Temperature Distribution in Insulated Temperature-Controlled Container by Numerical Simulation

Bin Li, Jiaming Guo, Jingjing Xia, Xinyu Wei, Hao Shen, Yongfeng Cao, Huazhong Lu and Enli Lü
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Bin Li: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Jiaming Guo: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Jingjing Xia: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Xinyu Wei: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Hao Shen: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Yongfeng Cao: College of Engineering, South China Agricultural University, Guangzhou 510642, China
Huazhong Lu: Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China
Enli Lü: College of Engineering, South China Agricultural University, Guangzhou 510642, China

Energies, 2020, vol. 13, issue 18, 1-16

Abstract: Cold-storage containers are widely used in cold-chain logistics transportation due to their energy saving, environmental protection, and low operating cost. The uniformity of temperature distribution is significant in agricultural-product storage and transportation. This paper explored temperature distribution in the container by numerical simulation, which included ventilation velocity and the fan location. Numerical model/numerical simulation showed good agreement with experimental data in terms of temporal and spatial air temperature distribution. Results showed that the cooling rate improved as velocity increased, and temperature at 45 min was the lowest, when velocity was 16 m/s. Temperature-distribution uniformity in the compartment became worse with the increase in ventilation velocity, but its lowest temperature decreased with a velocity increase. With regard to fan energy consumption, the cooling rate of the cooling module, and temperature-field distribution in the product area, velocity of 12 m/s was best. Temperature standard deviation and nonuniformity coefficient in the container were 0.87 and 2.1, respectively, when fans were located in the top four corners of the container. Compared with before, the average temperature in the box was decreased by 0.12 °C, and the inhomogeneity coefficient decreased by more than twofold. The results of this paper provide a better understanding of temperature distribution in cold-storage containers, which helps to optimize their structure and parameters.

Keywords: computational fluid dynamics; numerical analysis; cold-storage container; temperature distribution; optimization; cold chain (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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