Abstract

The passive method by using a vortex generator (VG) is an effective method for the improvement of convective heat transfer. This study is focused on usage of concave rectangular winglet vortex generator (CRW VG) for improving convective heat transfer in a fin-and-tube heat exchanger using numerical simulation. Concave rectangular winglet pairs (CRWP) and rectangular winglet pairs (RWP) VGs were mounted inside the gap between fins (gas side) with variations of the number of VG pairs of rows. Inlet air velocity variations expressed by the Reynolds numbers were ranged from 364 to 689. Augmentation of heat transfer is indicated by the ratio value of heat transfer convection coefficient between cases using VG and that without using VG (baseline). The results show that the convection heat transfer coefficient for cases using CRWP VG is higher than that using RWP VG. Convection heat transfer coefficient increases up to 102% by mounting CRWP VG at Re = 364. However, the increase in convection coefficient is accompanied by a rise in pressure drop to 216.8%.

Highlights

  • Abstract.The passive method by using a vortex generator (VG) is an effective method for the improvement of convective heat transfer

  • This mixing enhances local heat and momentum transfer from the wall to the main flow. These results indicate that the use of Concave rectangular winglet pairs (CRWP) VG improves the convection coefficient better than rectangular winglet pairs (RWP) VG for the same Reynolds number because of stronger longitudinal vortex generated from the CRWP VG than that of RWP VG

  • At Re = 364, the use of 1 row of RWP and CRWP VGs increases the value of convection coefficients by 11% and 22% respectively to the baseline

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Summary

2Physical and numerical models

Continuity, momentum and energy equations were applied for solving the physical problems. In order to solve the mathematical equations, boundary conditions were applied to some predetermined regions. Momentum and energy with some boundary conditions were solved by using computational fluid dynamics code (ANSYS Fluent 14.5). There are similar tendencies for convection coefficient and pressure drop values between the results of these simulations with the results of experiments performed by Joardar and Jacobi [4]. By comparing the simulation and Joardar and Jacobi’s experimental results, the value of convection coefficients deviate from 8% to 13% in the Reynolds number ranges from 523 to 942. While the pressure drop value deviates from 4% to 16% in the same range of Reynolds numbers

3Results and discussion
Findings
Conclusions
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