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Optimization design of cane sugar evaporative crystallizer based on orthogonal test and computational fluid dynamics
Author(s) -
Zhang Jinlai,
Meng Yanmei,
Wang Hui,
Yao Tao,
Yu Shuangshuang,
Chen Ji
Publication year - 2020
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.13355
Subject(s) - computational fluid dynamics , process (computing) , crystallization , mechanical engineering , process engineering , computer science , simulation , mechanics , engineering , chemical engineering , physics , operating system
This article describes an optimization design of a sugar evaporative crystallizer using numerical simulation experiments. Computational fluid dynamics (CFD) is used to simulate the circulation flow of sugar juice in the crystallizer, and the numerical experiments are designed according to orthogonal experiment matrix. First, based on the specific working characteristics of sugar evaporative crystallizer, major factors influencing the cane sugar evaporative crystallization process were identified. Then CFD software was utilized to establish various three‐dimensional CFD models of the sugar evaporative crystallization with different factors and levels. Statistics software (IBM SPSS) is used to analyze the CFD simulation results. In order to measure circulation velocity under different conditions, physical experiments were conducted in the experiment platform in our laboratory. The circulation velocity measured under the optimal condition was increased by 128%, and the crystallization efficiency could be guaranteed. Practical Applications Computation fluid dynamics (CFD) enables studying the details within the crystallizer, making the invisible become visible. The orthogonal test replaces all tests with partial tests. The orthogonal test coupled CFD technique can hugely decrease the cost of optimization design. The application of this method will benefit the optimization design of food engineering.