/s |
| μ | = | viscosity, N-s/m2 |
| μt | = | turbulent viscosity, N-s/m2 |
| p | = | density, kg/m3 |
| ρbf0 | = | density of the base fluid at temperature of 273 K, kg/m3 |
| ω | = | vorticity magnitude, 1/s |
| ωs | = | vorticity component along the flow direction |
Subscripts
| 0 | = | pure water flow at Re = 5,000 |
| bf | = | base fluid |
| i,j,k | = | indices in x, y, z directions |
| in | = | inlet |
| m | = | bulk |
| mi | = | inlet bulk |
| mo | = | outlet bulk |
| max | = | maximum |
| nf | = | nanofluid |
| np | = | nanoparticle |
| pw | = | pure water flow |
| r | = | ribbed channel |
| ref | = | reference condition |
| s | = | smooth channel |
| w | = | wall |
Additional information
Notes on contributors
Mokhtar Kanikzadeh
Mokhtar Kanikzadeh received his M.Sc. in thermofluids from the Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran, in 2013. He is currently working at a research center. His research interest is focused on heat transfer enhancement and computational micro- and nanofluidics.
Ahmad Sohankar
Ahmad Sohankar is an associate professor in the Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran. He received his M.Sc. from this department in 1991 and Ph.D. from the Department of Thermal and Fluid Dynamics, Chalmers University of Technology, Gothenburg, Sweden, in 1998. His main research interests include turbulence modeling, computational fluid dynamics, heat transfer enhancement, and experimental methods.