Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm

doi:10.1016/j.cjche.2020.05.036

中国化学工程学报 ›› 2020, Vol. 28 ›› Issue (8): 2142-2151.DOI: 10.1016/j.cjche.2020.05.036

• Chemical Engineering Thermodynamics • 上一篇下一篇

Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm

Mirollah Hosseini¹, Hamid Hassanzadeh Afrouzi², Sina Yarmohammadi², Hossein Arasteh³, Davood Toghraie⁴, A. Jafarian Amiri², Arash Karimipour⁵

1 Department of Mechanical Engineering, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Mazandaran, Iran;
2 Faculty of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran;
3 Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran;
4 Department of Mechanical Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr, Iran;
5 Sustainable Management of Natural Resources and Environment Research Group, Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam

收稿日期:2019-10-01 修回日期:2020-04-28 出版日期:2020-08-28 发布日期:2020-09-19
通讯作者: Arash Karimipour

Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm

Mirollah Hosseini¹, Hamid Hassanzadeh Afrouzi², Sina Yarmohammadi², Hossein Arasteh³, Davood Toghraie⁴, A. Jafarian Amiri², Arash Karimipour⁵

1 Department of Mechanical Engineering, Islamic Azad University, Qaemshahr Branch, Qaemshahr, Mazandaran, Iran;
2 Faculty of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran;
3 Department of Mechanical Engineering, Isfahan University of Technology, Isfahan, Iran;
4 Department of Mechanical Engineering, Khomeinishahr Branch, Islamic Azad University, Khomeinishahr, Iran;
5 Sustainable Management of Natural Resources and Environment Research Group, Faculty of Environment and Labour Safety, Ton Duc Thang University, Ho Chi Minh City, Vietnam

Received:2019-10-01 Revised:2020-04-28 Online:2020-08-28 Published:2020-09-19
Contact: Arash Karimipour

摘要/Abstract

摘要： In this study, the heat transfer optimization (evaporation) and the specification of the FX-70 zeotropic refrigerant flow inside a corrugated pipe have been investigated. Despite the low HTC (HTC), this type of refrigerant is highly applicable in low or medium temperature engineering systems during the evaporation process. To eliminate this defect, high turbulence and proper mixing are required. Therefore, using heat transfer (HT) augmentation methods will be necessary and effective. In order to find the most favorable operating conditions that lead to the optimum combination of pressure drop (PD) and HTC, empirical data, neural networks, and genetic algorithms (GA) for multi-objective (MO) (NSGA II) are used. To investigate the mentioned cases, the geometric parameters of corrugated pipes, vapor quality, and mass velocity of refrigerant were studied. The results showed that with vapor quality higher than 0.8 and corrugation depth and pitch of 1.5 and 7 mm, respectively, we would achieve the desired optimum design.

关键词: Optimization, Genetic algorithm, Neural network, Corrugated tube, FX-70 refrigerant

Abstract: In this study, the heat transfer optimization (evaporation) and the specification of the FX-70 zeotropic refrigerant flow inside a corrugated pipe have been investigated. Despite the low HTC (HTC), this type of refrigerant is highly applicable in low or medium temperature engineering systems during the evaporation process. To eliminate this defect, high turbulence and proper mixing are required. Therefore, using heat transfer (HT) augmentation methods will be necessary and effective. In order to find the most favorable operating conditions that lead to the optimum combination of pressure drop (PD) and HTC, empirical data, neural networks, and genetic algorithms (GA) for multi-objective (MO) (NSGA II) are used. To investigate the mentioned cases, the geometric parameters of corrugated pipes, vapor quality, and mass velocity of refrigerant were studied. The results showed that with vapor quality higher than 0.8 and corrugation depth and pitch of 1.5 and 7 mm, respectively, we would achieve the desired optimum design.

Key words: Optimization, Genetic algorithm, Neural network, Corrugated tube, FX-70 refrigerant

Mirollah Hosseini, Hamid Hassanzadeh Afrouzi, Sina Yarmohammadi, Hossein Arasteh, Davood Toghraie, A. Jafarian Amiri, Arash Karimipour. Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm[J]. 中国化学工程学报, 2020, 28(8): 2142-2151.

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Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm

Optimization of FX-70 refrigerant evaporative heat transfer and fluid flow characteristics inside the corrugated tubes using multi-objective genetic algorithm

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