Multi-objective optimization of stirring tank based on multiphase flow simulation

• Published in: Chemical engineering research & design Vol. 189; pp. 680 - 693
• Main Authors: Yao, Zongwei, Xu, Hongxu, Li, Jing, Xu, Tianshuang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2023
• Subjects: AHP; EWM; Kriging model; NSGA-II; Solid-liquid suspension; Stirring tank; NSGA-II; AHP; Stirring tank; Kriging model; EWM; Solid-liquid suspension
• ISSN: 0263-8762
• DOI: 10.1016/j.cherd.2022.11.043

Stirring tanks are regarded as pivotal equipment for solid-liquid suspension operations in industrial processes such as adsorption and crystallisation, and its performance is complex in relation to the pulp phase, structure and process conditions. However, the traditional design method for stirring tank structure is sophisticated and time-consuming, which greatly limits the design efficiency. To address the high cost and inefficiency of traditional design methods, this paper performed a multi-objective optimal design of stirring tank based on numerical simulation, surrogate model, NSGA-II, Entropy Weighting Method and Analytic Hierarchical Process. Firstly, the flow field state of stirring tanks with different structural dimensions and operating parameters was simulated with computational fluid dynamics (CFD), which was subsequently validated by Particle Image Velocimetry. Then, for the key parameters including stirring speed, stirrer diameter, stirrer height from the bottom and paddle pitch, experiments were designed using the Latin Hypercube method to establish a Kriging model based on the gained simulation data. Afterwards, the Pareto front was obtained from the optimization using NSGA-II with two objectives of stirring power and suspension uniformity. The result of Analytic Hierarchy Process and Entropy Weighting Method showed that the selected optimal solution can improve the suspension uniformity by 0.7 % while reducing power consumption by 48.3 % compared to the initial design. [Display omitted] •An multi-objective optimization model for stirring tank was developed.•Combination of Kriging and NSGA-II reduces the consumption of resources dramatically.•Balancing objective and subjective factors by integrating AHP and EWM.•The optimal solution reduces energy cost by 48.3 % at no loss in.