Computational modeling of airflow and heat transfer in a vented box during cooling: Optimal package design
文献类型: 外文期刊
第一作者: Han, Jia-Wei
作者: Han, Jia-Wei;Han, Jia-Wei;Zhao, Chun-Jiang;Yang, Xin-Ting;Qian, Jian-Ping;Fan, Bei-Lei
作者机构:
关键词: Computational fluid dynamics (CFD); Numerical analysis; Forced-air precooling; Temperature distribution; Heat transfer
期刊名称:APPLIED THERMAL ENGINEERING ( 影响因子:5.295; 五年影响因子:5.175 )
ISSN: 1359-4311
年卷期: 2015 年 91 卷
页码:
收录情况: SCI
摘要: Optimization of fresh fruit packaging designs is required to reduce energy loss by minimizing the pre-cooling time and to enhance fruit quality by providing more uniform cooling without inducing chilling injuries. In this work, a computational fluid dynamics (CFD) model is developed to study the airflow patterns and heat transfer inside an existing container and a newly developed container. The CFD model employs an unsteady-state approach based on a two-equation eddy-viscosity turbulence model (SST-kappa -omega model). The cooling performance of the existing container and the new container are evaluated experimentally and numerically with the CFD model. The CFD results reveal a complex and uneven distribution of the airflow inside the existing vented package. Such airflow leads to a non-uniform temperature distribution over the produce, with a maximum temperature difference of similar to 8 degrees C between two layers of stacked produce. For the new boxes, the half-cooling time and coefficient of temperature variation are about twofold less than those for the existing boxes, and the maximum temperature difference is similar to 2.5 degrees C between two layers of stacked produce. Thus, the new package design clearly shows significant improvements in cooling performance. The numerical model is verified by comparing the simulation results to those of experiments, and the predicted results are consistent with the measured results. The maximum temperature deviation is less than 1.5 degrees C, and the maximum root-mean-square error and average relative error for produce temperature are 1.452 degrees C and 13.6%, respectively. This research provides a reliable theoretical and experimental basis for improving airflow and produce-temperature uniformity and for minimizing energy consumption during the forced-convection cooling of produce. (C) 2015 Elsevier Ltd. All rights reserved.
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