Numerical Method-Based Grain Temperature Distribution of Semi-Underground Double-Storey Squat Silos During Static Storage

IF 2.9 3区 农林科学 Q3 ENGINEERING, CHEMICAL Journal of Food Process Engineering Pub Date : 2025-01-05 DOI:10.1111/jfpe.70032
Libing Jin, Doudou Zhu, Chuang Li, Linran Qiao, Xu Wang, Qiang Wu
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Abstract

Grain temperature (GT) is a crucial factor in determining the safety of grain storage. To elucidate the evolution rule of grain storage temperature distribution (TD) in semi-underground double-storey squat silos (SUDSSS), a numerical model of the TD of stored grain was constructed. A numerical model of the TD of the grain bulk (GBUL) in the squat silo and the underground silo was developed, and the model was validated through field experiments. Then, a numerical model of the TD of the GBUL in SUDSSS was established. The TD of storage grain in SUDSSS was analyzed by numerical simulation, and the 1-year temperature variation rule of stored grain in the static storage in SUDSSS was obtained. The study shows that (1) the GT within 2 m of the silo wall in the aboveground layer of the SUDSSS, was found to vary significantly with a range of 10.62°C–27.37°C based on the variation of the outside temperature. The GT in the underground layer remains at a quasi-low temperature throughout the year, with an average temperature of no more than 17°C. (2) The original GTs are set at varying levels in a SUDSSS. The temperature differential between the average GT and the original GT after 1 year of storage is 2.21°C, 1.79°C, 1.51°C, 1.13°C, and 0.34°C, respectively, in the aboveground layer. If the original temperature is relatively low, the greater the temperature change after 1 year of storage, which is still well below 20°C, long-term storage requires a lower original GT. (3) The temperature change of paddy in the SUDSSS was the most pronounced during the storage period. The temperature differential between the paddy stored in the aboveground layer for 8 months and the initial is 2.15°C, and the differential is 0.77°C when stored in the underground layer for 12 months. The temperature change of wheat and maize during storage was minimal, whereas the temperature of paddy exhibited significant fluctuations. (4) The maximum temperature differential of 15 and 3 m in condition one is 2.08°C and 2.28°C, respectively. An increase in grain height results in a reduction in temperature change during storage. Comprehensive different grain loading conditions, the GT in the peripheral area of the aboveground layer and the mean temperature of the underground layer discernible change with the varying grain loading heights. Furthermore, the temperature fluctuations of the aboveground and underground layers are largely independent of one another.

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基于数值方法的半地下双层深蹲筒仓静态贮存期间粮食温度分布
粮食温度是决定粮食储存安全性的重要因素。为了阐明半地下双层深蹲筒仓(SUDSSS)储粮温度分布的演化规律,建立了储粮温度分布的数值模型。建立了深筒仓和地下筒仓中粮食散粒分布的数值模型,并通过现场试验对模型进行了验证。在此基础上,建立了ssusss中GBUL的TD数值模型。通过数值模拟分析了冷库储粮的TD,得出了冷库静态储粮的1年温度变化规律。研究表明:(1)根据外界温度的变化,SUDSSS地上层筒仓壁2 m范围内的GT变化显著,变化范围为10.62℃~ 27.37℃。地下GT常年保持准低温,平均温度不超过17℃。(2)原GTs在SUDSSS中设置为不同的水平。储存1年后,平均温度与原始温度的地上温差分别为2.21℃、1.79℃、1.51℃、1.13℃和0.34℃。如果原温度较低,贮藏1年后温度变化越大,仍远低于20℃,则长期贮藏需要较低的原温度。(3)稻谷的温度变化在贮藏期间最为明显。地上层储存8个月的稻谷与初始的温差为2.15℃,地下层储存12个月的稻谷温差为0.77℃。小麦和玉米贮藏期间温度变化不大,而水稻贮藏期间温度波动较大。(4)工况一15 m和3 m的最大温差分别为2.08℃和2.28℃。谷物高度的增加导致贮藏期间温度变化的减小。综合不同的粮食加载条件,随着粮食加载高度的变化,地表外围区域的GT和地下层的平均温度有明显的变化。此外,地上层和地下层的温度波动在很大程度上是相互独立的。
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来源期刊
Journal of Food Process Engineering
Journal of Food Process Engineering 工程技术-工程:化工
CiteScore
5.70
自引率
10.00%
发文量
259
审稿时长
2 months
期刊介绍: This international research journal focuses on the engineering aspects of post-production handling, storage, processing, packaging, and distribution of food. Read by researchers, food and chemical engineers, and industry experts, this is the only international journal specifically devoted to the engineering aspects of food processing. Co-Editors M. Elena Castell-Perez and Rosana Moreira, both of Texas A&M University, welcome papers covering the best original research on applications of engineering principles and concepts to food and food processes.
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