Temperature Distribution in Insulated Temperature-Controlled Container by Numerical Simulation
文献类型： 外文期刊
作者： Li, Bin 1 ; Guo, Jiaming 1 ; Xia, Jingjing 1 ; Wei, Xinyu 1 ; Shen, Hao 1 ; Cao, Yongfeng 1 ; Lu, Huazhong 3 ; Lu, Enli 1 ;
作者机构： 1.South China Agr Univ, Coll Engn, Guangzhou 510642, Peoples R China
2.Guangdong Mech & Elect Coll Technol, Sch Automobile, Guangzhou 510515, Peoples R China
3.Guangdong Acad Agr Sci, Guangzhou 510640, Peoples R China
关键词： computational fluid dynamics; numerical analysis; cold-storage container; temperature distribution; optimization; cold chain
期刊名称：ENERGIES （ 影响因子：3.004； 五年影响因子：3.085 ）
ISSN：
年卷期： 2020 年 13 卷 18 期
页码：
收录情况： SCI
摘要： 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 degrees 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.
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