Wang, Haoqi, Jin, Yi, Lu, Xiaoping, Dong, Liyang, Ma, Yaoshuai, Huang, Rongjie, Li, Hao, Sun, Chunya, Wang, Jie, Yang, Xinyu and Zhang, Shuai ORCID: https://orcid.org/0000-0002-9796-058X (2026) Multi-objective optimization method of operation parameters for large vertical mills based on combined agent model. Powder Technology, 468:121568. ISSN 0032-5910 (Print), 1873-328X (Online) (doi:10.1016/j.powtec.2025.121568)

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Abstract

A large vertical mill is a mineral grinding system. There are various measuring and monitoring operating points and multi-physics coupling, which means that optimizing its operating parameters is crucial for improving its system performance. This paper presents a combined agent model to optimize the system's multi-operation parameters. First, a numerical model of the particle fluid system is created using CFD-DPM, and the performance model of a vertical mill is developed based on factors such as production, specific surface area, and energy consumption. Next, a surrogate model is constructed by combining Kriging, polynomial response surface, and radial basis function. Based on this model, a multi-objective optimization framework is established. Finally, the LGM vertical mill is used to demonstrate the optimization. A comparison analysis reveals that the final product's output has increased by 0.78%, and its specific surface area has increased by 10.38%. Furthermore, the energy consumption has decreased by 13.51%.

Item Type:	Article
Uncontrolled Keywords:	numerical simulation, CFD-DPM coupling method, Rosin-Rammler distribution, combined agent model; multi-objective optimization
Subjects:	Q Science > Q Science (General) T Technology > T Technology (General)
Faculty / School / Research Centre / Research Group:	Greenwich Business School Greenwich Business School > Networks and Urban Systems Centre (NUSC) Greenwich Business School > School of Business, Operations and Strategy
Last Modified:	24 Jun 2026 15:15
URI:	https://gala.gre.ac.uk/id/eprint/52366

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