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Heat Transfer Enhancement Using Rectangular and Triangular Shaped Baffles with and without Nanofluid: New Insight into Optimization of Flow Geometric Parameters

Abstract

In this paper, the optimization of geometric parameters that affect heat transfer and pressure drop of water-Al2O3 nanofluid were carried out in rectangular and triangular baffles with different volume fractions of nanofluid. The investigations were done in two-dimensional state and under boundary condition of constant temperature. Flow modeling was performed by considering Pb = 0.5, 1 and 2 as pitch, h = 3, 4, 5 as height, and φ = 0.02, φ = 0.04 and φ = 0.00 as volume fractions. The range of Reynolds number was 2000 < Re <10 000 and the periodic boundary condition was used to reduce the time of computations. Optimization was performed using genetic algorithm. The results of modeling show that the installation of the baffle increases heat transfer and pressure drop. Among two types of baffles, the highest amount of heat transfer is related to triangular baffle and the highest amount of friction coefficient is related to rectangular baffle. It was also observed that the pitch and height of the baffle have inverse and direct relationship with heat transfer and coefficient of friction, respectively. The thermal performance of heat exchanger increases with the increases of volume fraction of the nanofluid and decreases with the increase of Reynolds number. Moreover, comparing to rectangular baffle, triangular baffle has the highest thermal performance in constant volume fraction. In order to maximize thermal performance in low Reynolds numbers, low Pb and high H ratios can be used. On the other hand, in high Reynolds numbers, high Pb and low H ratios maximize thermal performance. In general, it can be concluded that the simultaneous use of aluminum oxide nanofluid and baffle increases the Nusselt number and in best condition, the optimization increases up to 1.5 times

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Correspondence to Farshad Kowsary.

APPENDIX

APPENDIX

C p Specific heat capacity, kj/kg k Greek letter
D Channel diameter, m μ Kinematic viscosity, kg/m s
f Friction factor ρ Density, kg/m3
H Dimensional heighy (=h/d) τ Stress, Pa
h Baffle height, m η Thermal efficiency coefficient
K Thermal conductivity Coefficient, w/m k φ Nanoparticle volume fraction
L Channel length, m ω Turbulence
\(\dot {m}\) Mass flow rate, kg/s Subtitles
Nu Nusselt number b Bulk
P Dimensional pitch (=p/l) ba Baffle
p Baffle pitch, m bf Base fluid
Pr Prandtl number E Enhanced
q Heat transfer, w i Unit vector
R Channel radius, m n Nanoparticle
Re Reynolds number nf Nanofluid
t Channel thickness, m t Turbulence
T Temperature, K w Width baffle
u Velocity in x direction. m/s   
\(v\) Velocity in y direction. m/s   
W Baffle thickness, m   
x, y Cartesian coordinates   
ΔP Pressure drop   
ΔTlm Logarithmic mesn temperature difference   

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Ghobadi, B., Kowsary, F. & Veysi, F. Heat Transfer Enhancement Using Rectangular and Triangular Shaped Baffles with and without Nanofluid: New Insight into Optimization of Flow Geometric Parameters. Prot Met Phys Chem Surf 58, 486–500 (2022). https://doi.org/10.1134/S2070205122030091

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  • DOI: https://doi.org/10.1134/S2070205122030091

Keywords:

  • heat transfer optimization
  • water-Al2O3 nanofluid
  • genetic algorithm
  • thermal performance