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PMID: 34828842 Published · epublish English Journal Article

Analysis of the Temperature Distribution in a Refrigerated Truck Body Depending on the Box Loading Patterns.

Foods (Basel, Switzerland) ·Vol. 10 ·No. 11 ·2021-10-23

So JH, Joe SY, Hwang SH, Jun S, Lee SH

Abstract

The main purpose of cold chain is to keep the temperature of products constant during transportation. The internal temperature of refrigerated truck body is mainly measured with a temperature sensor installed at the hottest point on the body. Hence, the measured temperature cannot represent the overall temperature values of transported products in the body. Moreover, the airflow pattern in the refrigerated body can vary depending on the arrangement of loaded logistics, resulting temperature differences between the transported products. In this study, the airflow and temperature change in the refrigerated body depending on the loading patterns of box were analyzed using experimental and numerical analysis methods. Ten different box loading patterns were applied to the body of 0.5 ton refrigerated truck. The temperatures inside boxes were measured depending on the loading patterns. CFD modeling with two different turbulence models (k-ε and SST k-ω) was developed using COMSOL Multiphysics for predicting the temperatures inside boxes loaded with different patterns, and the predicted data were compared to the experimental data. The k-ε turbulence model showed a higher temperature error than the SST k-ω model; however, the highest temperature point inside the boxes was almost accurately predicted. The developed model derived an approximate temperature distribution in the boxes loaded in the refrigerated body.

Keywords
CFD modelling airflow loading pattern refrigerated truck temperature prediction
作者与单位
共 5 位作者,点击展开单位 / ORCID
So Jun-Hwi
Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea.
Joe Sung-Yong
Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea.
Hwang Seon-Ho
Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea.
Jun Soojin ORCID
Department of Human Nutrition, Food and Animal Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, USA.
Lee Seung-Hyun ORCID
Department of Smart Agriculture Systems, Chungnam National University, Daejeon 34134, Korea. | Department of Biosystems Machinery Engineering, Chungnam National University, Daejeon 34134, Korea.
Article Info
Journal
Foods (Basel, Switzerland)
Abbr.
Foods
ISSN
2304-8158
Published
2021-10-23
电子出版
2021-00-23
Language
English
Country/Region
Switzerland
NLM ID
101670569
基金资助
Chungnam National University · 2020-0533-01
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