Multi‐objective optimization of cane sugar continuous crystallization system design based on computational fluid dynamics

Abstract

This work focused on improving circulation and mixing of the massecuite and reducing the energy loss in the cane sugar continuous crystallization system. The developed Computational Fluid Dynamics (CFD) model is based on the continuous crystallization system of a sugarcane mill in Guangxi, China and verified with the actual operation data. The calculated entropy production and pressure drop of the system are used as indices for assessing the performance of the system. Next, 350 CFD simulations are conducted in the parametric experiment platform with 9 parameters and produces a collection of data. Then based on the CFD dataset, the data‐driven model is employed for regression of the relations between key parameters and indices. The implemented data‐driven model is used for Non‐dominated Sorting Genetic Algorithm (NSGA‐II) to obtain the optimal result of Pareto frontier. CFD simulation with the optimized parameters reduces entropy by 9.76% and reduces pressure drop by 11.52%.