首页|Temperature digital twins model for blueberry pre-cooling based on micro-cluster method
Temperature digital twins model for blueberry pre-cooling based on micro-cluster method
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Objectives:In order to improve the prediction accuracy of forced-air pre-cooling for blueberries,a mathematical model of forced-air pre-cooling for blueberries based on the micro-cluster method was established.Materials and Methods:In order to determine the optimal micro-cluster model parameters suitable for forced air pre-cooling of blueberries,three factors controlling the micro-cluster geometry parameters were evaluated by 7/8 pre-cooling time,uniformity,and convective heat transfer coefficient.Results:It was found that the optimal values of the number of micro-clusters(n3),the distance between individual units within a micro-cluster(a)and the distance between micro-clusters(c)were 3,0.75,and 0.2,respectively.Under these optimal values,the temperature error of the micro-cluster method remained below 1 ℃,achieving highly accurate temperature predictions during the blueberry pre-cooling process.The re-sults showed that the micro-cluster method effectively solved the challenges of complex configuration,long simulation time,and low accuracy compared to the porous medium and equivalent sphere methods.Conclusion:Based on the above analysis,it can be concluded that the micro-cluster method provids a theoretical basis for optimizing forced-air pre-cooling processes and making informed control decisions.
Blueberrymicro-cluster methodforced-air pre-coolingtemperature digital twins
王达、杨相政、吴迪、贾连文、魏雯雯
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Jinan Fruit Research Institute of All-China Federation of Supply and Marketing Cooperatives,Jinan,China
College of Agriculture and Biotechnology,Zhejiang University,Hangzhou,China
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