Abstract
To simulate the change process of arbitrary physical properties with freezing time, this article first analyzes the current process of food freezing and refrigeration, and then numerically simulates this process in combination with supply chain theory to enhance the shelf life of food and save costs. The time-varying numerical simulation technology is applied to the self-developed simulator to analyze the food freezing and refrigeration process. The results show that comparing the water flooding characteristic curves of the two models, it can be seen that the freezing effect is weak due to less water production at the initial stage of production. When the water cut is lower than 30%, the curves of the conventional model and the time-varying model are exactly the same; as the freezing effect increases, under the same water content, the recovery degree of the time-varying model is higher, and this gap gradually increases as the production progresses. The final recovery factor of the time-varying model is 55%, which is 5% higher than that of the conventional model. Time-varying numerical simulation is more accurate than conventional numerical simulation in predicting waterflooding efficiency and ultimate recovery factor.
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References
Yenipazarli, A., Vakharia, A.J.: Green, greener or brown: choosing the right color of the product. Ann. Oper. Res. 250(2), 537–567 (2017)
Khaksar, E., Abbasnejad, T., Esmaeili, A.: The effect of green supply chain management practices on environment performance and competitive advantage: a case study of the cement industry. Technol. Econ. Dev. Econ. 22(2), 293–308 (2016)
Liu, Y., Zhu, Q., Seuring, S.: Linking capabilities to green operations strategies: the moderating role of corporate environmental proactivity. Int. J. Prod. Econ. 187, 182–195 (2017)
Xu, X., Luo, Q., Bai, Q.: Optimal strategy analysis of multi-level green supply chain under carbon emission constraints and carbon tradable mechanism. Ind. Eng. Manage. 21(1), 5–9 (2016)
Seth, D., Rehman, M.A.A., Shrivastava, R.L.: Green manufacturing drivers and their relationships for small and medium (SME) and large industries. J. Clean. Prod. 19(8), 1381–1405 (2018)
Chen, Y., Chang, T., Lin, C., et al.: The influence of proactive green innovation and reactive green innovation on green product development performance: the mediation role of green creativity. Sustainability 8(10), 96–106 (2016)
Lao, K.: Research on the influence mechanism of consumer innovation on green consumption behavior. Nankai Manage. Rev. 16(4), 106–113 (2018)
Liu, Y., Zhu, Q., Seuring, S.: Linking capabilities to green operations strategies: the moderating role of corporate environmental proactivity. Int. J. Prod. Econ. 18(7), 182–195 (2017)
Bai, C., Tang, J.: Game analysis of green supply chain cooperation among manufacturing-sales companies. J. Syst. Eng. 32(6), 818–828 (2017)
Zhu, Q., Li, X., Zhao, S.: Cost-sharing models for green product production and marketing in a food supply chain. Ind. Manage. Data Syst. 118(4), 654–682 (2018)
Qu, Y., Guan, Z., Ye, T.: Research on dynamic optimization and coordination of supply chain collaborative green innovation based on CVaR guidelines. Ind. Eng. Manage. 23(4), 78–79 (2018)
Hong, Z., Guo, X.: Green product supply chain contracts considering environmental responsibilities. Omega 83(3), 155–166 (2019)
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Hou, Y. (2021). Numerical Simulation Technology of Food Freezing and Refrigeration Process Based on Supply Chain. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Advances in Intelligent Systems and Computing, vol 1398. Springer, Cham. https://doi.org/10.1007/978-3-030-79200-8_94
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DOI: https://doi.org/10.1007/978-3-030-79200-8_94
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