Simulation and Optimization Study on the Performance of Fin-and-Tube Heat Exchanger

Nijie Jing (), Yudong Xia, Qiang Ding, Yuezeng Chen, Zhiqiang Wang and Xuejun Zhang
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Nijie Jing: Institute of Refrigeration & Cryogen, Zhejiang University, Hangzhou 310027, China
Yudong Xia: Institute of Energy Utilization and Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Qiang Ding: Institute of Energy Utilization and Automation, Hangzhou Dianzi University, Hangzhou 310018, China
Yuezeng Chen: Ningbo Hicon Industry Co., Ltd., Yuyao 315470, China
Zhiqiang Wang: Ningbo Hicon Industry Co., Ltd., Yuyao 315470, China
Xuejun Zhang: Institute of Refrigeration & Cryogen, Zhejiang University, Hangzhou 310027, China

Sustainability, 2023, vol. 15, issue 15, 1-15

Abstract: Heat exchangers (HX) are often utilized in industry, and the optimization of the performance of HX is a key area of research. In this study, EVAP-COND software 4.0 and genetic algorithm (GA) based optimization methods were proposed to optimize the circuitry and fin pitch of a finned tube heat exchanger for an air conditioner. A simulation model for a multi-circuit finned-tube evaporator used in an air conditioning unit was developed using the EVAP-COND software, and further validated based on the experimental data. Considering the refrigerant flow maldistribution of the original HX, four different circuit arrangements, i.e., types A, B, C, and D, were designed and optimized circuitry obtained. Based on both simulation and experimental results, D-type HX with 1.8 mm fin pitch was selected as 10% tubes could be saved with no significant loss of heat transfer capacity. Then the fin pitch was further optimized using the multi-objective GA method, with both Colburn factor j and friction factor f being considered. Optimization results showed that, in Pareto front, points 1 to 4 showed the increase in the Colburn factor j was negative, while the decrease in the friction factor f was positive. The friction factor decreased by 3.5% as one moved from Point 1 to Point 4, but the Colburn factor rose by 1.02%. Points 5 to 10 demonstrated that, while the decrease in the friction factor was negative, the increase in the Colburn factor was positive. The friction factor decreased by 5.31%, but the Colburn factor increased by 1.51% when going from Point 5 to Point 10. The results of optimization demonstrated that the objective function performed at its optimum when the fin pitch was around 1.77 mm.

Keywords: finned-tube heat exchanger; genetic algorithm; fin pitch; optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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